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A model of conceptual complexity Rank, Anders Dennis 1977

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A MODEL OF CONCEPTUAL COMPLEXITY by ANDERS DENNIS RANK B.Ap.Sc, University of British Columbia, 1970 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN THE FACULTY OF GRADUATE STUDIES (Department of Psychology) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA August, 1977 (£) Anders Dennis Rank, 1977 In p r e s e n t i n g t h i s t h e s i s in p a r t i a l f u l f i l m e n t o f the r e q u i r e m e n t s f o r an advanced degree at the U n i v e r s i t y o f B r i t i s h C o l u m b i a , I a g r e e that the L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and s tudy . I f u r t h e r a g ree t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y pu rpo se s may be g r a n t e d by the Head o f my Department o r by h i s r e p r e s e n t a t i v e s . It i s u n d e r s t o o d tha t c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l not be a l l o w e d w i t h o u t my w r i t t e n p e r m i s s i o n . Anders Dennis Rank Department o f P s y c h o l o g y  The U n i v e r s i t y o f B r i t i s h Co lumbia 2075 Wesbrook Place Vancouver, Canada V6T 1W5 Date 7. 1977 i ABSTRACT Various theoretical and experimental works in the fields of conceptual complexity, information processing, electroencephalography, and brain trauma are reviewed. A model of conceptual complexity is then derived which u t i l i z e s some of the viewpoints and data found in these works, and also i s mainly consistent with current knowledge about cognitive processes. A more detailed review of the conceptual complexity literature i s then presented, along with an analysis of the implica-tions of the present model with respect to that literature. Appendices contain other implications of the model in other fields, as well as an outline of a research program. i i TABLE OF CONTENTS Abstract L i s t of Figures Page i i v Introduction Review William T. Powers Aleksander R. L u r i a Schroder, Driver, and Streufert E. Roy John A Model of Human Information Processing Basic Outline Detailed Description Sensory buffers and output functions Comparison units for motor behaviour Programs Memory (a) Long-term memory (b) Short-term memory and the s e r i a l processor 44 The reorganization system 48 Information Usage 49 Perception 49 Motor behaviour 50 Thinking and decision-making 51 Conceptual Complexity 54 Detailed Model 55 Categorization complexity 55 Rule complexity 56 Decision-making complexity 57 Behavioural complexity 58 Hypotheses 59 Relationship to Conceptual Complexity L i t e r a t u r e 62 Tests 65 Categorization complexity 66 1 3 3 19 23 26 29 29 31 31 35 36 39 i i i TABLE OF CONTENTS (continued) Page Tests (continued) Rule complexity 67 Decision-making complexity 68 Behavioural complexity 69 Bibliography 70 Appendix A: Other Implications 78 Hierarchical, Automatic Programs and Normal Processing 78 Brain Plasticity and Specificity 79 Attitudes Measurement 81 Behaviour and Attitude Change 82 Appendix B: A Research Program 84 Overview 85 Physiology 89 Techniques 94 LIST OF FIGURES Page F i g u r e 1. A n e u r o n a l adder 6 F i g u r e 2. A n e u r o n a l s u b t r a c t o r . 7 F i g u r e 3. A n e u r o n a l a m p l i f i e r . 8 F i g u r e 4. A n e u r o n a l m u l t i p l i e r . 9 F i g u r e 5. (a) An example of a f i r s t - o r d e r c o n t r o l s ystem (b) An e q u i v a l e n t f l o w diagram. 10 10 F i g u r e 6. A b e h a v i o u r a l c o n t r o l u n i t u s i n g memories o f p a s t p e r c e p t u a l s i g n a l s as r e f e r e n c e s i g n a l s . 11 F i g u r e 7. The g e n e r a l o r g a n i z a t i o n o f t h e mind. 30 r This thesis i s an attempt to construct a model of the information processing functions which are salient to a discussion of conceptual complexity, mainly using ideas developed by Schroder, Driver and Streufert (1967), Powers (1973) and Luria (1973). Although the model, of necessity, describes1 many of the functions normally dealt with in the fields of perception, memory, cognition and so forth, i t i s not intended to be a definitive theoretical exposition of any or a l l of these more limited areas. Rather, the model is meant to show that a l l of these processes must be accounted for in any model which deals with a more global aspect of brain functioning such as conceptual complexity. By implication, such an integrative viewpoint must also be taken in other areas such as attitude change or attitude measurement, some of which are briefly discussed in the Appendices. Although I have attempted to make this model consistent with current models in the more speci-alized fields of psychology, i t s emphasis on the processes necessary to describe conceptual complexity w i l l occasionally put i t in conflict with these more circumscribed theories. These processes are defined in terms of the input data they work with, the kinds of transformations or decisions made from those data, and the various kinds of outputs pro-duced. Although the basic flow of processing in the model presented here i s computer-like, the phsyiological structure underlying these processes is hypothesized to use an analogue, rather than a d i g i t a l , process. In general, the model describes processes, not content. This means that attitude change might, for example, be described in terms of the temporal sequence of rule and memory usage and the comparison decisions 2 necessary to produce such change, but very l i t t l e w i l l be said about the actual content of such rules and comparisons. Only broad generali-zations can be made about such content, since in many kinds of processes i t w i l l be partly determined by the history and culture of the in d i v i -dual. In attitude change, for example, one person may mainly consult the opinion of experts, while another might pay the most careful atten-tion to the presumed wishes of his family and ancestors. The process of information search occurs in both people, but the content of that search may be highly individualistic. It i s , of course, d i f f i c u l t to distinguish between processes determined genetically and those deter-mined environmentally; for the sake of simplicity, I w i l l assume that the potential for the development of the processes described in this model is genetically present in a l l human beings, although specific environmental influences may accelerate, retard, or even prevent their appearance in certain situations. The model w i l l provide an outline of the processes present in the brain, a brief description of the neural wiring producing such processes, and an outline of possible equivalences between these processes and the physical organization of the brain. The purposes of such a model are four-fold: (1) to make more clear the relationships among, and the common features of, a number of diverse fields of psychology in order to fa c i l i t a t e the use of information from one f i e l d to another, (2) to pro-vide insight into the processes underlying many content areas, (3) to develop new paradigms for the study of process structures, and (4) to give impetus to the development of other processing models at the same general level of analysis. 3 REVIEW The following review of the most pertinent theories which led to the present model i s not intended to be an exhaustive look at the work that has been done on information processing. Nor is i t intended to be an especially c r i t i c a l review of this work. Rather, i t i s presented with the purpose of explaining briefly some of the concepts which w i l l be incorporated into the model in the following sections, and indicating why I found them insufficient in themselves for the kind of model de-veloped here. These theories do not represent major departures from the mainstream of thought in their areas but are presented as repre-sentative samples of current thinking which were most germane in the development of the present model. William T. Powers Powers (1973) has provided a hypothesis about the functional sig-nificance of several kinds of elementary neuron circuits found in the nervous system. In addition, he has conceptualized a hierarchy of con-t r o l systems which are comprised of various of these elementary circuits, and which in turn comprise a l l the processing faculties of the brain. I w i l l begin with a look at the elementary neuron circuits that Powers described. In the Introduction, I mentioned that my model assumes analogue, rather than d i g i t a l , computing elements. This idea i s taken directly from Powers, who f i r s t explained precisely how such elements could operate. He f i r s t notes that a neuron seems to operate in a binary 4 mode in the sense that the neuron fires whenever an excitation threshold is exceeded, and the discharge shape, timing, and magnitude are always invariant under different excitations. However, this does not neces-sarily imply that the signal operated upon by the neuron consists of these binary impulses. Rather, many psychologically relevant percep-tual phenomena have been shown to be correlated with the frequency of f i r i n g of a neuron. For example, the f i r i n g rate of a temperature sensor in a cat depends smoothly upon the temperature of that neuron (e.g., Dodt and Sotterman, 1952). Note that the exact dependency of f i r i n g rate to input stimulation i s not important in this argument, so long as some regular dependency exists. In the nervous system, signals, especially to muscles, are usually transmitted not just by single neurons, but by parallel bundles of re-dundant fibers. A good s t a t i s t i c a l average may then be made of the fi r i n g frequency of this bundle, making this signal a reliable one to use to carry information in the nervous system. The discrete binary impulses, on the other hand, are subject to vagaries in timing due to the individual nature of the neurons producing them and the varying lengths of the axons conducting them, which would make their use as the basic information unit impossible in the nervous system. Therefore, Powers defines the neural current as "the number of impulses passing through a cross-section of a l l parallel redundant fibers in a given bundle per unit time" which i s to be the basic information unit of the nervous system. The next step is to show that neurons using this frequency informa-tion can perform the basic operations needed by a computing system. In 5 Figures 1 through 6, I w i l l reproduce Powers' drawings of the connections needed to perform such operations with only the following general comments: f i r s t , that the law of conservation of energy (and current) does not apply since the required energy is supplied to the system along the whole length of the axon by the surrounding tissue allowing each of the branches in Figure 3, for example, to carry a neural current equal to I. This i s unlike a made-made electrical c i r c u i t , where each branch would have to carry a current of second, that since a com-puter can and does perform a l l necessary operations using only adders and subtracters, presumably the nervous system could too. The symbol +o indicates an excitatory synapse, -# indicates an inhibitory one. In a l l cases, i t i s the neural current which is being operated on, rather than each discrete impulse. Multiplication occurs when two inpulses must arrive simultaneously in order for the c e l l to f i r e . Powers notes that integrators and differentiators can also be simply constructed; I w i l l omit these circuits from discussion since the foregoing i s certainly sufficient to form a f a i r l y efficient com-puting system. The next important concept is that of negative feedback control. "Feedback" i s a word which is often used very loosely to describe any kind of information returned from some process or event, but which does not necessarily have any effect on that process or event. As used here, feedback w i l l always refer to negative feedback: that i s , to information about a process or event which i s passed back almost im-mediately to a control point in order to influence future actions in 6 Figure 1. A neuronal adder. The frequency I 3 equals the sum of the input frequencies I, and I 2 since both synapses are excitatory (Powers,1973, p. 27.) I , A neuronal subtractor. The frequency 1^ is approx-imately equal to the-,4i^f.er.ence>-of the input frequencies 1^ and I,, since one synapse i s inhibi-tory (Powers, 1973, p. 28.) 8 Figure 3. A neuronal amplifier. The input i s divided into 3 branches, each of which carries a neural current of I,. The output of the neuron Is therefore three times I, (Powers, 1973, p. 29.) 9 Figure 4. A neuronal multiplier. This c e l l has an elevated f i r i n g threshold which requires two excitatory impulses to arrive simultaneously in order to in i t i a t e f i r i n g (Powers, 1973, p. 30.) 10 Figure 5. a. b. An example of a first-order control system. An equivalent flow diagram. ( Refer to Powers, 1973, p. 43 and p. 83. ) 11 H I O H E . R O R D E R S or m addre&S &\qnol l3' perceptual switcU ^p.s.^^-''>0—— o^-c memory switck CO m. s ) -Punc.T"ioi\ 7~TT L O W E . R O R D E R S ress Figure 6. A behavioural control unit using memories of past perceptual signals (m) as reference signals (r). ( Powers, 1973, p. 221.) 12 that process or event in a mathematically determined manner such that errors are reduced; i t w i l l be the key concept in describing how motor behaviour is controlled. It is analogous to the term "feedback" used in servo-mechanism theory (e.g., D'Azzo and Houpis, 1966). The main elements of a negative feedback control unit (servomechanism) are shown in Figure 5. Suppose the effector is a muscle. Then the feedback system works' in the following way to create the proper muscle tension: the brain provides a neural current to energize the muscle, whose tension is a function of the magnitude of the neural current reaching i t (Milner, 1970). The signal provided by the brain is called the reference signal, r_. The output of the muscle is i t s tension, o^. A special stretch receptor in the muscle tendon (the Golgi tendon receptor) generates a perceptual feedback signal, j), whose magnitude (frequency) is directly related to the amount of muscle tension. This signal is sent back to the comparator (the spinal motor neuron), in such a way that i t is sub- tracted from the reference signal. Thus only the error signal, e_, is really used to control the muscle tension. Suppose that, due to some disturbance, the muscle has not con-tracted by the amount required by the reference signal. Then the feed-back signal _p_, which depends upon that contraction, w i l l be rather smaller than i t should be. Since p_ is subtracted from _r at the motor neuron, the effect i s to make the error signal, e_, a bit larger, increasing the muscle tension. Similarly, i f the muscle should contract a bit too much, the effect of the subtraction r_ - _p_ w i l l be to reduce e_ somewhat, and therefore to reduce the muscle tension. The "negative" 13 part of "negative feedback control" refers to this subtraction: only i f the feedback is negative w i l l this control system work properly. Note that "error" in this case does not mean "mistake": the control system stabilizes to some steady state in which e_ is some constant non-zero value. Only i f the muscle is completely flaccid i s e = 0. Simplifying things somewhat, the steady-state conditions of the feedback loop are such that e_ = _r - p_, and p_ = ke, where k i s a con-stant known as the Loop Amplification Factor. The effect of varying k is to regulate the sensitivity of the system: as k increases, the system controls errors more accurately. Using Powers' example (p. 64), i f k = 10 and a muscle system is disturbed by a force of 10 pounds, the muscle effort countering this disturbance w i l l be 9.1 pounds. If k = 100, however, the countering effort w i l l be 9.9 pounds. (Note that although the greater part of a disturbance may be countered auto-matically, only by changing r_ w i l l i t be completely countered.) Unfortunately, i t is not possible to work through the effects of such a disturbance in a simple manner using the steady-state equations above because they do not take into account the time-dependencies existing in the system. Disturbances do not occur instantaneously, they occur over some f i n i t e period of time. Similarly, the neural currents p_, _r, and e^  cannot change instantaneously, but rather vary according to the physical limitations of the system. The exact mathe-matical description of a feedback system depends on knowing the nature of such time-dependencies. In the case of inorganic systems such as those described by D'Azzo and Houpis (1966), these dependencies are determined by the physical laws pertaining to the operation of the 14 elements of those systems. Such a des c r i p t i o n i s currently impossible for organic systems because we lack d e t a i l e d knowledge of t h e i r method of operation. We are now ready to discuss Powers' model of the organization of the human nervous system. He conceives of a hierarchy of nine behavioural control systems; each co n t r o l l e v e l works to adjust i t s output functions (e.g., muscles i n Figure 5) so that the perceptual, signals reaching i t are "correct", r e l a t i v e to the reference signals supplied to i t by a higher-order c o n t r o l system. Each l e v e l of the hierarchy receives information of a c e r t a i n kind, integrates that information i n c e r t a i n ways, and passes i t upwards to the next highest l e v e l . Level One: Intensity The lowest l e v e l system controls and perceives i n t e n s i t y of neural current. The perceptions involved a r i s e d i r e c t l y from sense receptors such as the Golgi tendon receptor; an example of a co n t r o l l e d quantity would be muscle tension. Powers i d e n t i f i e s the p h y s i o l o g i c a l units for t h i s l e v e l with the s p i n a l motor loop for motor perception and c o n t r o l , and the r e t i n a f o r v i s u a l perception. Level Two: Sensation or Vector Control F i r s t order perceptual signals are combined by weighted summation c i r c u i t s to produce a s i g n a l which can be thought of as an n-dimensional vector, where n i s the number of f i r s t - o r d e r signals involved. This vector need not represent any " r e a l - l i f e " p h y s i c a l quantity, but Powers considers that i t may do so i n the case of kin e s t h e t i c c o n t r o l and v i s u a l perception: f o r example, some "vectors" may represent j o i n t r o t a t i o n angles. These vectors are the r e s u l t of second order input 15 f u n c t i o n s — t h e u n i t s f o r w e i g h t e d s u m m a t i o n : t h e y a r e a n a l o g o u s t o t h e c u r r e n t p r o d u c e d b y t h e G o l g i t e n s o n r e c e p t o r s — t h e f i r s t o r d e r i n p u t f u n c t i o n s . F o r m o t o r b e h a v i o u r , P o w e r s i d e n t i f i e s t h e s e i n p u t f u n c t i o n s w