Education, Faculty of
Kinesiology, School of
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UBCV
Donald, Joshua Reginald
Master of Science - MSc
University of British Columbia
The vestibular system, located bilaterally in the inner ear, plays an integral role in maintaining standing balance and interpreting our perception of self-motion. Healthy aging causes anatomical deterioration in both peripheral/brainstem vestibular regions and central vestibular integration structures including thalamus, cortex, and cerebellum. While traditional assessments of rotational perception rely on minimal detection thresholds, they fail to examine central integration of vestibular information using suprathreshold stimulation. Moreover, these detection threshold protocols often fail to identify well-known effects of aging on the vestibular system. Therefore, this thesis investigated how healthy aging affects peripheral and central vestibular perception of rotation using a suprathreshold stimulation paradigm. Twenty healthy older adults (range: 60-78 years old) and twenty-five healthy young adults (range: 18-29 years old) performed a rotation perception task on a custom-built rotating platform. Participants tracked platform rotation using a rotary dial while experiencing suprathreshold pseudorandom sinusoidal rotations (0.02-0.11 Hz; ±30°) with eyes closed and white noise masking. Peripheral/brainstem vestibular function was assessed by testing the visual vestibulo-ocular reflex (VVOR) using identical pseudorandom sinusoids. Visual-vestibular interactions were evaluated using the subjective visual vertical test (SVV), where participants determined when a vertical line returned to 0° after 30° clockwise and counterclockwise rotations. Performance metrics included frequency-based measures of coherence, gain, and phase between platform and dial rotation, VVOR gain and phase comparing eye velocity to head velocity, and SVV error from both rotation directions. Older adults demonstrated significantly lower coherence (p=0.002) and significantly higher phase shift (p<0.001) in the rotation perception task, indicating impaired central integration of vestibular information. Older adults also showed significantly lower VVOR gain (p<0.001), suggesting peripheral/brainstem vestibular deficits. However, gain differences between age groups were not observed in the perception of rotation task. SVV performance showed no age-related differences, with all participants performing within the accepted error range (±2°). These findings demonstrate that older adults exhibit deficits in central integration of vestibular information that do not directly correlate with peripheral/brainstem function assessments using suprathreshold stimulation. This understanding may inform future clinical techniques for assessing vestibular deficits in older adults and patients with vestibular disorders.
PERIPHERAL AND CENTRAL VESTIBULAR CONTRIBUTIONS TO PERCEPTION OF ROTATION IN HEALTHY AGING by Joshua Reginald Donald B.Sc., Mount Royal University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Kinesiology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2025 © Joshua Reginald Donald, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Peripheral and central vestibular contributions to perception of rotation in healthy aging submitted by Joshua Reginald Donald in partial fulfilment of the requirements for the degree of Master of Science in Kinesiology Examining Committee: Dr. Mark G. Carpenter, Professor, School of Kinesiology, UBC Supervisor Dr. Romeo Chua, Professor, School of Kinesiology, UBC Supervisory Committee Member Dr. J. Timothy Inglis, Professor, School of Kinesiology, UBC Supervisory Committee Member iii Abstract The vestibular system, located bilaterally in the inner ear, plays an integral role in maintaining standing balance and interpreting our perception of self-motion. Healthy aging causes anatomical deterioration in both peripheral/brainstem vestibular regions and central vestibular integration structures including thalamus, cortex, and cerebellum. While traditional assessments of rotational perception rely on minimal detection thresholds, they fail to examine central integration of vestibular information using suprathreshold stimulation. Moreover, these detection threshold protocols often fail to identify well-known effects of aging on the vestibular system. Therefore, this thesis investigated how healthy aging affects peripheral and central vestibular perception of rotation using a suprathreshold stimulation paradigm. Twenty healthy older adults (range: 60-78 years old) and twenty-five healthy young adults (range: 18-29 years old) performed a rotation perception task on a custom-built rotating platform. Participants tracked platform rotation using a rotary dial while experiencing suprathreshold pseudorandom sinusoidal rotations (0.02-0.11 Hz; ±30°) with eyes closed and white noise masking. Peripheral/brainstem vestibular function was assessed by testing the visual vestibulo-ocular reflex (VVOR) using identical pseudorandom sinusoids. Visual-vestibular interactions were evaluated using the subjective visual vertical test (SVV), where participants determined when a vertical line returned to 0° after 30° clockwise and counterclockwise rotations. Performance metrics included frequency-based measures of