i t h t h e s e n s o r y n u c l e i o f t h e b r a i n s t e m . S i m i l a r l y , t h e s e c o n d o r d e r o u t p u t f u n c t i o n s a r e i d e n t i f i e d w i t h t h e m o t o r n u c l e i o f t h e b r a i n s t e m . L e v e l T h r e e : C o n f i g u r a t i o n C o n t r o l T h e s e c o n d - o r d e r s y s t e m s p r o d u c e p e r c e p t u a l s i g n a l s w h i c h a r e p a s s e d t o t h e c e r e b e l l u m a n d t h a l a m i c a r e a s . T h e i n t e g r a t i o n o f t h i s v e c t o r i n f o r m a t i o n i s c o n s i d e r e d t o r e s u l t i n i n f o r m a t i o n a b o u t c o n - f i g u r a t i o n s : f o r e x a m p l e , k i n e s t h e t i c a l l y i t p r o v i d e s d a t a o n t h e p o s i t i o n a n d o r i e n t a t i o n o f t h e b o d y ; v i s u a l l y , i t w o u l d p r o v i d e d a t a a b o u t o b j e c t f o r m s . T h e p r e c e e d i n g t h r e e l e v e l s a r e t h e e a s i e s t t o c o n c e p t u a l i z e a n d t h e l e a s t o p e n t o a r g u m e n t . P o w e r s c o n s i d e r s t h e n e x t t w o l e v e l s t o b e t h e f i n a l s t a g e s o f p e r c e p t i o n a n d m o t o r b e h a v i o u r . T h e f o u r l e v e l s a f t e r t h a t d e a l w i t h a c t i v i t i e s o f t h e b r a i n w h i c h d e a l w i t h t h e p r o -c e s s i n g o f t h e s e p e r c e p t i o n s . L e v e l F o u r : C o n t r o l o f T r a n s i t i o n s T h i s l e v e l p e r c e i v e s a n d c o n t r o l s c h a n g e s o f p e r c e p t i o n , f o r e x a m p l e , v i s u a l m o t i o n o r t h e c h a n g e i n t o n e o f a m u s i c a l n o t e . I t i s v e r y t e n t a t i v e l y i d e n t i f i e d b y P o w e r s w i t h t h e s e c o n d s o m a t i c s e n s o r y a r e a o f t h e c e r e b r a l c o r t e x . L e v e l F i v e : C o n t r o l o f S e q u e n c e A t t h i s l e v e l t h e k e y v a r i a b l e i s t h e t e m p o r a l o r d e r o f e v e n t s . T h i s l e v e l c o u l d , f o r e x a m p l e , b e t h e o n e a t w h i c h c o m p l e x m o t o r 16 sequences such as the motions necessary for writing are "remembered" and could reasonably be the level at which particular phoneme orders are recognized and given word meanings. Powers feels that there i s some evidence (Bickford, Dodge, and Vilhein, 1960) that such a level may exist just below the precentral .cortex. Level Six: Control of Relationships This level analyzes the conjunction of certain perceptions or events as being examples of some set or rule. These relationships may be logical (identifying both grass and trees as being plants), or i l l o g i c a l (identifying bad luck with the breaking of a mirror). Level Seven: Control of Programs At this level, l i s t s of relationships, motor sequences, etc. are called up sequentially, but with choice points inserted in some places to allow various actions to occur depending upon the outcome of a previous decision, as in the ways we might search for a missing set of keys. Level Eight: Control of Principles This level employs heuristic principles to decide which set of programs might be appropriate to run in a given situation, as in a chess player's use of the heuristic "keep strength in the centre" to decide which of several possible gambits (programs) to employ. "Strength" is not a well-defined relationship; rather i t i s a principle embodied in several programs. Level Nine: Control of Systems Concepts Essentially, some sort of common pattern i s recognized in different principles, and given an identity of i t s own. Such an idea as 17 "nationalism", for example, might be an example of an i n t e g r a t i o n of various p r i n c i p l e s into a whole, which upon examination, may have l i t t l e real-world existence. It i s the way. perhaps, that each i n d i -v i d u a l orders the " r e a l i t y " of h i s world. Another important concept i s that of reorganization. The r e -organization system's function i s to randomly change already e x i s t i n g programs and h i e r a r c h i e s , or create new ones; without a reorganization system, there can be no learning of* processes. Again, i t i s a negative feedback system i n the sense that i t works to minimize the d i f f e r e n c e between a set of reference signals and a set of perceptions. Powers considered these reference signals to be r e l a t e d to the i n t r i n s i c v a r i a b l e s of the organism: that i s , those g e n e t i c a l l y determined variables which a f f e c t the p h y s i o l o g i c a l s u r v i v a l of the organism, and which have g e n e t i c a l l y determined reference l e v e l s . The means by which such reorganization occurs i s unknown at present, although Powers believes that i t may operate, at l e a s t i n part, by a l t e r i n g synaptic c o n d u c t i v i t i e s . Powers also believes that consciousness i s perception and awareness r e s u l t i n g from the monitoring of £ signals from various systems by the reorganization system since t h i s f i t s the i n t r o s p e c t i v e sensation of "perceiving perception". Note that reorganization i s r e a l l y more d e s c r i p t i v e of a b r a i n process necessary for learning than of some ph y s i c a l organization to a f f e c t that process — Powers recog-nizes that t h i s process could be an i n t e g r a l part of the very systems i t acts upon, or could be some manner of higher order control system. Powers, and I, have l e f t for the end the d i f f i c u l t question of 18 where those higher order reference signals originate. He feels that the most elegant and parsimonious approach i s to envisage memory being in some way associated with each neural comparator. This memory con-sists of a number of addressable codes which refer to past perceptual signals, and those codes are probably comprised of chemical changes within the comparator system, perhaps in accordance with the RNA theory of Hyden (1969). When the appropriate address memory signal arrives at the memory unit, the corresponding code i s "played back", causing a duplicate of some formerly experienced p_ signal to be generated as an _r signal and transmitted to the comparator. Thus memory, too, i s hierarchically organized, for each memory unit w i l l code information that has been integrated in a manner appropriate to that level of pro-cessing. The output function of such a system, then, must consist of the mechanism to produce the address signals to be sent to the next lower level control system memories. Last, notice in Figure 6 that the control system has switches associated with the perceptual tract and the memory tract. These allow for control (both switches vertical), passive observation (perceptual switch vertical, memory switch horizontal), automatic be-haviour (perceptual switch horizontal, memory switch vertical), and imagination (both switches horizontal). I have used selected portions of Powers' theory to explain in detail the operation of some parts of my model. By i t s e l f , however, i t tends to leave some questions unanswered. What exactly does a "program" consist of? How do the various hierarchies operate when, for example, behaviour and cognition programs are running simultaneously? 19 How do short-term and long-term memory f i t in? And how exactly might reorganization operate? Aleksander R. Luria A.R. Luria (1973) has developed a model of the relationship between the physical parts of the brain and their roles in brain func-tioning by studying patients who have suffered brain lesions. The classical approach has been to identify very specific processing func-tions with certain areas of the brain because lesions of those areas cause performance decrements of those functions (e.g., Kleist, 1934). Luria argues that this approach is subject to error for two reasons. First, lesions in many different areas may cause the same specific functional decrement (singing a b i l i t y , for example, could be affected by lesions to either the auditory cortex or the sensorimotor area controlling the larynx); and second, a lesion in one place causes many specific decrements, only some of which are lik e l y to be investigated by the experimenter (a blind person, for example, w i l l have many per-formance decrements, such as walking, piano playing, etc.). This, in turn, implies that the brain i s not organized into l i t t l e boxes, each of which performs a certain specific function (such as addition, or recognition of melodies), but rather i s organized into a complex functional system in which many areas play a role in any single kind of processing. The way to learn about this organization, he says, i s to observe the common factors underlying the complete syndrome of problems arising from any given lesion. At this point, i t i s interesting to note that some of the syndromes 20 he presents as examples demontratlng such common factors seem to be almost identical to some of the hierarchical levels proposed by Powers. For example: kinaesthetic apraxia (inability to place a limb in the correct position), corresponds to Level Three of Powers' scheme; spatial apraxia (inability to perform movements in the correct direction and orientation, although Luria sees i t as inab i l i t y to place the limbs in the correct position in space) corresponds to Level Four; kinetic apraxia (inability to perform smoothly coordinated motor movements) clearly corresponds to Level Five; and apraxia of goal-directed action (loss of purpose) would correspond to some of the yet higher levels. Luria, however, does not clearly present these as being functional pro-cesses (and certainly not hierarchical ones), but rather deals with such symptoms individually, as they occur in specific areas such as speech, letter recognition, and so forth. Three points are to be noted in this: f i r s t , that independent evidence presented in support of a completely different theory is also not inconsistent with Powers' theory; second, that finding the., "common factors" underlying lesion syndromes i s clearly open to more subjectivity than we would like to see as Powers and Luria postulate different factors from essentially similar data; and third, that Luria appears to f a l l into exactly the trap he warns up to avoid — that of interpreting lesion evidence in too narrow a way. He does, however, consider a more general level of functional organization consisting of three parts: f i r s t , "a unit for regulating tone or waking" (mainly the reticular formation), second, "a unit for obtaining, processing, and storing information from the outside world" 21 (the l a t e r a l areas of the neocortex or the p o s t e r i o r convex surface of each hemisphere i n c l u d i n g the o c c i p i t a l , temporal, and p a r i e t a l r e g i o n s ) , and t h i r d , a u n i t f o r programming, r e g u l a t i n g and v e r i f y i n g mental a c t i v i t y (the f r o n t a l and p r e f r o n t a l areas). In a d d i t i o n , each of these u n i t s c o n s i s t s of three h i e r a r c h i c a l c o r t i c a l zones: f i r s t , the primary p r o j e c t i o n areas, which exchanges in f o r m a t i o n w i t h the periphery of the second; the secondary p r o j e c t i o n - a s s o c i a t i o n area, which processes i n f o r m a t i o n or creates programs, and t h i r d , the t e r -t i a r y zone of overlapping, which i n t e g r a t e s the operation of many d i f -f e r e n t processing areas. A l l three p r i n c i p a l b r a i n u n i t s work i n t e r -dependently although a l l three sub-units of each need not be i n opera-t i o n at a l l times. L u r i a goes on to describe i n d e t a i l the s p e c i f i c e f f e c t s that l e s i o n s have on v i s u a l , a u d i t o r y , speech, motor, memory, and i n t e l l e c -t u a l f u n c t i o n i n g , but the i d e n t i f i c a t i o n of these e f f e c t s i n terms of t h e i r r e l a t i o n to h i s general model of processing i s too vague to be of use i n understanding the b r a i n ' s system. In e f f e c t , there are so many sub-processes which must operate w i t h i n one of h i s process cate-g o r i e s that we are l e f t i n the dark as to how things work — d e s c r i -bing a b r a i n f u n c t i o n as one which "creates programs" i s not very h e l p f u l , we know that programs must be created, but we don't know how or i n what s i t u a t i o n s . Because of the vagueness of h i s process d e s c r i p -t i o n s , they w i l l not be r e f e r r e d to o f t e n i n the model I am presenting. Rather, reference w i l l be made to L u r i a ' s compendium of l e s i o n syn-dromes (which may be thought of as content d e s c r i p t i o n s ) where they bear d i r e c t l y on e i t h e r Powers' model, as I have shown e a r l i e r , or on 22 the physiological features of my model. There is one processing distinction which Luria makes, however, that is pertinent to the following model: that of successive versus simultaneous synthesis, terms similar in meaning to serial versus parallel processing. An overview and extension of this idea i s found in a paper by Das, Kirby and Jarman (1975). Luria says that simultaneous syn-thesis, occurring the occipital-parietal region, is involved in three areas: direct spatial perception, creation of Gestalt images from con-secutive presentation or parts of the image, and complex intellectual processes. Successive processing, occuring in the fronto-temporal regions, is used in analysis of speech, writing, music, etc. Das et a l . (1975) assume that direct perception and the creation of Gestalt images can be performed in either a simultaneous or a suc-cessive manner, depending on the exact nature of the problem and the individual's personal preference, which may be molded by social and genetic factors. They believe that complex intellectual behaviour is more flexible, using either or both kinds of processing in order to solve the problem most effectively. For example, they factor-analyzed the scores on a number of cognitive tests arid found that two factors usually emerge, one corresponding to tasks performed in simultaneous fashion, the other to those performed in a successive manner. They also found that which kind of processing was used by an individual on a given task depended on several variables, including cultural back-ground and educational experience. The distinction between simultaneous and successive processing w i l l be taken up in the model presented here, but worded in a different, and more specific, manner. 23 Harold M. Schroder, Michael J. Driver and Siegfried Streufert Schroder, Driver and Streufert (1967) provide an interesting analysis of memory and processing functions, in that i t relates i n -ternal processes to relatively easily observable external behaviours. Schroder, Driver and Streufert, like myself, have attempted to develop a process, rather than a content, model but have tried to restrict themselves to dealing only with what we might c a l l high-level "idea" processing; that i s , they do not deal with the i n i t i a l processing necessary for translating elementary perceptions into recognizable thoughts, with memory process or emotions, nor with motor behaviour. Rather, they theorize about the way in which "thoughts" (which they loosely categorize as attitudes, decisions and judgements) are related to one another in memory, and how various ideas are combined and in-tegrated in decision-making. They postulate two interdependent factors underlying such informa-tion processing: the number of dimensions along which an "idea" i s conceptualized, and the kind of rules used to integrate those dimensions. An integration index can then be derived which measures the complexity of the integration rules which an individual uses in processing informa-tion about some idea. Because of the different circumstances under which the dimensions and rules pertaining to those different ideas are learned, this index i s content-specific in that an individual i s lik e l y to process different ideas using rules differing in complexity. Some persons, however, w i l l have higher average integration indices than others. This index of conceptual complexity may be measured by means of 24 the Paragraph Completion Test, designed to determine the various d i -mensions that people use to characterize certain ideas, and the nature of the rules used to combine those dimensions. A very simple integra-tion structure would be one which analyzes the dimensions according to a single fixed rule, without alternatives or conflict. A somewhat more complex structure would be able to organize the dimensions in at least two alternative ways, but would have no overall rule which related those two alternate organizations; thus there is a choice in deciding what to think about an idea, but no sense of those choices being part of a larger idea. A reasonably complex structure has, in addition to the features already discussed, some means of comparing different organization rules and integrating them into more general rules. If those rules, in turn, are subject to being interpreted as being part of an even more general rule that may be generalized to many situations in complex ways then a very high level of conceptual complexity has been attained. Clearly this could become an in f i n i t e regression of rule upon rule; in practice, the integration index is judged according to a fixed set of c r i t e r i a as to the number and kind of integrations, and the underlying continuous nature of conceptual complexity i s understood. The most important thing about these c r i t e r i a i f that they are, or should be, content-free; only the structure of rules is analyzed, not the content. At this point i t is useful to note the basic similarity between this model of conceptual complexity and Powers' more general model: both are hierarchical in nature and both postulate that various kinds of transformations and integrations are performed on information in 25 order to generate new meaning from i t . Powers, however, most clearly describes this hierarchy for perceptual processes. He i s self-admlttedly vague in his description of his highest two levels, which deal with principles and systems concepts. Schroder et a l . address themselves exclusively to these .high levels of thought, postulating a similar kind of hierarchical organization for them. Unfortunately, they do not deal with this hierarchy in terms of either the control of mentation or i t s relationship to a general processing model, leaving i t s function some-what obscure. Although this i s a useful approach to a d i f f i c u l t subject, some vexing problems remain. One is that the theory does not sufficiently differentiate between the process of categorizing information and that of making decisions using that information. Categorization (discri-mination of the dimensions of a stimulus and determination of i t s associations) necessarily involves rules for determining which cate-gories a certain stimulus f i t s into. Is this rule usage, then equi-valent to "decision-making"? In