coherence, gain, and phase between platform and dial rotation, VVOR gain and phase comparing eye velocity to head velocity, and SVV error from both rotation directions. iv Older adults demonstrated significantly lower coherence (p=0.002) and significantly higher phase shift (p<0.001) in the rotation perception task, indicating impaired central integration of vestibular information. Older adults also showed significantly lower VVOR gain (p<0.001), suggesting peripheral/brainstem vestibular deficits. However, gain differences between age groups were not observed in the perception of rotation task. SVV performance showed no age-related differences, with all participants performing within the accepted error range (±2°). These findings demonstrate that older adults exhibit deficits in central integration of vestibular information that do not directly correlate with peripheral/brainstem function assessments using suprathreshold stimulation. This understanding may inform future clinical techniques for assessing vestibular deficits in older adults and patients with vestibular disorders. v Lay Summary The vestibular system, located in our inner ears, detects head movement and tells us about where we are in space. As we age, the vestibular system undergoes natural deterioration, which can lead to issues such as dizziness and maintaining balance. While traditional testing focuses on minimum detectable motion thresholds, this thesis examined how older adults process above-threshold rotational movements. Older and young adults tracked the movement of a rotating platform using a rotary dial. Both groups also completed tests of eye motion and perception of verticality. Older adults struggled more with accurately tracking rotation and displayed somewhat reduced eye movement responses, though their vertical orientation perception remained intact. These findings reveal age-related changes in vestibular motion processing beyond simple detection thresholds. This research could lead to improved diagnostic testing and better interventions for patients with vestibular disorders and balance issues, potentially reducing fall risk in the aging population. vi Preface The study presented in this thesis was conducted in the Neural Control of Posture and Movement Laboratory at the University of British Columbia’s Vancouver campus. At the time of completion, the study has not been submitted for publication. The study was designed and led by Joshua Donald, under the guidance of Drs. Mark G. Carpenter, Romeo Chua, and J. Timothy Inglis. The rotating platform was constructed by Joshua Donald, Dr. Mark G. Carpenter, and Dr. Romeo Chua. Joshua Donald recruited and collected all the older adult data and a subset of young adult data, and oversaw the collection of the remainder of the young adult data, which was conducted by Lisa W. Liu. All data collected for this thesis was analyzed by Joshua Donald. All text and figures presented in this thesis were created by Joshua Donald, under the guidance of Drs. Mark G. Carpenter, Romeo Chua, and J. Timothy Inglis. The protocol described in this thesis has been approved by the University of British Columbia’s Behavioural Research Ethics Board [H23-01839-A003]. The use of generative artificial intelligence (GenAI) was limited to the revision of writing for improved diction and/or clarity, and the refinement of code used in the analysis in this thesis. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ..................................................................................................................................x List of Figures ............................................................................................................................... xi List of Abbreviations .................................................................................................................. xii Acknowledgements .................................................................................................................... xiii Dedication .....................................................................................................................................xv Chapter 1: Introduction ................................................................................................................1 1.1 The Vestibular System .................................................................................................... 1 1.1.1 Vestibular Anatomy ................................................................................................ 1 1.1.2 Vestibular Integration in Standing Balance ............................................................ 4 1.1.3 Perception of Self-Motion ....................................................................................... 4 1.1.4 Vestibular Perception .............................................................................................. 5 1.1.4.1 Vestibular Perception of Rotation ....................................................................... 6 1.2 The Aging Sensorimotor System .................................................................................... 8 1.2.1 Aging and the Vestibular System ........................................................................... 9 1.2.2 Aging and Postural Control .................................................................................. 