this theory, the situation i s unclear. Another problem i s that rules must have content, at least at the level of processing that this theory deals with. It i s easy to think of simple rules that have complex content; for example, "There are two sides to every question." Judging by structure, i t is a clear case of an inflexible rule, and therefore i t must be rated as conceptually simple. Judging by content, however, i t is equally clearly a case of a rule allowing for at least two viewpoints and therefore i t i s moderately complex. Thus although the content of the subject under discussion should rightfully be ignored, the content of the rules used to process 26 i d e a s about t h a t s u b j e c t cannot be. A l t h o u g h S c h r o d e r e t a l . p r o v i d e an ad hoc way o f s c o r i n g s u c h r e s p o n s e s , t h e y do n o t c o n s i d e r s u c h problems i n t h e i r t h e o r y . A t h i r d p r o b l e m i s t h a t a p e r s o n ' s b e h a v i o u r may be a t a d i f f e r e n t l e v e l o f c o m p l e x i t y f r o m h i s i n f o r m a t i o n p r o c e s -s i n g . The model p r e s e n t e d h e r e a t t e m p t s t o p a r t l y c l e a r up some o f t h e s e q u e s t i o n s , and d e t a i l e d d i s c u s s i o n o f them w i l l be f o u n d i n t h e f o l l o w i n g c h a p t e r s . E• Roy Jo h n The n e u r o p s y c h i a t r i s t , E. Roy John ( 1 9 7 6 ) , has d e v e l o p e d a model o f b r a i n p r o c e s s i n g w h i c h has s e v e r a l f e a t u r e s i n common w i t h t h a t o f Powers, n o t a b l y t h o s e o f i n f o r m a t i o n l e v e l h i e r a r c h i e s , and an i n f o r m a -t i o n f l o w d i a g r a m w h i c h c o u l d e a s i l y be i n t e r p r e t e d i n t h e c o n t e x t o f r e f e r e n c e s i g n a l s , a l t h o u g h John does n o t see i t i n q u i t e s u c h a mechanis-t i c way. The p r o c e s s i n g h i e r a r c h y d e f i n e d by John i s more p h i l o s o p h i c a l , and f a r l e s s m e c h a n i c a l , t h a t t h a t o f Powers. I n a d d i t i o n , t h e e x a c t d e t a i l s o f t h e p r o c e s s e s i n v o l v e d , w h i c h a r e v e r y e x p l i c i t l y s t a t e d by Powers f o r a t l e a s t h i s f i r s t f i v e l e v e l s , a r e l e f t u n d e f i n e d by J o h n , so t h e f o l l o w i n g b r i e f d i s c u s s i o n w i l l o n l y o u t l i n e t h e g e n e r a l I n a t u r e of t h e h i e r a r c h y . H i s f i r s t i n f o r m a t i o n l e v e l i s t h a t o f s e n s a t i o n s , and i s c l e a r l y i d e n t i c a l t o Powers' f i r s t l e v e l o f i n t e n s i t y . J ohn's second l e v e l i s t h a t o f p e r c e p t i o n s , w h i c h g i v e meaning t o s e n s a t i o n s i n terms of s u b - c o n s c i o u s memories o f s i m i l a r p a s t e x p e r i e n c e s . T h i s l e v e l , a l t h o u g h c o m b i n i n g l e v e l s two t h r o u g h f i v e o f Powers, d i f f e r s 2 7 f r o m Powers' p e r c e p t u a l l e v e l s i n one major r e s p e c t : Powers wo u l d argue t h a t n e u r o n a l c i r c u i t s f o r t h e c r e a t i o n o f such p e r c e p t i o n s be-come " w i r e d - i n " a f t e r some l e a r n i n g p e r i o d , and would n o t i n v o l v e t h e c o m p a r i s o n o f i n p u t p e r c e p t i o n s w i t h remembered ones. John's t h i r d l e v e l i s t h a t o f c o n s c i o u s n e s s : h e r e t h e v a r i o u s p e r c e p t i o n s a r e u n i f i e d w i t h a p p r o p r i a t e memories, e m o t i o n s , d r i v e l e v e l s , and programs i n t o what John c a l l s "a sequence o f m u l t i v a r i a t e 'frames'". T h i s would seem t o be r o u g h l y a n a l o g o u s t o Powers' l e v e l s ; s i x and se v e n , a l t h o u g h t h e d i s t i n c t i o n between a u t o m a t i c p r o c e s s i n g and p r o c e s s i n g r e q u i r i n g r e o r g a n i z a t i o n ( t h e c r i t i c a l key i n Powers' d e f i n i t i o n o f awareness) i s n o t made. John's f o u r t h l e v e l d e f i n e s s u b j e c t i v e e x p e r i e n c e as b e i n g t h e v a r i o u s meanings w h i c h can be a p p l i e d t o t h e same p e r c e p t i o n s i n d i f -f e r e n t c i r c u m s t a n c e s , and c o n s i s t s o f s u c h t h i n g s as t h o u g h t s , p l a n s , e m o t i o n s , shapes, and sounds. S i n c e i t mixes so many d i f f e r e n t k i n d s o f "meaning", i t i s i m p o s s i b l e t o f i t i n t o Powers' scheme v e r y w e l l , where t h e d i f f e r e n t i a l p r o c e s s i n g o f meaning c o u l d p r e sumably be a t a l m o s t any l e v e l e x c e p t t h e f i r s t . The f i f t h l e v e l i n John's t h e o r y i s t h e s e l f , w h i c h c o n s i s t s o f an a c c u m u l a t e d memory o f an i n d i v i d u a l ' s l i f e h i s t o r y o f s u b j e c t i v e e x p e r i e n c e s . John's s i x t h l e v e l , s e l f - a w a r e n e s s , i s t h e r e a l - t i m e i n s t a n t a n e o u s p e r c e p t i o n o f s u b j e c t i v e e x p e r i e n c e i n t h e l i g h t o f memory o f p a s t e x p e r i e n c e s , and i s n o t c l e a r l y d i f f e r e n t i a t e d f r o m t h e l e v e l o f s u b j e c t i v e e x p e r i e n c e . N e i t h e r o f t h e s e l e v e l s has a d i r e c t e q u i v a l e n t i n Powers' p r o c e s s model, perhaps because t h e y seem t o d e a l more w i t h c o n t e n t t h a n w i t h p r o c e s s i n g . 28 If we disregard the discrepancy between John's and Powers' des-cription of when certain information integrations take place, and whether they are conscious processes or not, one part of the processing flow scheme appears very similar in the two models: John says that present perceptions are compared to memories of past sensations in order to build up the multivariate frame in which appropriate plans or programs are contained; Powers says that the reference signals control-ling lower levels consist of the memories of past perceptual signals. They disagree mainly on whether memories are needed to build up "subjective experience" or "meaning" in ordinary situations. John goes on to present a fascinating body of EEG data related to experiments in simple classical conditioning paradigms, discrimination paradigms, and perception paradigms. Although these data can be made to f i t John's model, I believe that they f i t more clearly into my extension of Powers' model, which has more potential for making specific physiological predictions. Discussion of these data w i l l be found in Appendix B entitled "A Research Program." 29 A MODEL OF HUMAN INFORMATION PROCESSING Basic Outline The general nature of the model is shown in Figure 7. It depicts a processing system u t i l i z i n g hierarchically-organized perceptual systems, motor output systems, programs, and long-term memory. The portions depicted in blue represent information in various forms, items in red represent programs, and portions in black represent processing areas. Information from the environment is received through sense receptors, whose only output consists of stimulation intensity data. This information is passed upwards through interconnected net-works of neurons which form the perceptual input functions, labelled (1) in Figure 7. These input functions consist of units made up of adders, subtractors, and so forth, as well as units acting as logical gates such as AND, NOR, etc. These integrated data are then available at the second level of processing, which may be thought of as an input buffer (2). Similar transformations provide higher level integrations of the data as they progress upwards through the system. Some portion of this information is available in short-term memory.(3) which holds i t for a few seconds without need for rehearsal. Processing of the information in the buffers, or of information drawn from long term memory (4), is accomplished by running one or more programs (5), whose exact features depend upon the system (motor, memory, etc.) being operated upon. In general the function of a program is to provide the signals necessary for certain kinds of i n -formation comparisons to occur. Programs are hierarchically organized; 30 Figure 7. The general organization of the mind ( refer to text for details. ) 31 each section of a program deals with information at a specific level of analysis. The number of levels encompassed by different programs varies. Many programs can run simultaneously (simultaneous synthesis) unless some new programs must be created by a reorganization system, or some programs which have not been well learned are running. In either case, parts of the new or poorly-learned programs must run in a serial processor (6) which i s closely related to STM (in Luria's terms, this i s successive synthesis). Ordinarily, however, different programs run in various different areas of the brain, rather than a l l running in some central computing area. Motor behaviour i s organized and controlled hierarchically by comparison units (7) operating on the principle of negative feedback control. "Thinking", which involves memory manipulation programs, may not be so organized, depending on the nature of the program. The kinds of data stored i n LTM are information received from various buffers, programs, and "rules" — that, rules for the construc-tion of programs. These data are also present at various levels of integration, and data about similar events may be present in several areas of the brain, i f those data have been stored during the running of different programs. Detailed Description Sensory buffers and input functions The data at each level of analysis are present in the form of neural currents originating from input function networks. These input functions consist of organized units of neural computing units (adders, 32 AND-gates, etc., as discussed previously) and are functionally and physically separate for different perceptual modalities, at least at low levels. The f i r s t order units are simply the various kinds of somatosensory receptors, such as those recognizing pressure, heat, red light, and so forth. The only information they transmit is about the intensity of stimulation — as the stimulation decreases, the neural current pro-duced by the receptor decreases (see P. Milner, 1970, pp. 161-163, for some examples). Note that this represents information coded in an analogue manner. These intensity data are combined in the second level systems to create new kinds of information. Powers believed that this information represents the orientation of the i r r i t a t i n g stimulus, but other kinds of meaning may also be extracted at this stage. For example, work done on animals using microelectrode recording from individual nerve cells has shown that several kinds of processing are performed in the retina-Maturana, Lettvin, McCulloch, and Pitts (1960), found that frog retinas contain groups of cells for detecting boundaries between areas of brightness contrast, others for detecting small, dark objects, and s t i l l others for responding to moving edges. Weisel and Hubel (1966) found groups of cells in the lateral geniculates of monkets which selectively responded only to spots of light, and others which only fired when stimulated by bars of light oriented in a particular direction. Although similar studies are d i f f i c u l t to perform on human beings, these data suggest that a particular layer of the retina or of the brain could conceivably be responsible for detecting several features of the 33 input. What exactly, then, determines whether one input function is at a higher level than another? The answer lie s in the exact nature of the neural connections to those input functions. If the unit for detecting contours receives i t s input signals from the output of the orientation detectors, then i t is a third level detector. If, on the other hand, i t receives i t s input directly from the rods and cones, without any mediation from the orientation detectors, then i t is a second level detector. Note that i t i s possible to do sophisticated pattern recognition (such as recog-nizing "things that are red, hollow, and asymmetrical") using only connections from the f i r s t order receptors. The number of inter-connections necessary for such a task, however, would be immense; i t is much less wasteful of neural space to recognize "red", "hollow", and "asymmetrical" at lower levels and use signals from those recog-nition units as the input to a higher level analyzer. In effect, this means that we may make educated guesses as to what functions are served at various processing levels, but that we cannot determine these functions on logical grounds alone. Only an investiga-tion of the neural circuits w i l l t e l l us what kinds of data are pro-cessed at any given level, and the nature of this processing w i l l un-doubtedly be different in different sense modalities. Note that the advantage of needing fewer connections when pro-cessing hierarchically i s partially offset by needing more time to analyze higher order information, since the information must pass through more computing units. This timing difference could be detected i f low order outputs were directly available to a program. If information 34 from a low-level system could be acted upon before i t passed upwards to a higher-level system, then reaction times to low integration level stimuli (e.g., intensity) should be lower than reaction times to higher level stimuli (e.g., shapes). Work on the reaction time paradigm by Ward and Wexler (1976) and Neisser (1963) shows that such direct access is probably possible (this direct access is often termed "multiple readout"). The Ward and Wexler study also indicates that curved shapes may also be processed at the same level as' straight lines. The hier-archy proposed by Powers seems mainly concerned with the processing of spatial information (orientation, movement, and so forth); this may well be true of the visual and kinesthetic systems. Other systems, however, undoubtedly perform their own specialized integrations. I make no predictions as to the exact nature of such integrations, nor as to how many levels of buffers there may be, although five perceptual levels would seem to be a reasonable minimum. The use of the term "buffer" implies at least short term storage of the information present at a given level of analysis. In.. Hunt's (1973) discussion, he writes that information in a given buffer is compared to stored LTM information; i f a match i f found a signal is passed upwards to the next level buffer. If such searches occurred at a l l buffer levels some storage of informa-tion would certainly be necessitated. What determines when a buffer changes i t s information i f a match i s not found is not adequately dealt with by Hunt. In the present model, temporal storage of information is not required for processing to occur at low levels. The term is re-tained since a given output device w i l l continue sending a signal up-wards so long as the appropriate input stimuli are present, rather than 35 j u s t when the s t i m u l i f i r s t appear ( r e l y i n g on higher l e v e l s to remember that those s t i m u l i are present). In t h i s l i m i t e d sense only i s there storage of information i n the low l e v e l buffers. In summary, the sensory buffers and input functions form a feature analysis system for the input from somatosensory receptors. Information present i n the form of neural currents at each buffer represents the recognition of features appropriate to the l e v e l of i n t e g r a t i o n of that buffer, and i s a v a i l a b l e both for program processing at that l e v e l and further i n t e g r a t i o n by a higher l e v e l system. Comparison units for motor behaviour As explained e a r l i e r , the comparison units u t i l i z e negative feed-back to compare perceptual input signals to reference signals i n order to c o n t r o l a set of output functions (see Figure 5). The output functions of one l e v e l generate the reference signals for the next lower l e v e l . The evidence presented by Powers for the existence of such control systems for generating motor behaviour i s very convincing (e.g., Bickford et a l . , 1969; Hess, 1957; Ranson and Clark, 1947). One of the features of such systems, however, i s that they control variables which are smoothly continuous, such as limb p o s i t i o n or speed of finger movement. Other systems that the brain must have, such as memory storage and search, l o g i c a l thinking, and program c o n t r o l , seem less amenable to such h i e r a r c h i c a l control networks. I believe t h i s i s because such systems ei t h e r work i n a more binary fashion than the motor system (as i n s e l e c t i n g one program o_r another program, rather than con-t r o l l i n g a smooth range of programs), or they operate at only one l e v e l of processing. How such systems might work w i l l be discussed i n more 36 detail in the section entitled "Information Usage". Programs Programs are ordered sets of instructions and choice points for organizing the computing units of the brain in such a way as to perform the required processing. They are hierarchically organized so that any given program may contain instructions for directing processing at a number of levels of integration, and may perform multiple operations at any one level. In addition, there may be several sub-programs available at any given level; a sub-program also consists of an ordered set of instructions and choice points, but is available as one of several options within the main program. Instructions for choosing which one is to run depend on the information input to a sub-program selection mechanism. A general program for opening a door, for example, w i l l contain sub-programs for different muscle movements depending on whether the door is hinged, sliding, or revolving; this i s an example of a f a i r l y high-level program. The program responsible for controlling respiration operates at a lower level than the one for opening doors, and may not have any sub-programs. Consider a program for directing a sequence of behaviours such as moving one's arm in small circles. This would require motor control for roughly the following control levels: motion (circles), configura-tion (arm straight), orientation (arm out to the side), and intensity (small angles). Remember that each control level generates the re-ference signals for the next lower level, and that Powers considers the reference signals to be address memory signals. I then identify programs to be ordered sets of memory address locations for generating 37 the correct kind and sequence of those reference signals, and ordered sets of computing address locations for organizing the logical units necessary to select sub-programs. Within a given program, those address locations are associatively linked and hierarchically ordered, from the most general addresses (those corresponding to the highest level systems) to the most specific ones (those corresponding to the lowest level systems). In addition, sub-programs are associatively linked to their main programs. This w i l l work i f memory consists of past perceptual signals, as Powers suggests, and i f i t is organized hierarchically and is physically present at the control systems. This mechanism of memory storage pro-vides a clue for the distinction between programs which seem to run automatically and simultaneously with other automatic programs (such as those controlling breathing, heart rate, etc.) and those which appear to run in successive steps and need more conscious mediation (such as learning to walk). If memories and their associated addresses may be stored at the site of integration then programs, which consist of similar addresses may also be stored there. I thus identify simultaneous and parallel processes as those which have run often enough that their address.lists are stored at the site of their operation — i.e., they have been learned. Different programs for different muscle groups may then easily run at the same time without interference, because they are running in physically separate areas of the brain rather than in a central computing unit. If two programs use the same set of muscles, and therefore the same program locations, they cannot run simultaneously; but there is nothing to prevent the same physical location from being 38 the storage place f o r addresses coded to several d i f f e r e n t programs. L i f t i n g one's arm, for example, i s part of many d i f f e r e n t programs. Therefore, s i m i l a r reference s i g n a l addresses w i l l be stored at the same l o c a t i o n f o r those programs, d i f f e r i n g only i n t h e i r a s s o c i a t i v e l i n k with higher l e v e l addresses. These l i n k s i d e n t i f y the programs of which each address i s a part. The as s o c i a t i v e l i n k , of course, must be some address code r e f e r r i n g to the address of the next higher computing l e v e l of the program or perhaps to the highest, most general one. The l o g i c a l units f o r s e l e c t i n g sub-programs (choice points) are also set up at the s i t e of the appropriate computing l e v e l . The decision-making part of the program which accomplishes t h i s does not select the addresses of memorized reference signals. Rather i t must somehow set up adders, AND-gates, and so f o r t h from some stock of neural ti s s u e which i s not being used for perception or motor co n t r o l , perhaps by a l t e r i n g synaptic thresholds or influence ( p o s i t i v e or negative e x c i t a t i o n ) at those s i t e s . Again, these c i r c u i t s become permanent, and the sub-program s e l e c t i o n becomes automatic, when that s e l e c t i o n mechanism has been run many times. Many kinds of programs besides motor programs may become automatic, of course. The analyzer responsible for constructing words from patterns of sounds, for example, runs automatically. Note that, although auto-matic ., t h i s i s probably a sequential analyzer; t h i s points out the fa c t that an automatic program can run i n p a r a l l e l with other programs, but the actual operation of that program may have to be sequential because of the nature of i t s task. 39 It should be noted that many reference signals, especially for behaviour, are undoubtedly supplied genetically (this i s certainly a strong point in favour of memory being coded in RNA or in proteins, which are synthesized using RNA codes). When I speak about detecting error during the running of. a program, i t should be understood that one kind of error could be a result of deviation from those genetic references (Powers' "intrinsic error"). Memory The identification of memory units with the units responsible for generating the reference signals at various levels of processing neces-sitates the hypothesis of a distributed, hierarchical type of long-term memory. Other workers have proposed similar models based mainly on the way in which language i s analyzed (e.g., Hunt, 1971; Lindsay and Norman, 1972). The derivation of similar models from very different viewpoints would seem to be a strong point in favour of this general view of LTM. A. Long-term memory Hierarchical memory consists of two things: the content of the memory — that i s , the thing being remembered — and a set of addresses for that memory. There are three basic kinds of content: information, programs, and rules for building programs. In addition, there are two basic kinds of addresses: one that i s used by the brain to "replay" the memory when that address signal arrives at the memory storage unit, and one or more others to associate that memory with other memories at the same level at higher or lower stages of integration. If, as seems reasonable, memory is coded chemically, then the content and the 40 addresses are l i k e l y to be all stored together in one master chemical code. This is not essential to the present model, however. The addresses which associate a memory with other memories at the same or different levels are i n i t i a l l y constructed during the running of the program that led to the original set of perceptions. The number of branches of that program at various levels and between levels of analysis is reflected in the number of associative addresses of that memory. For example, think of the word "pedestrian". No doubt a number of associations spring to mind, related perhaps to walking, store fronts, and so on. Now imagine that you are driving a car, and think of "pedestrian" again. The associations this time are probably very different from those you f i r s t thought of, i l l u s -trating how memory associations may be linked to the programs which were running when those memories were stored. The generation of address codes during program operation amounts to a kind of "content addressing", since different pieces of informa-tion having similar content w i l l be processed by similar programs, or even within the same main program. Such content addressing is consis-tent with the theories of other workers (Norman, 1968; Shiffrin and Atkinson, 1969), but is discussed here with emphasis on the programs that produce i t . The last example clearly shows that memory, whether hierarchical in nature or not, does not contain one fixed set of associations for any given subject or idea. Rather, i t shows that memory is redundantly stored in many physical locations in the brain since i t is stored during the operation of different programs in different brain areas. Each of 41 t h e s e redundant "memories", however, a r e s u b t l y d i f f e r e n t f r o m each o t h e r i n t h a t t h e i r a s s o c i a t i o n s a r e d i f f e r e n t . How t h e n do t h e two v i e w s o f " p e d e s t r i a n " e v e r become r e c o g n i z e d as b e i n g r e l a t e d t o each o t h e r , g i v e n t h a t i t i s i m p o s s i b l e t o d r i v e and t o s i t r e a d i n g a paper a t t h e same time? C l e a r l y , i t w o u l d be d i f f i c u l t f o r t h e programs f o r t h o s e two a c t i o n s t o become a s s o c i a t e d , t h u s l e a d i n g t o a memory a s s o c i a t i o n . The answer, I t h i n k , i s t h a t we must p o s t u l a t e t h e p r e s e n c e o f some s p e c i a l programs i n t h e memory p r o c e s s i t s e l f . F i r s t , f o r r e a s o n s w h i c h p r o b a b l y r e l a t e t o e v o l u t i o n a r y s u r v i v a l , a u t o m a t i c programs have e v o l v e d f o r c h e c k i n g i n c o m i n g p e r c e p t i o n s a g a i n s t a l r e a d y s t o r e d i n f o r m a t i o n t o d e t e c t c o n s i s t e n c i e s and i n c o n s i s t e n c i e s between t h e two. T h i s i n v o l v e s b o t h LTM and STM. E x a c t l y what c o n s i s t e n c i e s a r e checked i s a moot p o i n t , b u t i t i s r e a s o n a b l e t h a t v i s u a l and a u d i t o r y p a t t e r n m a t c h i n g w o u l d be among t h e f i r s t t o be e v o l v e d . Note t h a t two p e r c e p t i o n s o f t h e same ev e n t w h i c h have been formed d u r i n g t h e o p e r a -t i o n o f d i f f e r e n t programs w i l l n e v e r be i d e n t i c a l t o one a n o t h e r , and so p e r f e c t matches w i l l n o t be found. Y e t some a s p e c t s o f t h o s e p e r -c e p t i o n s w i l l be s i m i l a r , and r e m a i n r e l a t i v e l y unchanged by t h e p r o -gram a s s o c i a t i o n s — such as the v i s u a l f e a t u r e s o f a p e d e s t r i a n — and so w i l l be a v a i l a b l e f o r m a t c h i n g . C h e c k i n g f o r " u n u s u a l " e v e n t s w o u l d be a n o t h e r u s e f u l program. Second, c o n s c i o u s a t t e n t i o n i s some-t i m e s d i r e c t e d towards two p i e c e s o f i n f o r m a t i o n , f o r any o f a v a r i e t y o r r e a s o n s , and a d e l i b e r a t e a t t e m p t i s made t o see i f any c o n s i s -t e n c i e s e x i s t . Such c o n s i c o u s c h e c k s w o u l d most l i k e l y o c c u r a t h i g h l e v e l s o f p r o c e s s i n g , u s i n g s o p h i s t i c a t e d c o m p a r i s o n r u l e s . To d e c i d e 42 that "the moon i s made of rock", and "the moon coalesced from a gas", are not inconsisent pieces of information required very complicated comparisons indeed f o r the man who f i r s t thought of the dust cloud theory of planetary formation. One very common reason for making such a conscious comparison i s when the same name i s associated with two hitherto separate pieces of data. This often gives r i s e to an "aha" response. Since the language analyzer and the set of rules of s c i e n t i f i c deduction are both programs, these l a s t two examples can be seen as s p e c i a l cases of the general way i n which memories are stored. Memories only become associated when they are rel a t e d by some program. Memory r e t r i e v a l operates by means of a r e t r i e v a l program which operates i n an asso c i a t i v e and constructive manner. Two main modes of operation are possible: automatic information search and non-automatic constructive search. Automatic information search may r e s u l t when a person i s asked a question r e l a t e d to data which has an as s o c i a t i v e address (or addresses) d i r e c t l y r e l a t e d to the question asked, as when a h i s t o r i a n i s asked "When did J u l i u s Caesar reign?" A non-historian, i f unable to access the same information d i r e c t l y , may then engage i n the constructive task of r e t r i e v i n g t h i s information by, for example, remembering when other r u l e r s governed before and a f t e r J u l i u s , and i n f e r r i n g the dates required. Some kinds of constructive sub-programs appear to work p a r t i a l l y automatically, however, such as those which search out the correct a s s o c i a t i v e addresses. Note that the re l i a n c e of memory search programs on asso c i a t i v e addresses means that these programs are r e l a t e d to the input programs running when the information 43 was memorized. Although automatic and non-automatic search strategies are similar in nature to the episodic and semantic memories, respec-tively, described by Tulving (1972), two differences exist. First, non-automatic searches in the present model need not rely exclusively on semantic processes as in Tulving's model. Second, the result of an automatic search w i l l reflect the encoding bias of the program which stored that information, but i t w i l l not be biased by the search i t -self; such bias is more lik e l y in the non-automatic search — a reverse of Tulving's prediction. Forgetting may occur both in STM and LTM. Many researchers have developed models of forgetting involving decay and interference pro-cesses in STM, and storage and retrieval mechanisms in LTM (see Lindsay and Norman, 1972 for a review). In addition, I wish to propose that two other mechanisms may be responsible: either the original per-ception was not stored (at least at the level the person is trying to remember) or the information is not sufficiently differentiated in terms of the programs associated with i t when i t was stored. As an example of the f i r s t process, a person may remember that a square was presented tachistoscopically during an experiment several weeks previously, but be unable to remember i t s size, colour, or orientation. Only the rela-tively high level meaning — square — was stored. In many situations only the highest level perceptions may be stored. It is reasonable to suggest that attentional processes are important in the selection of perceptions to be stored, but no detailed model of attention w i l l be described in this model. The second process probably operates in situations like the typical serial learning experiment. Words are 44 forgotten because the learning program i n operation during the task contained no processes f o r di s t i n g u i s h i n g the various words from one another. If some words are d i f f e r e n t from the others (e.g., a d i f -ferent colour) they are remembered much better (see Kohler, 1940, for a review), since now d i f f e r e n t programs, having d i f f e r e n t associations, are used during the processing. Although t h i s d i f f e r e n t i a t i o n may appear to be a property of the stimulus, rather than the program used to process i t , I believe that the work done by L u r i a (1969) with a mnemonist shows that the converse i s true. L u r i a found that the mnemonist he studied t y p i c a l l y memorized l i s t s by creating very e l a -borate image associations between the items; these associations seem much more l i k e programs for processing the items than properties of the items themselves. In general, of course, i d e n t i f y i n g f o r g e t t i n g with aspects of the programs processing the data i s consistent with my t h e o r e t i c a l linkage between programs and LTM. B. Short term memory and the s e r i a l processor The r o l e of STM (a memory of l i m i t e d capacity and duration; e.g., M i l l e r , 1956; Peterson and Peterson, 1959) i s not quite as clear as that of LTM, since the h i e r a r c h i c a l nature of the buffers, programs, and LTM does not l o g i c a l l y imply any p a r t i c u l a r structure f o r STM. Indeed, i t would seem that an organism could survive without any STM processing whatever, merely coding a l l information into LTM. Figure 7 shows STM as encompassing portions of some of the higher l e v e l s of the input buffers. How many buffers are a v a i l a b l e i n STM, and how much of each buffer i s a v a i l a b l e , i s currently a subject of controversy. Whatever i s the case, i t i s assumed here that t h i s 45 information is available to the serial processor (SP). Programs which have not run often enough, or because they have just been created, run in a sequential manner. The basically serial nature of STM has been investigated mainly in the context of sentence analysis, by such researchers as Lindsay and Norman (1972). In my model i t is assumed that sentence analysis has to be not only a serial program due to the nature of the task, but must run in the SP using information held in STM, because no one sentence is analyzed often enough for that analysis to become automatic (although sentences like "How are you?" may be exceptions). One function of STM, then, can be to hold information long enough for special purpose programs such as the sentence analyzer to work on i t . Another special program which seems to run in STM is selective attention. Although selective, or "channel", attention could be present in the input buffers, some workers believe that attention mechanisms work only in STM, meaning that STM encompasses a l l of a buffer (e.g., Shiffrin and Grantham, 1974; Shiffrin, Pisoni and Castaneda-Mendez, 1973). The studies by Shiffrin et a l . are worthy of further scrutiny, • however. Both studies presented near-threshold signals masked by white noise. The subjects had to detect whether and where the signal was present. In the Shiffrin and Grantham study, a signal was pre-sented to the subjects to either the eye, ear, or skin. In the simul-taneous condition, any of the sensory modes could contain the signal within 500 msec of the subject's pressing a start button; in the suc-cessive condition, the signal would be present either visually in the 46 f i r s t 500 msec, auditorily in the second 500 msec, or t a c t i l e l y in the third 500 msec. A pre-STM attention effect was considered to be the presence of a better hit rate in the successive condition than in the simultaneous condition; such an effect was not found, and the authors concluded that attention must operate in STM, rather than before i t . The second study was similar, except that signals were presented to one or the other ear. The assumption made by Shiffrin et a l . is that the identification process should be more accurate in the absence of any irrelevant infor-mation, so that when attention is focused exclusively on a single modality (by using pre-STM attention) the hit rate would be higher. However, since STM was far from overloaded in this paradigm and the SP was probably not involved, there seems to be no particular reason to believe this. Ths signal recognition could well be part of an auto-matic STM search search program for "unusual" events, the memory load was not impaired. Indeed, Eijkman and Vendrik (1965) found precisely this. There was no difference between attending to two modalities (either of which could contain a signal) and attending to only one (but without switching, as in the Shiffrin et a l . studies). This is not intended to resolve the question, as a great deal of inconclusive work has been done on this topic. I merely wish to leave open the possibility that STM only encompasses part of a buffer, i.e., that attention is a pre-STM effect, quite possibly performed by the SP. The "multiple read-out" feature -discussed earlier indicates that i t i s possible for STM to operate in several buffer levels; but perhaps i t i s only the SP which does so. The capacity of STM is usually con-47 sidered to be about 5 to 9 "chunks" of information (e.g., M i l l e r , 1956; Simon, 1975); i n the present model i t i s hypothesized to be the number of addresses which may be held i n STM. Thus a chunk i s a general address for a piece of information, and contains the code for the pro-gram which analyzed that information, as explained e a r l i e r . A chunk can contain d i f f e r e n t amounts of information according to the program which coded i t . The s e r i a l processor i s an area of brain ti s s u e which can be set up to run novel programs to analyze the information i n STM. Besides being l i m i t e d by STM capacity i n the amount of information i t can handle, i t i s also presumably l i m i t e d i n the number of program steps i t can perform i n p a r a l l e l , perhaps to as few as one step. Since no one seems to have tested STM during the running of more than one pro-gram, as opposed to running d i f f e r e n t programs sequentially, however, the exact nature of the SP and i t s r e l a t i o n s h i p to STM i s quite vague. It i s even possible that several STM's or SP's are a v a i l a b l e i n d i f f e r e n t areas of the brain. The s p l i t - b r a i n work by Sperry (1964), for example, could be interpreted as evidence f or STM associated with both v i s u a l and motor areas. Since a program consists of addresses, however, and since STM can only hold about 5-9 addresses, I suggest that the number of novel program steps which can be generated at any one time i s also 5-9. Some of them are presumably executed by the SP, while the others are held by STM. The higher l e v e l program (address) for generating these steps, however, may need to be stored as w e l l , thus further reducing the STM capacity. 