10 1.2.2.1 Aging on Vestibular Functioning and Reflexes ................................................ 12 1.2.3 Testing of Vestibular Functioning & Perceptual Thresholds in Older Adults ...... 13 viii 1.2.4 Considerations Regarding Vestibular Functioning & Perception Methodology .. 15 1.3 Summary ....................................................................................................................... 18 1.4 Aim & Hypothesis ........................................................................................................ 19 Chapter 2: Methods .....................................................................................................................20 2.1 Participants .................................................................................................................... 20 2.2 Experimental Measures ................................................................................................. 20 2.3 Experimental Protocol .................................................................................................. 24 2.4 Data Analysis ................................................................................................................ 28 2.5 Statistical Analysis ........................................................................................................ 34 Chapter 3: Results ........................................................................................................................36 3.1 Age-related vestibular perception ................................................................................. 36 3.2 Age-related differences in VVOR ................................................................................ 37 3.3 SVV Error ..................................................................................................................... 37 3.4 Effect of VVOR gain on perceptual gain ...................................................................... 38 3.5 Effect of SVV error on perceptual gain ........................................................................ 38 Chapter 4: Discussion ..................................................................................................................45 4.1 Vestibular perception of rotation performance ............................................................. 46 4.2 Age differences of the VVOR ....................................................................................... 48 4.3 No effects of aging on SVV performance ..................................................................... 49 4.4 Correlation between peripheral and central vestibular processing ............................... 50 4.4.1 Vestibular perception of rotation and VVOR ....................................................... 50 4.4.2 Vestibular perception of rotation and SVV .......................................................... 51 4.5 Neural pathways involved in vestibular perception of rotation .................................... 51 ix 4.5.1 Peripheral/brainstem vestibular processing .......................................................... 51 4.5.2 Central vestibular processing ................................................................................ 52 4.6 Potential clinical implications ....................................................................................... 54 4.7 Limitations .................................................................................................................... 54 4.8 Future directions ........................................................................................................... 56 4.9 Conclusion .................................................................................................................... 57 References .....................................................................................................................................58 Appendices ....................................................................................................................................71 Appendix A ............................................................................................................................... 71 Appendix B ............................................................................................................................... 72 x List of Tables Table 3.1. Statistical results of the 2 (Frequency band) x 2 (Age) mixed ANOVA ..................... 39 Table 3.2. Post hoc analyses of significant main effects from the mixed ANOVA ..................... 39 Table 3.3. Independent t-test results for mean SVV error ............................................................ 43 Table 3.4. Linear regressions of perceptual gain to VVOR gain and SVV mean error ................ 43 xi List of Figures Figure 2.1. Perception of rotation experimental setup. ................................................................. 22 Figure 2.2. Calibration trial profile. .............................................................................................. 22 Figure 2.3. Horizontal VVOR test setup. ...................................................................................... 25 Figure 2.4. EOG Calibration schematic. ....................................................................................... 