48 T h e r e o r g a n i z a t i o n s y s t e m T h e r e o r g a n i z a t i o n s y s t e m i s r e s p o n s i b l e f o r t h e c r e a t i o n o f n e w p r o g r a m s . T h e s e n e w p r o g r a m s m a y d i r e c t p e r c e p t i o n , b e h a v i o u r , o r i n f o r m a t i o n c o m p a r i s o n s , a n d c o u l d , o f c o u r s e , l a t e r b e c o m e a u t o m a t i c . S i n c e n o v e l p r o g r a m s a r e b e i n g r u n , t h e r e o r g a n i z a t i o n s y s t e m m u s t r u n t h e s e p r o g r a m s i n t h e S P . T h i s i m p l i e s t h a t o n l y p a r t o f a n e w p r o g r a m c a n b e l e a r n e d a t a t i m e , w h i c h i s c e r t a i n l y c o n s i s t e n t w i t h c o m m o n k n o w l e d g e . T h e S P m u s t c r e a t e t h e s e p r o g r a m s a c c o r d i n g t o s o m e s e t o f r u l e s o f i t s o w n . R e o r g a n i z a t i o n o c c u r s w h e n a s e r r o r s i g n a l f r o m s o m e p r o g r a m o r s u b - p r o g r a m e x c e e d s s o m e c r i t i c a l a m o u n t , a n d t h e r e a r e n o m o r e p r o -g r a m s a v a i l a b l e u n d e r t h e g e n e r a l a d d r e s s a t w h i c h t h e e r r o r o c c u r r e d . S i n c e p r o g r a m s a r e o r d e r e d s e q u e n c e s o f a d d r e s s e s , s e l f - g e n e r a t e d r e o r g a n i z a t i o n m u s t b e t h e g e n e r a t i o n o f d i f f e r e n t a d d r e s s o r d e r s , a n d / o r t h e g e n e r a t i o n o f a d d r e s s l i s t s f r o m s o m e c o n t e n t a r e a p r e -v i o u s l y u n a s s o c i a t e d w i t h t h e p r o b l e m a t h a n d . T h e f i r s t c o r r e s p o n d s t o " t r y i n g t h i n g s a d i f f e r e n t w a y a r o u n d " ; t h e s e c o n d t o " t r y i n g s o m e t h i n g c o m p l e t e l y n e w " . T h e s e n e w a d d r e s s e s m a y b e g e n e r a t e d e i t h e r r a n d o m l y o r t h r o u g h t h e u s e o f s o m e p r o g r a m f o r m u l a t i o n r u l e s . T h e s e r u l e s , n a t u r a l l y , a r e l i k e h i g h e r - l e v e l p r o g r a m s , t h e o n l y d i f f e r e n c e b e i n g t h a t t h e y d o n o t r u n a u t o n a t i c a l l y . R e o r g a n i z a t i o n m a y a l s o o c c u r i f o n e c a n l e a r n t h e n e w p r o g r a m b y w a t c h i n g t h e b e h a v i o u r o f o t h e r s , o r b y b e i n g e x p l i c i t l y t o l d t h e c o r r e c t p r o g r a m ; t h e s e w a y s , h o w e v e r , m u s t n e c e s s a r i l y g e n e r a t e o n l y h i g h - l e v e l r e o r g a n i z a t i o n . L o w e r - l e v e l c h a n g e s m u s t b e e f f e c t e d b y t h e i n d i v i d u a l ( f o r e x a m p l e , w e m a y b e t o l d t h e p r i n c i p l e s o f d r i v i n g a c a r , b u t w e m u s t p r a c t i c e 49 a l l the behaviours ourselves). Reorganization w i l l end when the error signal drops below the c r i t i c a l value, E. The value of E w i l l be different in different content areas, and in different individuals. Reorganization is clearly the key to learning, but i t s mechanism is the most unclear of anything in this model. Children certainly find learning a new program to be very rewarding (e.g., Bower, 1974), but adults appear to find i t more d i f f i c u l t and aversive, perhaps be-cause more systems become interrelated, and changing one implies a need to change-many others as well. Information Usage  Perception Perception programs control the operation of the input functions in the buffers. These input functions abstract "meaning" from lower order signals from the somatosensory system. Most of these programs are "hard-wired", especially at the lower levels. That i s , they are genetically predetermined and highly resistant to change, although they may need certain environmental conditions in order to develop properly. The organization of visual perception in detecting contours, movement, and colour mixes, for example, appears to be virtually identical in a l l individuals i f one disregards acuity. Some higher level integrations, such as perceiving perspective appear to be either learned or dependent on exposure to the correct environmental conditions to bring out the hard-wired capability (see Deregowski, 1972, for a review). It does not appear that we can easily modify the action of perceptual programs at low levels, but that may be because we seldom 50 need to do so. In unusual situations, such as when wearing prism goggles which invert the visual f i e l d , i t appears that a slow, i n -complete, modification of these processes does occur (e.g., Kohler, 1962). When such modification becomes automatic, i t must be because the input functions have been reorganized. At higher levels, more programs and integrations are possible. We may see a picture as a random pattern of dots un t i l we are told that i t really represents a picture of a tree — and a tree appears. At f i r s t , of course, this may be a memory process such as template matching (see Neisser, 1967, for a review), but i t can easily become an automatic process i f we see similar pictures again and again. The change to automatic integration implies a direct modification of the high level perceptual program. As discussed earlier, the way in which information associations are formed is determined by the program running at the time. In a l l but the most unusual situations, these associations are relatively high level ones in the perceptual system. Motor behaviour A sub-program at a given level of motor control w i l l use perceptual and memory information at that same level of analysis both for the control operation and for making decisions about program switching. That information, however, w i l l consist of data which have become associated with the program then running, and hence the details they contain w i l l tend to be those relevant to the program. Other details w i l l tend to be ignored and lost. In addition, the relevance of this detail to any other program w i l l tend to be missed since i t w i l l not 51 n e c e s s a r i l y produce e r r o r i n the motor output. For example, the sub-programs a s s o c i a t e d w i t h the perception of a pedes t r i a n to a d i r v e r do not i n v o l v e paying a t t e n t i o n to the pedestrian's f a c i a l expression. The d r i v e r might then e a s i l y miss the pedestrian's expression of alarm as he watches the d r i v e r run a red l i g h t . That same expression would not go unnoticed to someone speaking to the p e d e s t r i a n , s i n c e f a c i a l expressions are data a s s o c i a t e d w i t h the program of "conversation". The a c t u a l feedback mechanism of behaviour i s considered to be as discussed by Powers. Thinking and decision-making Thinking and decision-making are defined as the process and output of conscious memory c o n t r o l programs running i n the STM and SP f o r r e t r i e v i n g and comparing i n f o r m a t i o n , r e s p e c t i v e l y . The program choice p o i n t s which s e l e c t between sub-programs are not considered i n . t h i s d i s c u s s i o n because the choices are performed a u t o m a t i c a l l y and uncon-s c i o u s l y . "Consciousness" i s then defined as being those processes performed i n the SP. "Awareness" c o n s t i t u t e s the inf o r m a t i o n momen-t a r i l y i n STM. Since the SP i s only part of STM, t h i s i m p l i e s that awareness completely subsumes, but i s not l i m i t e d t o , consciousness. Using these d e f i n i t i o n s w h i le assuming that a t t e n t i o n i s a post-STM process creates a problem when t r y i n g to answer questions l i k e , "Why am I not always aware of my f e e t , but I am when I t h i n k about them?" I f awareness c o n s i s t s of eve r y t h i n g i n STM, and STM contains a l l the informa t i o n i n a l l of the b u f f e r s , or at l e a s t i n those r e -c e i v i n g somatosensory i n f o r m a t i o n , then we should be "aware" of our feet a l l the time. Several r e s o l u t i o n s are p o s s i b l e . A t t e n t i o n may 52 be a pre-STM e f f e c t , p e r h a p s p a r t l y d i r e c t e d by t h e SP, d i f f e r e n t m o d a l i t i e s may be d i r e c t e d p r e f e r e n t i a l l y i n t o STM ( f o r example, I seem t o be more e a s i l y and more c o n t i n u a l l y aware o f my e n t i r e v i s u a l f i e l d t h a n o f my a u d i t o r y f i e l d ) ; o r t h e r e may be STM's o f d i f f e r e n t c a p a c i t i e s f o r d i f f e r e n t k i n d s o f i n f o r m a i o n . The d e f i n i t i o n s above a r e , o f c o u r s e , r a t h e r a r b i t r a r y ; but i t seems u s e f u l t o d i s t i n g u i s h between t y p e s o f p r o c e s s e s and o f i n f o r m a -t i o n w h i c h a r e somewhat d i f f e r e n t i n out i n t r o s p e c t i v e awareness, and w h i c h , t h e r e f o r e , may a l s o be c r e a t e d by d i f f e r e n t p r o c e s s e s . Powers (1 9 7 3 ) , f o r example, a l s o makes t h i s d i s t i n c t i o n , h o l d i n g awareness t o be t h e r e c e p t i o n o f h i g h - l e v e l . . p e r c e p t u a l s i g n a l s , and c o n s c i o u s n e s s t o be t h e m o n i t o r i n g o f t h o s e s i g n a l s by t h e r e o r g a n i z a t i o n system. Hunt ( 1 9 7 1 ) , however, does n o t make t h i s d i s t i n c t i o n , c o n s i d e r i n g a t t e n t i o n and c o n s c i o u s n e s s t o be t h o s e p r o c e s s e s w h i c h a r e b e i n g p e r -formed by a C e n t r a l P r o c e s s i n g U n i t (CPU), and i d e n t i f y i n g t h e CPU c l o s e l y w i t h language a n a l y s i s . However, t h e s e d i f f e r e n c e s i n v i e w p o i n t about c o n s c i o u s n e s s and awareness a r e s l i g h t , and p e r h a p s o f o n l y m i n o r i m p o r t a n c e , e x c e p t i n how t h e y r e l a t e t o STM. A t what p r o c e s s i n g l e v e l do t h i n k i n g and d e c i s i o n - m a k i n g o c c u r ? P h i l o s o p h i c a l l y , t h e y seem h i g h e r t h a n p e r c e p t i o n , motor c o n t r o l , o r memory s t o r a g e ; but t h e y may n o t be h i g h e r i n terms o f p h y s i c a l o r g a n i -z a t i o n . I t i s d i f f i c u l t t o c o n c e p t u a l i z e e i t h e r o f them as n e g a t i v e -f e e d b a c k c o n t r o l u n i t s , e x c e p t i n t h a t t h e y w i l l b o t h o c c u r as a r e s u l t o f e r r o r s i g n a l s o r i g i n a t i n g when memory s e a r c h programs d e t e c t i n -c o n s i s t e n c i e s , o r when a d e c i s i o n i s c a l l e d f o r . I d e n t i f y i n g t h i n k i n g w i t h p r o c e s s i n g done by a l anguage a n a l y z e r seems to o s i m p l e : f o r 53 example, people solve some kinds of visual problems by moving images around in their imaginations. It seems more reasonable to consider the language analyzer as an area separate from STM and the SP, which may be used in certain conscious processes. Thus, although the lan-guage processor may well use STM and the SP, i t is not identical to either of them. Indeed, Hunt says that some rules available in lan-guage analysis may not be available in<.certain other problem-solving tasks. Our definitions of consciousness and awareness certainly imply that the information these functions use may be at different levels. Perhaps i t is easiest to conceptualize their processes as being at different levels as well, with the exception that the reorganization system must be at a higher level than anything i t reorganizes. Powers' definitions of eighth and ninth level systems (control of principles and control of system concepts, respectively) sound like functions which would control our thinking, but perhaps they merely represent different kinds of programs available for conscious processes. 54 CONCEPTUAL COMPLEXITY The above model i s u s e f u l i n b r e a k i n g down c o n c e p t u a l c o m p l e x i t y i n t o more s p e c i f i c p r o c e s s i n g components t h a n has been done b e f o r e . R a t h e r t h a n s e e i n g c o m p l e x i t y i n terms o f o n l y d i s c r i m i n a t i v e and/or i n t e g r a t i v e components, I p r o p o s e t h a t a t l e a s t f o u r s e m i - i n d e p e n d e n t components a r e i n v o l v e d i n p r o c e s s i n g c o m p l e x i t y . These components a r e c a t e g o r i z a t i o n , d e c i s i o n - m a k i n g , r u l e , and b e h a v i o u r a l c o m p l e x i t y . These f o u r components r e l a t e t o v a r i o u s s t a g e s i n t h e p r o c e s s i n g system. F i r s t , t h e a u t o m a t i c a n a l y s i s o f i n f o r m a t i o n i n t h e i n p u t b u f f e r s p r o v i d e s b o t h d i s c r i m i n a t i o n and i n t e g r a t i o n o f i n f o r m a t i o n , r e s u l t i n g i n t h e d a t a used by v a r i o u s programs. T h i s a u t o m a t i c a n a l y s i s may d i f f e r i n t h e number o f dimemsions d i s c r i m i n a t e d and t h e number o f c o n s t r u c t s g e n e r a t e d , r e s u l t i n g i n v a r y i n g degrees o f c a t e g o r i z a t i o n  c o m p l e x i t y . Second, p e r c e i v e d d a t a and d a t a r e t r i e v e d f r o m LTM a r e used t o s e l e c t a program t h a t i s a p p r o p r i a t e t o t h e p e r c e i v e d s i t u a t i o n . The s e l e c t i o n f l e x i b i l i t y and t h e c o m p l e x i t y o f t h e program and t h e i n f o r m a t i o n i t uses d e t e r m i n e ' d e c i s i o n - m a k i n g c o m p l e x i t y . T h i r d , whereas c a t e g o r i z a t i o n and d e c i s i o n - m a k i n g r u n r e l a t i v e l y a u t o m a t i c a l l y , v a r i o u s s i t u a t i o n s w i l l e l i c i t t h e use o f memory p r o c e s s e s t o c r e a t e new programs and/or c o n s t r u c t s , r e q u i r i n g r u l e usage i n t h e SP. R u l e  c o m p l e x i t y r e f e r s t o t h e s t r u c t u r e and c o n t e n t o f such p r o c e s s e s . F i n a l l y , we may c o n s i d e r t h a t i n s i t u a t i o n s where b e h a v i o u r s a r e e l i c i t e d , t h o s e b e h a v i o u r s may v a r y i n f l e x i b i l i t y and c o m p l e x i t y , r e s u l t i n g i n b e h a v i o u r a l c o m p l e x i t y . 55 These four components of complexity relate to the processes described in the model of the. brain system and are most easily thought of in terms of structure rather than content. However, as discussed in the introductory remarks about conceptual complexity, confusion may arise when a subject's response exhibits different amounts of complexity depending on whether the structure or the content of the response i s considered. There i s no simple way around this d i f f i c u l t y ; however, a hypothesis w i l l be made below as to the ontogenetic development of such responses. Detailed Model Categorization complexity of a given subject topic would include: (1) The number of different pieces of information available about the subject in a l l memory areas. (2) The number of different chunks associated with roughly equivalent pieces of information. This number w i l l be positively correlated with the number of sub-programs relevant to that piece of informa-tion within any given program. (3) The number of "constructs" linked together. Constructs may be thought of as being general addresses associated with different programs; the number of linked constructs reflects the number of programs with which the topic has become associated. This linkage implies that those programs have also become associated with each other. (4) The complexity of the processing necessary to produce that chunk of information. This relates to the content of the information and 5 6 o f the p r o c e s s i n g t h a t p r o duced i t . F o r example, c h u n k i n g b i n a r y d i g i t s by t r a n s l a t i n g them i n t o d e c i m a l numbers i n v o l v e s l e s s complex ( o r a t l e a s t , l e s s c o m p l i c a t e d ) p r o c e s s i n g t h a n , s a y , t a k i n g t h e b i n a r y d i g i t s t o be Morse code ( d o t s and dashes f o r ones and z e r o s ) , t r a n s l a t i n g them i n t o l e t t e r s , and t h e n c o n s t r u c t i n g acronyms from t h o s e l e t t e r s . W i t h l o n g p r a c t i c e , an i n d i v i d u a l m ight p e r f o r m t h e g r e a t e r p a r t o f e i t h e r c h u n k i n g method i n an a u t o m a t i c manner. C a t e g o r i z a t i o n c o m p l e x i t y w o u l d t e n d t o be e l i c i t e d by q u e s t i o n s s u c h as "What do you know about ?" R u l e c o m p l e x i t y r e l a t e s t o t h e c o m p l e x i t y o f memory p r o c e s s e s w h i c h may be used on i n f o r m a t i o n and c o n s t r u c t s s t o r e d i n LTM. The purpose o f t h e s e p r o c e s s e s i s t o d e t e c t c o n s i s t e n c i e s and i n c o n s i s t e n c i e s be-tween d i f f e r e n t c o n s t r u c t s , as m e n t i o n e d e a r l i e r . I t woul d depend on: (1) The t o l e r a n c e f o r e r r o r i n t h e memory s e a r c h programs: more co n -n e c t i o n s w i l l be made as t h e c r i t i c a l t o l e r a n c e d e c r e a s e s . I n s e a r c h i n g f o r a c o n s i s t e n c y between t h e s t a t e m e n t s "The moon i s made o f r o c k " , and " t h e moon c o a l e s c e d f r o m a ga s " , a p e r s o n h a v i n g a l a r g e e r r o r t o l e r a n c e may n o t do any memory s e a r c h e s o r a t t e m p t to c r e a t e any new r u l e s ; a p e r s o n h a v i n g s m a l l e r r o r t o l e r a n c e may spend a l i f e t i m e p e r f e c t i n g r u l e s w h i c h i n t e r r e l a t e l a r g e amounts o f i n f o r m a t i o n and many programs. Note t h a t i n any i n d i -v i d u a l r u l e c o m p l e x i t y may be h i g h i n some c o n t e n t a r e a s and low i n o t h e r s . (2) The number o f a v a i l a b l e r u l e s f o r comparing c o n s t r u c t s and t h e number o f a s s o c i a t i o n s between them. 57 (3) The content complexity of the rule, in terms of the complexity of processing which was necessary to generate that rule. Reducing inconsistency in the previous example by saying "Planets were formed from gaseous nebula" shows higher content complexity than does reducing inconsistency by saying "So what, I don't care", although in both cases the processing is simple, once the rule i s learned. (4) The complexity of categorization, in that the potential for rule complexity increases as the complexity of information those rules act upon increases. Rule complexity may be el i c i t e d by questions such as "How do and relate to one another?" Note two content areas must be specified, not one as in categorization complexity. Clearly categori-zation and rule complexity are similar, the difference being that categorization complexity is determined by the kind and number of programs running during the learning of the information while rule com-plexity i s a function of the memory processes which combine information already present in LTM; categorization processes run automatically, while rule processes run in the SP. Rule complexity is more content-independent and less related to the circumstances under which the information was learned than is categorization complexity. Decision-making complexity relates to the operation of programs on information in a specific environmental situation, rather than in a more abstract memory process. It is dependent upon: (!) The amount of information used and the categorization complexity of that information. 58 (2) The number of programs which could be used to process the informa-tion. This w i l l range from low (only the one program immediately associated with that precise environmental condition) to medium (several associated programs are available because of moderately high categorization complexity) to high (several previously un-related programs are used as they become associated through rule usage). (3) The f l e x i b i l i t y used in choosing the program or rules to use. An individual may have many programs available but may use only the simplest ones most of the time. (.4) The complexity of the program structure as indicated by the number of choise points i t contains. (5) The number of situation-specific outputs possible in the decision process. Decision-making complexity w i l l tend to be el i c i t e d in specific problem tasks, such as "If were the case, what would you do about i t ? " Behavioural complexity w i l l depend on: (1) The number of available behavioural outputs. A person may have highly complex processing i n a given situation, leading to several available decisions about what he should do, but only be able to do one of them (the perceptive, but shy, person would be a good example of this). (2) The tolerance for error, especially at high level analysis. As error tolerance decreases, the person tends to be forced to employ various other behaviours, more perfectly suited to various situations. 59 Hypotheses The preceeding model describes several semi-independent features of the processing system. Two main points should be noted about such a system i n reference to a discussion of conceptual complexity or, indeed, any other r e l a t i v e l y " h i g h - l e v e l " psychological concept. F i r s t , that i t i s d i f f i c u l t to describe the o r i g i n s of any psychologically i n t e r e s t i n g behaviour without examining the functions of the several i n t e r a c t i n g features which were instrumental i n producing that behaviour. Very few of the outputs that psychologists measure can reasonably be thought of as being the r e s u l t of only one independent, homogeneous process. Rather, i t i s necessary to t r y to determine exactly which processes are involved i n the s i t u a t i o n , and to theorize on that basis. This point i s expanded upon i n Appendix A, Attitude Measurement. Second, note that the processes described by the model are both considerably d i f f e r e n t from each other (implying some independence of functioning and complexity) and semi-independent within themselves across d i f f e r e n t program areas. As a r e s u l t , we may hypothesize that an i n d i v i d u a l may have d i f -ferent processing complexity not j u s t i n d i f f e r e n t content areas (as Schroder et a l . , 1967, have suggested), but also i n d i f f e r e n t process areas. A judge who considers many c o n f l i c t i n g and complicated aspects of a case, but who always decides i n the end that the accused person must be g u i l t y might be said to use a r e l a t i v e l y complex categorization process but a r e l a t i v e l y simple decision process. The f l e x i b i l i t y and appropriateness of the judge's sentence could be seen as r e f l e c t i n g the complexity of a d i f f e r e n t decision process as w e l l as that of a 60 behavioural output. Similarly, a superstitious person may evolve a complex rule system for explaining the interrelations between various events without necessarily employing complex processing in other areas. We might expect, however, that such an individual would tend to have relatively complex decision-making and behavioural processes i f he or she decided to act in ways which minimized the unpleasant consequences of breaking "bad luck" superstitions. It i s a matter for empirical investigation to determine the degree of correspondence between the various complexities of structure in the four areas of processing mentioned above. However, since the complexity found in any given area is at least indirectly related to error tolerance, we might expect a small positive correlation between the complexities of different areas i f this tolerance is constant in different areas. Remember that error is detected in some manner in a neuron comparison unit; to the degree that such comparison units are similar across processes we may expect error tolerances in those processes to be related. The purpose of further dividing conceptual complexity in this way, of course, is to attempt to improve the predictive validity and des-criptive usefulness of complexity when used in conjunction with mea-sures of behaviour or mental processes. To the extent that this model accurately describes cognitive functions, and that suitable measurement devices may be found for them, i t is hypothesized that the set of four measures w i l l prove more predictively and descriptively useful than any single measure of complexity. It should be emphasized here, how-ever, that the postulated program-dependent nature of complexity means that complexity is not such a global attribute of mental processes as is 61 often implicitly assumed. That is the validity of any measurement of the complexity of the four cognitive functions w i l l depend on how similar the content area tapped during the measurement is to the con-tent area which the researcher wishes to describe or predict. The ontogenetic development of the various processes occurring in these areas has, of course, long been studied in many different areas of psychology. However, part of the model presented here describes the development of automatic processes from non-automatic ones, which w i l l lead to changes of function not only within a given process, but also in the transfer* of function from one process to another. In particular, there w i l l be a gradual shift of function over time from relatively non-automatic processing to relatively automatic processing as a particular function is repeated. Some functions which originally had to be run as rule manipulations in the SP w i l l later become automatic decision functions;, decision functions may eventually be incorporated into categorization processes. For example, a rule structure consisting of "hot things cause pain i f touched" and "pain i s to be avoided", w i l l soon be incorporated into the more automatic decision program " i f i t ' s hot, don't touch i t " . This decision might later be incorporated into the categorization "hot-bad" associated with those situations in which the original program was true. In this latter situation, the decision rules may be superceded or l e f t more simple .and fewer in number, with a concomittant increase in the com-plexity of categorization complexity. Such a reduction in high-level complexity accompanied by an increase in low-level complexity is almost certainly only true for 62 adults. Clearly rules are built up by processes tending to increase complexity at high levels using information found at low levels of processing. Thus these processes might be seen as being in opposition to those described above which tend to decrease high level complexity. When relatively large amounts of new, unintegrated data is being encountered (as i s the case with children), such a combination of pro-cesses w i l l overall tend to increase high level complexity. At some point, however, most incoming information w i l l be dealt with auto-matically and so the result of these processes w i l l be to decrease high level complexity. The adult in a "rut" w i l l tend to use automatic programs far more often than rules. Thus any procedure which measures rule usage w i l l find such usage to follow an inverted U-shaped curve over the course of an individual's l i f e . To the extent that a person's l i f e situation keeps introducing new experiences to be integrated into a cognitive scheme, this rule usage curve w i l l tend to peak at later ages. Relationship to Conceptual Complexity Literature It i s d i f f i c u l t to relate this model to specific research in the f i e l d of conceptual complexity because most of that work has been done using either tasks involving discriminative (categorization) complexity as developed by Kelly (1955) and Bieri (1955, 1961), or tasks involving integrative complexity as modeled by Schroder et a l . (1967) and Harvey, Hunt and Schroder (1961). Although studies using either of these approaches often prove predictively useful in specific situations, there has been l i t t l e attention paid to the relationship between the 63 two models, and no attempts have been made to Integrate these forms of complexity into a general model of brain activity. In addition, many workers only consider complexity with respect to social stimuli, considerably reducing the certainty with which we can extrapolate their findings into general processing ac t i v i t i e s . The studies that consider several areas of complexity simul-taneously have been done quite recently and are not yet very sophisti-cated. MacNeil (1974) notes that workers in the complexity f i e l d have not usually tried to combine integrative and discriminative complexity ideas into an overall theory, and have also not made much headway in identifying the rules used in integrative complexity. In particular, he notes that concept attainment rules have not been found to have very much in common with integrative complexity rules. He proposed a descriptive model which synthesizes the two complexity approaches in relation to the Neisser and Weene (1962) rules for concept attainment. Although he presents no experimental evidence, i t is clear that he intends to use a concept attainment paradigm as a tool to discover the relationship between integrative and discriminative processing. Epting and Wilkins (1974) present measures of the intercorrelations between two measures of discriminative complexity, two measures of integrative complexity, and a measure of discrepant information inte-gration in a person-perception task. None of the correlations exceed .31, and six of the ten correlations are below .11; Epting and Williams suggest that this reflects the possibility that each measure i s evalu-ating a different cognitive process. However, the low correlation of .25 between the Schroder et a l . measure (1967) and the person-perception 64 integration measure (Kaplan and Crockett, 1967) tends to weaken one's confidence in their results in that the two measures use almost iden-t i c a l procedures for assigning ratings of complexity. Only the form of the data used i s different in that the Schroder et a l . measure uses responses to incomplete sentence stems and the Kaplan and Crockett method uses descriptions of a person; i t seems most unlikely that this should be of any significance. Scott (1969) similarly found that various other measures of cog-nitive functioning within a metric multidimensional model of cognitive space tended to show only limited consistency across content areas within a given process area, and limited consistency across1 process areas within a given content area. His measures of processing included several not considered here, such as articulation, affective consistency, and centrality; his measures of dimensionality and integration, however, were not highly correlated with each other. A similar study was done by Kuusinen and Nystedt (1975), who used various factor analytic methods to study the relationship between Bieri self-constructs and three measures of integration as defined by Vannoy (1965); these measures were also taken when constructs were supplied to the subjects. They found low convergent validity between the various cognitive mea-sures and also found that the type of construct used affected the intercorrelations of the measures. The above-mentioned studies show a recent trend towards considering the relationship between discriminative and integrative processing in a more quantitative manner than has been done previously. They support in a general way the hypotheses that these process areas may be 65 independent in terms of complexity and that complexity may be quite different in different content areas. The hypothesis that the error tolerance associated with a given content and program area may change given various work of Press, Crockett, and Delia (1975) and Earle (1970). In these studies charac-ter evaluations and cue learning, respectively, became more complex when the subjects were placed in situations which encouraged such pro-cessing. In both studies, however, only subjects who were concep-tually complex with respect to the task at hand showed such an increase; there was no change for non-complex subjects. Tests The two main hypotheses of the model are that the structure of cognitive processes may be described in terms of four semi-independent areas of functioning, and that some combination of these four areas w i l l prove to be more predictively and descriptively useful than any single measure of complexity. The a b i l i t y to test such hypotheses, of course, i s limited by the a b i l i t y to accurately measure the complexity of the four process areas. Given measures of these processes, any experiment which essentially duplicates a single cognitive process experiment but with measurements of a l l four process areas w i l l at least show i f these measures are heuristically useful. Showing the "true" relationship of these measures to the actual cognitive processes is much more involved: see Appendix B for a fuller description of how this might be done. Since any testing of this model depends on the development of such measurement techniques, this section w i l l describe 66 some ways in which these measures could be developed. The outline of possible measures w i l l loosely follow the points outlined under Detailed Model, above. Categorization Complexity (1) The number of pieces of information available about a given topic w i l l to some degree reflect the different ways in which that topic may be categorized. It might be measured by means of a world-knowledge questionnaire about the given content area. However, as such a questionnaire would probably inevitably tap into various memory processes, i t s r e l i a b i l i t y would be open to question. The number of self-generated constructs e l i c i t e d from a Bieri-type construct role task would also tend to reflect the amount of i n -formation present about the topic, and might be less subject to the above criticism. (2) The number of constructs linked to a given topic might be measured by asking for constructs associated with an experimenter-supplied construct. These el i c i t e d constructs would then be used in a role construct task and the number which were independent at some criterion level would reflect the construct linkages for that topic. (3) The content complexity of a given construct or chunk of information must be measured in a relatively subjective manner. However, some of the ideas of Schroder et a l . (1967) with respect to the simul-taneous use of several points of view about a topic as reflecting complexity might prove useful here. F i r s t , does a given self-generated construct e x p l i c i t l y or implicitly assume the conjunction of opposing views? If so, that construct would be considered to 6 7 have a more complex content that one that presented a single viewpoint. The construct "contradictory" would be an example of one having some complexity of content. Note that Schroder et a l . would disagree with this i f the construct were used in a simple fashion. Second, are two or more self-generated constructs po-tentially conflicting? If so, then presumably some complex pro-cessing must have been responsible for such a situation and we may consider this type of categorization to have relatively high content complexity. Using both the constructs "warm" and "forbidding" about the same person would be an example of such a situation. A third way of measuring this might be to give experimenter-generated associations to them. Given that the subject uses the stimulus constructs in an independent manner, the number of identical associated to the conflicting stimulus constructs w i l l reflect the degree of content complexity. Rule complexity (1) The tolerance for error in the memory search programs cannot be measured directly unless some physiological way can be found to do so. However, i t might be measured indirectly by presenting the subject with a situation which contains ambiguities and potential conflicts (perhaps in a standard person-perception task) and using the number of conflicts and ambiguities which the subject notices as a measure of this facet of rule complexity. (2) The number of available rules for comparing constructs would be reflected by the number of conflicts and similarities noticed in an ambiguous person-perception task. Alternately, in a paragraph 68 completions task (Schroder et a l . , 1967) this measure would be reflected by the number of content areas mentioned by the subject, without regard for the decisions reached. (3) The content complexity of the rule w i l l be reflected in the number of disparate content areas which are related by the rule. As in categorization complexity, i t may be possible to e l i c i t rules about potentially conflicting areas and noting how many are similar, or by judging whether the rule implicitly or explicitly related dissimilar content areas. Decision-making complexity (1) The amount of information used w i l l be reflected in the number of content areas sampled for data before a decision i s reached. Although this i s similar in nature to point (3) of rule complexity, here i t would be measured in the context of a specific decision situation rather than in a descriptive situation as for rule com-plexity. (2) The number of programs available and the f l e x i b i l i t y of using those programs could be measured in a hypothesis-testing or concept-formation situation by noting the number of hypotheses employed and the time taken to try a new hypothesis when the experimental con-tingencies for "correct" responses are changed. Complexity w i l l be associated with trying more hypotheses and changing hypotheses more quickly. Alternately, the facet of decision complexity m i g h t . b e measured in a paragraph completion task how many different decision are referred to, without regard for which de-cision the subject actually employs with respect to the specific 69 situation dealt with in that paragraph. (3) The content complexity of the program would be related to the number of choice points referred to and could be measured as such in a paragraph completion task. It would also be reflected in :the im-p l i c i t or explicit use of conflicting information, but the auto-matic nature of programs may make this d i f f i c u l t to measure except as a function of conscious rule processing. (4) The number of situation-specific outputs (either decisions or behaviours) possible could be measured by expli c i t l y asking the subject to l i s t a l l of the decisions which he feels would be reasonable in the experimental context, without regard for which one i s considered to be superior. Behavioural complexity (1) Given that a subject has previously indicated that a number of situation-specific behaviours are possible in a given context, a f i e l d study of the number of behaviours actually employed in that situation would be a measure of behavioural complexity. This i s , of course, rather clumsy, but any attempt to measure this aspect of complexity in any non-behavioural manner must inevitably measure the other aspects of complexity to some degree, counfounding the measure. (2) The f l e x i b i l i t y of behaviours again may only be properly measured in a f i e l d study of behaviours under changing situations. 