25 Figure 2.5. Protocol schematic. ..................................................................................................... 27 Figure 2.6. Participant calibration trial line of best fit. ................................................................. 29 Figure 2.7. Time domain perception of platform rotation. ........................................................... 30 Figure 2.8. Frequency domain power spectrum of perception of rotation. ................................... 31 Figure 2.9. Neurospec analysis for perception of rotation task. ................................................... 32 Figure 3.1. Group-averaged perception of rotation results in the frequency domain ................... 40 Figure 3.2. Average older adult frequency-dependent coherence ................................................ 41 Figure 3.3. Mean VVOR gain and phase across age groups ........................................................ 41 Figure 3.4. SVV error across age groups ...................................................................................... 42 Figure 3.5. Linear regressions between frequency-dependent perceptual gain and VVOR gain . 44 Figure 3.6. Linear regressions between frequency-dependent perceptual gain and SVV mean error ............................................................................................................................................... 44 xii List of Abbreviations ABC – Activities-specific Balance Confidence ANOVA – Analysis of variance IMU – Inertial measurement unit mTBI – mild traumatic brain injury PIVC – Parieto-insular vestibular cortex PPPD – Persistent postural perceptual dizziness PVP – Position vestibular pause neurons SCD – Semicircular ducts SVV – Subjective visual vertical VOR – Vestibulo-ocular reflex VVOR – Visual vestibulo-ocular reflex VN – Vestibular nuclei VO – Vestibular-only neurons xiii Acknowledgements I would first like to thank my supervisor, Dr. Mark Carpenter, for his invaluable time and support throughout my time here at UBC. Your guidance on the various projects I got myself involved in was exceptional, and I thank you for pushing me to strive for nothing but the best. I also want to thank my committee members, Dr. Romeo Chua and Dr. J. Timothy Inglis. Romeo, I appreciate your patience with me as we debugged various issues with the “Crazy Susan” over its lifetime, and for your expertise when we were getting this project off the ground. Tim, thank you for our enlightening conversations about human anatomy, and for your enthusiasm on all aspects of the vestibular system! I would also like to acknowledge NSERC, the Faculty of Education, and the School of Kinesiology at UBC for their financial support throughout my degree. A very big thank you to everyone past and present in the Neural Control of Posture and Movement lab. Your comradery extends beyond the lab, and I am forever grateful for the community that we have established. Thanks to Emma, Heather, Jeff, and Kyle for being great mentors as my time at UBC was just starting. Thanks to Keara and Xiangwei for being not just great lab mates, but great friends. Thanks to Lisa for her tremendous effort in helping me with data collection. Thanks to Sayna, Emmarie, Cole, Braden, and Aaron for your vibrant energy as new members of the lab. A special thanks to Solenne, Annika, and Ben. I couldn’t have asked for a better cohort to go through graduate school with together, and I deeply cherish our friendship. To my Osborne (and honorary Osborne) friends: Gregg, Nick, Isabel, Paul, Liam, Alex, Candy, Amin, and Xueqing—whether it be traveling to conferences, assisting with data collection, or just being around to talk science, your support and expertise have been invaluable. xiv To my partner, Briana, thank you for being a constant source of strength and encouragement every single day. Lastly, I want to thank my family and friends both here in Vancouver and back home in Calgary. Your steadfast support, whether over the phone or in person, has meant everything to me. xv Dedication This thesis is dedicated to my grandparents, Reg and Chloe Anderson. The value you see in pursuing higher education allowed me to get to this point. Thank you for everything1 Chapter 1: Introduction 1.1 The Vestibular System Located bilaterally, the vestibular system continuously provides us with information about where our head is in space. It is constantly sending information regarding head orientation (i.e., head turned to the left or right, up or down), and whether or not the head is moving in space by way of acceleration in a multi-axial sense, meaning the interpretation of both linear and angular accelerations. The vestibular end organs are always in use, even when motionless due to the constant acceleration of gravity, which helps the vestibular system interpret which way is up relative to gravity. The vestibular system provides tremendous value to how we interpret available sensory information: whether that be reflex-related responses or even how we move about in space. This sensory information can be utilized by the vestibular system to aid the nervous system in producing a corresponding response, whether it be a postural adjustment, spatial orientation or even how we perceive our own motion in space. 