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If the c r i t i c a l error level i s exceeded, program change or reorganization results. Note that higher level control systems need to react more slowly than low level ones in order to remain stable (if high-level systems acted faster than low-level ones, the high-level systems would act before the low-level ones has a chance to correct any errors they detected, introducing new errors Into a l l the systems; a steady state would be very d i f f i c u l t to achieve). Correspondingly, we would expect the c r i t i c a l error tolerance to be larger in the higher order systems. This, in turn, implies that running high level automatic programs is "the path of least resistance," since i t results in the least probability of having to alter programming. Using high level programming means using programs to deal with highly integrated material. This high integration level of informa-tion while running automatic perceptual programs, however, implies a loss of detail and of specificity, i f we assume that lower level pro-grams are only run when the higher level error tolerance i s exceeded. This may, perhaps, sound contradictory, as we are used to asso-ciating "highly integrated" with a richness of processing and large amounts of information. In fact, although a general information address is created through detailed input comaprison programs, that detail i s submerged in lower level information buffers; we can think 79 of the detail as being in "categories", and the higher level address as being a "supercategory". Processing i s easiest when very general programs process the information found in :these supercategories. Of course, doing the easiest thing possible is not necessarily what the individual wants to do; many theorists believe that people seek to maintain some optimum, non-zero, level of arousal (e.g., Yerkes and Dobson, 1908; Schroder et a l . , 1967). In the present model, the level of arousal may be equated with total amount of error present in various systems which is greater than the error tolerance for those systems. Playing tennis, for example, may produce arousal in several ways: i f we are losing when we wish to win, i f we are trying to move faster than we are used to or our conditioning permits, i f we are trying always to hit the b a l l a certain way but sometimes miss, and so forth. Reducing error in any of these systems (by beating poor players, be getting physically f i t , or by improving co-ordination) reduces arousal, and may result in our changing some program to increase i t s error (for example, looking for more skilled competitors). From casual observation, however, i t appears that we prefer to contain this arousal to only a few areas, while striving for tranquility in others. People don't seem to maintain a great deal of arousal in every activity, but rather in just a few, usually consciously chosen ones. In the majority of everyday, behaviours, such as driving, eating, walking, and so forth, many people appear to prefer acting relatively automatically, and with l i t t l e arousal. This small amount of arousal could, of course, be considered optimal in those situations. For some individuals this automatic activity may carry over into such areas as 8 0 casual s o c i a l i n t e r a c t i o n s , reading, studying, and many forms of decision-making. How much processing i s done automatically, and.in what areas, could best be studied i n the context of i n d i v i d u a l d ifferences. Brain P l a s t i c i t y and S p e c i f i c i t y If the brain has been damaged, but not too severely and not i n both hemispheres, a program function which o r i g i n a l l y was l o s t w i l l gradually reappear i n some other area of the brain, either i n a nearby area or i n the equivalent area of the opposing hemisphere (Rose, 1975). The reappearance of the function must be due to the action of the reorganization system. Since the function only reappears i f the damage i s not too widespread, one of two things i s implied. Either the rules used f o r generating new programs are stored i n ph y s i c a l locations near, or i d e n t i c a l with, those of the programs they create (with apparently some redundancy across hemispheres), or the brain's s p e c i f i c i t y i s due to the fac t that the necessary program interconnections are p a r t i a l l y hard-wired, and other areas of the brain simply don't have the necessary p h y s i c a l connections. The model predicts that loss of memory due to i n j u r y would not be as severe as l o s s of program function, since roughly equivalent memories would be present i n d i f f e r e n t areas of the brain, having been stored during the running of d i f f e r e n t programs. In the event of memory l o s s , c a r e f u l questioning under d i f f e r e n t circumstances (corresponding to d i f f e r e n t programs) might show that the memory i s s t i l l present but has l o s t some of i t s associations. I don't know i f anyone has found t h i s kind of as s o c i a t i v e memory lo s s . 81 Attitudes Measurement The measurement of attitudes has always presented severe problems to psychologists. This theory helps c l a r i f y the reasons for, i f not the solutions to, those problems in two main areas: program specificity of attitudes, and content/process measurement distinctions. Fi r s t , the theory implies that measurement of an attitude in the laboratory, for example, is only going to be useful i f we wish to study other attitudes about, or behaviours in, the laboratory. Remember that associations (either of information or of programs) are built up during the running of programs, so that an attitude used in one situation need not be very consistent with the attitude about the same topic when used in a different situation. We may love pedestrians when we are walking and hate then when we are driving. The traditional approach to this problem has been to assume that there is some kind of global consistent attitude for any given subject matter, and that situation-specific anomalies are relatively unimportant (e.g., Allport, 1937). The present theory suggests that, in fact, the global attitude is the anomaly, and the specific attitudes are the important ones, since the latter deter-mine what information is processed at any given time. Measuring global attitudes is confounded by the nature of an individual's memory programs: the more consistency they create, either in the normal course of events or during the attitude measurement, the more meaning a global attitude may have. However, a global attitude constructed during the measurement process does not necessarily have any relevance to the person, who may forget i t immediately afterwards, and revert to situation-specific ones. 82 Second, various kinds of measurement instruments e l i c i t different kinds of data depending on which area of processing they tap. In ways roughly analogous to those described above under "Conceptual Complexity", different kinds of questions may measure the content of the memory store, or the programs which are used to process that content, or the kinds of behaviour used, a l l of which w i l l tend to be situation-specific. Careless questions which tap several situational contexts may e l i c i t constructed, more global attitudes through forcing rule usage by the subject. The above discussion implies that more care must be taken in designing the format of questionnaires to ensure that the appropriate kind of data is being solicited, and that those questionnaires should relate as clearly as possible to the situation of interest. I leave the implementation of these suggestions as an exercise for the alert reader. Behaviour and Attitude Change Many researchers have found that attitudes and behaviour may be changed relatively independently of one another (see e.g., Bem, 1972, for a review). The present theory i s entirely consistent with those results, in that informational attitude changes (rather than evaluative or emotional ones) are the result of higher level processing than are behaviour changes. Changing the behaviour involves changing i t s re-ference signals. Since these signals are supplied by a program inde-pendent of the memory program that searches for informational consistency, there is no reason why changing a .behaviour should necessarily change 83; the c o r r e s p o n d i n g a t t i t u d e . S i m i l a r l y , changing the c o n t e n t of an a t t i t u d e i n v o l v e s u s i n g a memory program; the changed a t t i t u d e w i l l then be a s s o c i a t e d w i t h t h a t program and not w i t h the b e h a v i o u r a l o r d e c i s i o n -making program. We would expect, though, t h a t p e r s o n s showing h i g h r u l e c o m p l e x i t y would tend t o have h i g h e r p o s i t i v e c o r r e l a t i o n s between changes i n be-h a v i o u r and a t t i t u d e , s i n c e t h e i r memory s e a r c h programs would be le s s l i k e l y t o t o l e r a t e e r r o r s i n c o n s i s t e n c y . I t i s c o n c e i v a b l e t h a t p e r -sons showing h i g h d e c i s i o n - m a k i n g c o m p l e x i t y would show lower c o r r e l a t i o n between b e h a v i o u r and a t t i t u d e , s i n c e t h e r e would be more program-s p e c i f i c a t t i t u d e s f o r a v a i l a b l e use and the e f f o r t o f making them a l l c o n s i s t e n t would be too h i g h . 8.4. APPENDIX B A Research Program Overview There are two basic approaches to be taken i n doing research on cognitive models. The f i r s t , and most commonly used, i s to deduce the operation of the brain from the analysis of a person's behaviour while he performs a task which i s supposed to discriminate between various kinds of processing. Memory process, f o r example, may be studied by using various s e r i a l learning paradigms, or s e r i a l synthesis by employing arithmetic problems formulated i n different ways. The i n t e r p r e t a t i o n of data from such studies i s made d i f f i c u l t because there i s no way of d i r e c t l y v e r i f y i n g that the task only activates those brain processes which the experimenter hopes to a c t i v a t e . The memory load imposed by an arithmetic problem, for example, may be considerable for someone who has not done such problems for many years; t h i s may confound the r e s u l t s i f the experimenter does not consider the r o l e of memory i n deriving the experimental hypothesis. The second way i s to study brain a c t i v i t y d i r e c t l y . The d i r e c t study of brain functions has most often been done using l e s i o n and ab l a t i o n techniques. In these studies, a portion of an animal b r a i n i s lesioned, and the i n v e s t i g a t o r seeks to determine what kinds of per-formance decrements r e s u l t . Paradigms involving biochemical assays of brain tissue are also used, e i t h e r a f t e r the i n j e c t i o n of drugs into the brain, or i n conjunction with l e s i o n studies. More recently, EEG work has become more popular, e s p e c i a l l y with the discovery of the 85 Contingent Negative Variation (CNV), and with the use of computer averaging to study the evoked potential (EP). The interpretation of such studies has generally proved to be d i f f i c u l t . Criticisms of paradigms involving searching for performance deficits after causing some brain areas to cease working (either per-menently, as with lesions, or temporarily, as with drugs) have been made frequently (e.g., Gregory, 1961; Luria, 1973) and center around three main points. First, the performance decrement resulting from a given lesion i s often only indirectly caused by that lesion, as in the famous example of hearing a b i l i t y in rats apparently being an inverse function of the number of limbs s t i l l attached to the rat (Cohen, 1971). This may be termed a problem of specific function. The severity of this problem increases as a function of how many systems are interconnected and inter-dependent. The second problem is that of localization: some functions seem to be confined to one small, relatively well-defined area of the brain, the most famous example being the motor areas mapped by Penfield and Roberts (1959). Others seem to be distributed through the entire cortex and defy attempts to localize them. In Lashley's famous learning study (1950) the decrement in maze performance of rats was related to the amount of cortex removed after learning the maze; no one area contained the memory. In addition, lesions in one area of the brain may cause neurons to degenerate in other areas. The third problem is that of precision: precise lesion, chemical 86 and e l e c t r i c a l studies often may be performed only on animals, and the re s u l t s of such studies, even on man's closer r e l a t i o n s such as monkeys, often do not apply to human beings. In addition, human lesi o n s are often caused by accidents, and tend to be so large as to involve many brain structures. Without denying the usefulness of decrement paradigms, the problems of p r e c i s i o n and s p e c i f i c function would i n d i c a t e that procedures i n -volving non-brain-damaged humans engaged i n c a r e f u l l y constructed tasks could be us e f u l i f some non-surgical means were a v a i l a b l e of measuring p h y s i o l o g i c a l brain a c t i v i t y ; at present only the EEG meets t h i s require-ment. In addition, the tasks must be such that t h e i r r e l a t i o n s h i p to some t h e o r e t i c a l model of information processing is. unambiguous: the s p e c i f i c function problem i s worsened when i t i s unclear what processing functions the task studied involves. For example, an asso c i a t i v e learning task may or may not require a subject to categorize information i n a novel way, and may or may not impose overloading of STM processes, depending on the nature of the stimulus materials and the way i n which they are presented. The s p e c i f i c function problem then, may be seen as not j u s t applying to performance decrement techniques, but rather as being a problem i n any paradigm. Only a task or stimulus which has been formulated using a clear theory of information processing can produce interpretable experimental r e s u l t s , either about the e f f e c t s of that task or stimulus, or about the v a l i d i t y of the theory. The above-mentioned problems mean that an analysis of the r e s u l t s of p h y s i o l o g i c a l studies w i l l provide only rather obscure clues as to the p h y s i c a l organization of brain functions. Nevertheless, some of the 87 data are h e l p f u l i n at l e a s t delineating general areas i n which some processing occurs. I propose that a combination of d i r e c t and i n d i r e c t methods may provide a more rigourous means of studying cognitive processes, since the data from one method of study can be used to help v e r i f y the assumptions of the other. In o u t l i n e , such a research program would progress roughly as follows: (1) Tasks of the most simple kinds w i l l be formulated so that they are as "pure" examples as possible of tasks a c t i v a t i n g the various brain functions proposed by t h i s model. For example, a simple perceptual task could be devised which imposes no load on LTM, the SP, the reorganizer, or program s e l e c t i o n . (2) The p h y s i o l o g i c a l a c t i v i t i e s accompanying such tasks w i l l be measured, and consistent a c t i v i t y patterns for tasks involving a given cognitive process w i l l be taken as s i g n i f y i n g the operation of that process. (3) These process patterns may then be studied when tasks a c t i v a t i n g more than one brain function are used. In t h i s way the i n t e r a c t i o n s ( i f any) between process patterns w i l l be found and temporal sequences of a c t i v a t i o n may be investigated. Having a cross-validated set of tasks and process patterns, any task may now be evaluated i n terms of what processes i t a c t i v a t e s . Also, cognitive models may be tested by looking for the a c t i v a t i o n of p a r t i c u l a r sequences of process patterns, or by noting inconsistencies i n those already developed, i n d i c a t i n g a problem i n the model currently being used. Although t h i s method s t i l l does not provide a d i r e c t , completely v e r i f i a b l e technique for measuring brain functioning, i t allows more c r o s s - v a l i d a t i o n of r e s u l t s than i s presently a v a i l a b l e and 88 should s i m p l i f y both the development of cognitive models and the con-s t r u c t i o n of tasks and stimulus materials. The a l e r t reader w i l l have noticed one major d i f f i c u l t y i n pursuing such a research program: what are the " p h y s i o l o g i c a l a c t i v i t i e s " which are to be measured? I believe that EEG processes are the ac-t i v i t i e s most c l o s e l y r e l a t e d to the ongoing a c t i v i t y of the brain, and presently may be studied by analyzing the CNV and EP or by c a l -c u l a t i n g the power spectrum of the EEG frequencies. Although i t has been found