1.1.1 Vestibular Anatomy The vestibular end organs are found bilaterally in the inner ear and consist of two integrated sensors, the otolith organs and the semicircular ducts. The vestibular otolith organs and semicircular ducts provide tonic feedback about linear and rotational head accelerations that when integrated with other sources of sensory feedback (e.g., visual and/or somatosensory) can sense gravitationally relative head position and posture (Day & Fitzpatrick, 2004). The otolith organs are made up of two integrated sensors called the utricle and the saccule. These organs are sensitive to linear accelerations both in the vertical and horizontal planes, in which they provide information about acceleration relative to gravity and linear 2 movements in both the anteroposterior and mediolateral planes (Day & Fitzpatrick, 2004). The otolith afferents are connected to hair cells with stereocilia embedded in a gelatinous matrix. On top of this matrix lie otoconia, crystals whose added mass acts to bend the stereocilia in response to linear accelerations (Day & Fitzpatrick, 2004). Linear accelerations bend the hair cells, causing either depolarization or hyperpolarization depending on the direction of stereocilia deflection. Otolith afferents, however, cannot distinguish between tilt and linear acceleration, as the afferents produce identical firing patterns for both movements (Day & Fitzpatrick, 2004; Fernandez & Goldberg, 1976). Due to the otolith’s inability to distinguish between tilt and acceleration, processing at a higher level needs to occur in order to understand the environment and create an Earth-referenced space to be able to navigate the external surroundings. There has been evidence in the place cells of the hippocampus, which encode for spatial location and depend on vestibular information (Day & Fitzpatrick, 2004) and the brain using gravity as an estimate of angular motion (Angelaki et al., 2004; Cullen, 2019) to differentiate between what is tilt and what is linear acceleration. The semicircular ducts (SCD) are responsible for the detection of acceleration that is angular. There are three ducts located bilaterally in the inner ear: anterior, posterior and horizontal ducts. They detect acceleration in a similar matter to the otolith organs by deflection of stereocilia mounted on the hair cells. These hair cells are clustered and project into a dome-shaped, gelatinous structure known as the cupula. The cupula is not sensitive to linear acceleration based on its circular structure and its corresponding internal endolymph movement. When a non-linear acceleration is evoked, the endolymph exerts an inertial force on the cupula, which causes a deflection of the hair cells and causes an excitatory or inhibitory response depending on the direction of deflection. This results in a release of glutamate from the hair cells 3 onto the sensory axons of the vestibular nerve, allowing for the representation (i.e., perception) of the non-linear acceleration. A critical feature of vestibular signal encoding lies in the firing patterns of vestibular afferents. Vestibular afferents maintain a continuous background discharge at rest, even in the absence of head movement (Goldberg & Fernandez, 1971). This tonic activity enables bidirectional signaling: when hair cells depolarize during angular or linear acceleration in one direction, the firing rate of associated afferents increases, whereas when hair cells hyperpolarize during movement in the opposite direction, firing rates decrease (Eatock & Songer, 2011). This physiological mechanism forms the foundation upon which higher-order vestibular processing builds complex motion perception. Together, vestibular information from the end organs (otoliths and SCD) are integrated through a collection of bilateral brainstem nuclei known as the vestibular nuclei. These nuclei are situated along the lateral wall of the fourth ventricle, and extend to the junction of the brainstem and the cerebellum (Barmack, 2003). The vestibular nuclei receive information from primary vestibular afferents of cranial nerve VIII (i.e., vestibulocochlear) originating from the end organs, as well as input from the cerebellum (Angelaki et al., 2004; Barmack, 2003). The vestibular nuclei are divided into four individual portions: superior, inferior, medial and lateral. The superior and inferior portions project onto the cerebellar cortex, whereas the medial and lateral portions are more involved in motor output through the medial and lateral vestibulospinal tracts (Barmack, 2003). Both the medial and lateral vestibulospinal tracts play key roles in the maintenance of standing balance. The medial vestibulospinal tract coordinates head, neck and eye movements, and the lateral vestibulospinal tract transmitting information to motor neurons in the lower limbs. Vestibular information is also relayed through the thalamus towards the cortex 4 which is thought to be responsible for conscious control of movement and awareness of motion-inducing stimuli (Staab et al., 2013). 