that c e r t a i n kinds of EP accompany decision making (see following references), there are s t i l l reasons for b e l i e v i n g that the EEG i s only i n d i r e c t l y r e l a t e d to processing. P e t i t mal e p i l e p t i c attacks, for example, produce grossly abnormal EEGs, yet the attack may be completely unnoticed by the patient (Johnson, Davidoff, and Mann, 1962) who may show only r e l a t i v e l y minor performance decrements which are not p e r f e c t l y i n phase with the EEG i r r e g u l a r i t i e s (Mursky and Van Buren, 1965). Nevertheless, the EEG s t i l l seems to be the technique with the most d i r e c t relevance to information processing. Other measures which have also been found to be r e l a t e d to processing, such as eyeblink rate (Holland and Tarlow, 1972), number of eye f i x a t i o n s (Loftus, 1972), heartrate decrement ( B l a t t , 1961), and skin resistance (Harding, Stevenes, and Marston, 1973), could also be used i n conjunction with the EEG, but generally t h e i r d i scriminative a b i l i t i e s are too small and t h e i r time scales too long to be worthy of much hope. The next two sections w i l l present a b r i e f review of the physio-l o g i c a l evidence about the functions of various brain areas and a 89 brief description of some techniques which could be used in the research program outlined above. Physiology The areas in which input buffering takes place are f a i r l y well known to be the retina, lateral geniculate and the occipital cortex for vision (e.g., see Luria, 1967; Marg, Adams, and Rutkin, 1968); the various areas of the temporal lobe, especially the transverse gryi of Heschel, as well as some processing by the cochlea and basilar membrane, for hearing (see P. Milner, 1970 or Luria, 1967 for reviews); and the parietal area for sensory-motor processing (e.g., Penfield an Jasper, 1954; Penfield and Roberts, 1959; Luria, 1967). Luria (1967) considers that everything in at least the second unit of the brain (that for processing and storing information) is arranged hierarchically (p. 69). Although he makes the same claim for the unit that regulates tone and the unit that programs mental activity, he seems to treat only the second unit as hierarchical in the sense of information inte-gration, rather than in the more limited sense of information flow. The control units for directing motor behaviour at the third level in Powers' scheme seem to be found in the cerebellum (Rose, 1975; Powers, 1973), and those for controlling the fourth order may l i e in the second somatic area of the sensory cortex (Powers, 1973, based on Penfield and Roberts, 1959). Second-order systems are iden-t i f i e d by Powers with the motor nuclei of the brain stem, and f i r s t -order systems are controlled by the spinal motor neurons. The physical locations of the reorganization system, the serial 90 processor, and memory (both STM and LTM, and of both information and programs) are far more d i f f i c u l t to pinpoint. Part of this d i f f i c u l t y is certainly due to the problems of interpretation discussed above, but part i s also due to the structure of the brain. In terms of this model, the precise localization of memories by Penfield and Roberts, for example, would be due to their somehow activating the general address for those specific memories which would be stored in specific locations. The elusiveness of the engram in Lashley's 1950 study, on the other hand, i s due to the fact that a given memory may be stored in many areas and associated with many programs. Thus electrical stimulation of the brain in two areas may produce two memories, each of which contains the memory, of a maze, for example., The memory of the maze remains approximately the same, but the associations differ. Lashley's study then implies that, for rats, programs related to searching out food are richly associated, so much so that maze learning becomes associated with other programs and memories across the entire cortex. Long-term memories of automatic programs and information are thus stored in many areas of the cortex; i t appears, however, that certain areas of the brain have specialized their function, although at present i t i s unclear whether that specialization involves program operation, memory storage, or both. The most obvious specialization is that of late r a l i t y : the l e f t hemisphere in right-handed people usually contains areas associated with verbal and sequential a b i l i t i e s , especially in the temporal lobe, while the right hemisphere seems more associated with spatial and simultaneous ones, again mainly in the temporal lobe (e.g., Galin and Ornstein, 1972) but also in the 91 p a r i e t a l region (Luria, 1967); i n addition, emotions seem associated with the ri g h t hemisphere (e.g., Schwartz, Davidson, Maer, and Bromfield, 1974). Even t h i s simple dichotomization i s probably an ov e r s i m p l i f i c a t i o n , however; P. Milner (1970) notes that the s p l i t -b r ain experiments done by Sperry and Gazzaniga (1967) imply that the rig h t hemisphere produces various verbal d e f i c i t s (e.g., L u r i a , 1967), while r i g h t hemisphere i n j u r i e s do not. Such d i f f u s i o n of function may i n the future be found to apply to s p a t i a l and simultaneous func-tions as w e l l . It also appears that STM i s present i n d i f f e r e n t areas of the brain. According to Lu r i a (1967), no one area of the brain gives r i s e to decrements i n STM when lesioned; rather, a mo d a l i t y - s p e c i f i c memory decrement w i l l appear i n the area associated with the processing of that modality. A l e s i o n i n the l e f t temporal lobe, f o r example, i n t e r f e r e s with immediate audio-verbal memory. R e l a t i v e l y l i t t l e i s known about such memory d e f i c i t s , e s p e c i a l l y i n the r i g h t hemisphere, but L u r i a hypothesizes that there are many mo d a l i t y - s p e c i f i c memories. This would imply the existence of many STMs. It appears that one region responsible f o r the transference of memory from STM to LTM i s the hippocampus, l y i n g i n the medial, temporal lobe (see Milner, 1970 and L u r i a , 1967 for reviews of t h i s l i t e r a t u r e ) . Patients with hippocampal damage may have unimpaired STM, but be unable to r e t a i n new information for more than a few minutes. Even though c e r t a i n s k i l l s learned i n motor and perceptual learning tasks may be retained, the patient i s usually unaware of having done those tasks before (B. Milner, 1962). In terms of my 92 model, these data suggest that what i s impaired i s the consolidation i n LTM of conscious memories from the SP, and that perhaps memories not acted upon by the SP can be at l e a s t p a r t i a l l y retained. This i s consistent with my e a r l i e r hypothesis that the SP and STM may only hold part of the data i n the higher l e v e l buffers. These consolidation problems are considered by several researchers to be r e l a t e d to i n -terference with the STM memory by i r r e l e v a n t s t i m u l i since the informa-t i o n i n STM i s immediately l o s t i f the patient i s d i s t r a c t e d (see L u r i a , 1967, for example). Note that the SP would c e r t a i n l y be involved i n any a t t e n t i o n a l mechanisms. We might consider two p o s s i b i l i t i e s f o r the r e l a t i o n s h i p between STM and the SP: (1) That the information i n the SP i s part of the information i n STM, but i s distinguished by being "attended to", probably as a r e s u l t of some kind of action by the limbic system and r e t i c u l a r formation (which are associated with medial temporal lobe s t r u c t u r e s ) ; and thus the SP and STM are d i f f e r e n t aspects of the same structure; (2) That a t t e n t i o n a l mechanisms d i r e c t information back and f o r t h between STM and the SP, which are d i f f e r e n t structures. In e i t h e r case, i t appears that consolidation of memories can occur from both STM and the SP into LTM. Damage to the f r o n t a l lobes of humans produces behaviour which i s stereotyped, unplanned, and rather unmodifiable. Simple behaviours, however, can be performed by such patients, verbal a b i l i t i e s seem unimpaired, t h e i r I.Q.'s are normal, and STM for verbal and v i s u a l material shows no d e f i c i t (see P. Milner, 1970 and L u r i a , 1967 for examples). Generally, the patients seem unable to change t h e i r 93 behaviour when i t i s inappropriate to the situation, and are unaware of committing any errors. This is in spite of the fact that they can repeat verbal instructions about what they should be doing, even while they are actually doing something else. This dissociation of verbal from motor responses leads Luria to conclude that lesions of the anterior frontal lobes cause a disturbance of the regulatory function of speech, as well as generally producing an inability to notice errors related to plans and intentions. In addition, the construction of hypotheses about the meaning of pictures seems to be impossible for such patients. The eye movements used to scan pictures in order to determine various kinds of information are groslly impaired, leading Luria (1967) to conclude that the patients are inable to formulate any clear plan for performing the visual search. These results seem to correspond to what might be expected i f there were lesions of the SP and reorganization system. Both are involved in the recognition of error in order to switch programs and construct new ones. It appears that only relatively high level errors go unrecognized, however, for previously learned programs run unimpaired; i t i s the selection of an appropriate program to use in a novel situation that becomes inappropriate. In terms of this model, however, lesioning of the SP should result in no learning at a l l , at least at higher levels. This hypothesis does not appear to be true. Simple tasks can be learned as long as they do not conflict with some "set" that the patient already has; but once learned they are very resistant to change even when they become inappropriate. These results are further complicated by the fact that patients having unilateral lesions '94 of the f r o n t a l lobes usually show these e f f e c t s , while patients with o r b i t a l lesions do not, or show diminished e f f e c t s . The s p e c i f i c r o l e of the f r o n t a l area i s thus i n considerable doubt, and awaits future study. Techniques For the research program outlined e a r l i e r to be f e a s i b l e , i t must be shown that the EEG can produce data that can be r e l a t e d to processing events. Such data include the evoked p o t e n t i a l (EP), contingent negative v a r i a t i o n (CNV), and EEG frequency analysis. The EP has been shown by several workers to have a l a t e p o s i t i v e component (known as P300) re l a t e d to information processing, i n that the P300 i s present when uncertainty i s being resolved (Sutton, Tueting, Zubin, and John, 1975), when novel s t i m u l i are presented ( R i t t e r , Vaughan, and Costa, 1968), or when s t i m u l i are "task relevant" (Donchin and Cohen, 1967). Some workers (Karline, 1970i Naatanen, 1970) f e e l that the amplitude of the P300 represents the state of per-paredness of the subject, and i s therefore r e l a t e d to a t t e n t i o n a l processes. However, the work of Rohrbaugh, Donchin, and Eriksen (1974) seems to show that i t i s i n f a c t related to decision making, at l e a s t for v i s u a l imagery tasks and for P300 measured at the vertex and occiput. This i s consistent with the research of R i t t e r , Simpson, and Vaughan (1972). Unfortunately, i n the work of Rohrbaugh, et a l . and R i t t e r et a l . the motor response required of the subject often occurred before the onset of the P300, which would seem to obviate the p o s s i b i l i t y of P300 being related to decision-making. In terms of the 95 present model, however, decision-making components of the EP should not be present at a l l at the vertex and occiput and might rather re-l a t e to some post-decision image formation or v e r i f i c a t i o n process. As mentioned i n the Introduction, E.R. John and h i s associates have also performed many experiments involving the EP i n both cats and humans. Their r e s u l t s i n d i c a t e that the EP displayed i n d i f f e r e n t areas of the brain re l a t e d to the meaning of the test stimulus d i s -played. Since d i f f e r e n t areas of the brain process d i f f e r e n t kinds of information, the r e l a t i o n s h i p of the EP to the test stimulus varied depending on where the EP was recorded. For example, John and Grinberg-Zylberbaum (c i t e d i n John, 1976) found that a v e r t i c a l l i n e used as a stimulus would produce d i f f e r e n t EPs i n the p a r i e t a l and temporal regions depending on whether i t was interpreted as the number "one" or the l e t t e r " e l l " , but that the EP was i d e n t i c a l i n both cases when recorded from the o c c i p i t a l area where primary v i s u a l perception pro-cesses occur. S i m i l a r l y , when the two stimulus "A" and "a" were pre-sented, d i f f e r e n t EPs were found i n the o c c i p i t a l region but not i n the temporal or p a r i e t a l regions. These data show that EPs are at l e a s t p o t e n t i a l l y discriminating i n terms of the meaning of the s t i m u l i processed i n a given area of the brain. The question of exactly what these EPs represent i s a d i f f i c u l t one to answer. John believes that they represent the a c t i v a t i o n of s p e c i f i c memories; i n my model they could represent the output from the automatic v i s u a l processing system, which does not require any reference or memory sig n a l s . In s i t u a t i o n s that require decisions and motor output, however, as i n the discrimination learning experiments performed with cats (john, Shimokochin, and 96 B a r t l e t t , 1969) i t has been found that the EP produced during the cat's response corresponds to the one which i s present when the correct stimulus has been presented. The same EP i s present i f the incor r e c t stimulus or some other stimulus were presented on that t r i a l ( i . e . , i f the cat made a mistake). This could r e s u l t from ei t h e r i n c o r r e c t perception or incor r e c t decision-making, and hence the generation of the i n c o r r e c t motor reference s i g n a l . Unfortunately, i t i s unclear from these data which has occurred. Nevertheless, the EP i s again implicated i n processing and decision-making. The CNV paradigm consists, i n i t s simplest form, of measuring EEG while a subject waits to make some motor response ( l i k e pushing a button) i n response to a stimulus a f t e r having been warned a few seconds previously that the stimulus was about to appear. In t h i s s i t u a t i o n a slow, negative p o t e n t i a l s h i f t of the EEG baseline i s ob-served. The shape of the CNV has been found to be correlated with the kind of information processing being performed. The CNV i s often thought of as an accompaniment to expectancy (e.g., Walter, Cooper, Aldridge, McCallum, and Winter, 1964); Weinberg, Michealewski, and Koopman (1976) have postulated that i t s amplitude i s p o s i t i v e l y re-late d to time estimation and negatively r e l a t e d to the information processing load occurring during the response discrimination. In addition, i t i s i n t e r e s t i n g to note that Weinberg and Papakostopoulos (1975) have found that the shape and amplitude of the CNV recorded from the f r o n t a l lobe are d i f f e r e n t from those recorded from the vertex, c e n t r a l , and p a r i e t a l regions, which a l l show; much more s i m i l a r i t y to each other. I f the f r o n t a l lobes are the s i t e of 97 "higher" processes involving the SP, we might expect the CNV magnitude to be smaller there than at other s i t e s i n the l i g h t of the Weinberg et a l . (1976) r e s u l t s since the processing there i s l e s s automatic, and produces greater load — and, i n f a c t , t h i s i s what Weinberg and Papakostopoulos observed. Thus, although the t y p i c a l CNV paradigm does not investigate the r o l e s of d i f f e r e n t brain areas i n various kinds of processing, i t would seem that the CNV could be useful i n such investigations to i n d i c a t e the presence of expectancy, time e s t i -mation, and information load. The frequency analysis of EEG data has also shown that various kinds of processing are accompanied by d i s t i n c t i v e changes i n the power spectrum of the EEG. Doyle, Ornstein and Galin (1974), for example, performed Fourier analyses on the EEGs produced during tasks such as w r i t i n g a l e t t e r , constructing a design from Kohs blocks, and doing arithmetic. They found r e l i a b l e differences i n EEG l a t e r a l asymmetry during the performance of d i f f e r e n t tasks, e s p e c i a l l y i n the alpha band, but also i n the beta bands, and occasionally i n the theta band. In a d i f f e r e n t vein, Martindale and Hines (1975) have found that persons d i f f e r i n g i n c r e a t i v i t y , as measured by the Remote Associates Test (Mednik and Mednik, 1967) and the Alternate Uses Test (Christensen, G u i l f o r d , M e r r i f i e l d , and Wilson, 1960) d i f f e r i n the amount of alpha a c t i v i t y generated during d i f f e r e n t kinds of cognitive tasks. The authors postulate that t h i s i s due to d i f f e r e n t i a l a b i l i t y to a c t i v a t e various kinds of c o r t i c a l processes, either s e l e c t i v e l y or g l o b a l l y . 98 These kinds of data from frequency analysis, the CNV and the EP suggest that a research strategy of the kind proposed here could pro-duce data which would show r e l i a b l e associations between the type of task employed and the kind of EEG a c t i v a t i o n produced, probably through a combination of a l l three techniques. In addition, the time sequence of EP or CNV a c t i v a t i o n across the cortex could provide valuable clues as to the operation of various brain functions. Decision-making, f o r example, must take place a f t e r primary perceptual processing i n a disc r i m i n a t i o n learning paradigm and so we would expect the e l e c t r o -p h y s i o l o g i c a l c orrelates of these processes to happen i n a s i m i l a r time sequence. Preliminary data indicate that such time sequencing of the EP i s present (gary E. Schwarts, personal communication, 1975). F i n a l l y , we might hope that i n the future better means w i l l be found to measure the brain a c t i v i t y , perhaps incorporating a mathematical analysis of the a c t i v i t y produced at an array of several hundred electrodes. Such an array may be able to three-dimensionally reproduce the a c t i v i t y of the mind, akin to the way that holographic images are reproduced from a two-dimensional v i s u a l array. 

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