1.1.2 Vestibular Integration in Standing Balance Despite its seemingly effortless execution, standing balance is a complex task maintained by the integration of sensory information from the visual, somatosensory and vestibular systems. Vestibular feedback plays an important role in the maintenance of standing balance and the execution of motor tasks (Day & Fitzpatrick, 2004). It relays key information regarding head tilt and position relative to gravity through the primary vestibular afferents to the vestibular nuclei in the brainstem, which can then be projected outwards for purposes of stabilizing the vestibulo-ocular reflex (VOR) or through the vestibulospinal tract to generate vestibulospinal reflexes in the lower limb for the maintenance of standing balance and posture (Cullen, 2012). Vestibular information is also relayed through the brainstem nuclei towards the vestibulocerebellum, which also relays information back towards the medial and lateral vestibular nuclei to maintain balance and coordinate eye movements (Barmack, 2003; Morton & Bastian, 2004). Somatosensory sources of information from muscles and joints are also integrated with vestibular information through vestibular-evoked balance responses (Dakin et al., 2007), the lateral vestibulospinal tract, which is responsible for maintaining upright posture and the medial vestibulospinal tract which controls neck muscles to help with the stabilization of the head (Angelaki & Cullen, 2008). 1.1.3 Perception of Self-Motion Through the integration of sensory cues provided by the surrounding environment, we are able to perceive a stimulus of head motion. This may be a stimulus that is generated actively, such as an evoked head motion, or passively, such as experiencing the acceleration of a moving 5 vehicle (Day & Fitzpatrick, 2004). It is crucial that interpretation of these motions differs in order to generate appropriate motor responses to avoid a fall. Active and passive movements are indistinguishable for the sensory systems and requires higher level processing. This suggests that in situations where motion thresholds are measured passively they are also relevant in an active context, such as postural sway (Fitze et al., 2023). Perception of motion can be looked at through a multisensory lens or by isolating a single sensory source of information (Fitzpatrick & McCloskey, 1994). However, for reliable perception of motion to be processed, there typically needs to be multiple sources of sensory input. In normal walking, proprioceptive input from both cutaneous receptors and lower limb muscles is integrated with both visual and vestibular sources of information to allow for relatively effortless execution of motion (Proske & Gandevia, 2012). There can also be issues with perception of motion, as individuals who either misinterpret or fail to perceive motion can lead to either imbalance or a fall. 1.1.4 Vestibular Perception The vestibular system plays an important role in not only maintaining standing balance, but also interpreting how we perceive our spatial orientation and self-generated motion. It is often overlooked in these aspects due to its integration with other sources of sensory information regarding balance control such as vision and somatosensation (Cullen, 2019). It aids in stabilizing gaze through the VOR, the production of limb movements to maintain postural control and being involved in complex tasks, such as navigation and reaching (Cullen, 2012). It also integrates information from the cerebellum, which can help with the generation of motor commands for self-generated movement (Barmack, 2003). More specifically, the vestibular system is crucial for how orientation and movement are perceived and interpreted (Cullen, 2014). Previous studies looking at vestibular thresholds for motion detection have found that 6 rotation in the yaw plane can be perceived at velocities as low as one degree per second (at a frequency of 1 Hz), with further decreases in perception of rotation thresholds seen with increasing frequency (Mergner et al., 1991; Peters et al., 2015). As previously mentioned, the vestibular system primarily perceives motion through the semicircular ducts and otolith organs depending on the nature and context of the motion (i.e., angular versus linear acceleration). It also plays a key role in spatial perception, which is thought to be involved with visual processing in the visual cortex (Angelaki & Cullen, 2008). Due to its integration with other sources of sensory information, studying vestibular perception of motion alone is inherently difficult, and at times thought to not be overly important for the maintenance of standing balance. Work done by Fitzpatrick and McCloskey (1994) suggests that the vestibular system is not important in the perception of sway when proprioceptive and visual sensory information is available. It has been argued, however, that regardless of having other sources of sensory information available, the vestibular system still plays an integral part in the perception of self-motion. Allum and colleagues (1994) demonstrated that individuals suffering from vestibular loss respond much slower to a low velocity perturbation of a support surface in comparison to healthy subjects. Valko and colleagues (2012) also showed that patients with total surgical ablation of their vestibular end organs had a much higher perception of yaw rotations during slow movements. 1.1.4.1 Vestibular Perception of Rotation Due to the inertial characteristics of the semicircular ducts, the vestibular system is an integral component in the perception of rotation about an axis. When a generated motion (active or passive) is applied, the endolymph of the semicircular ducts lags, causing the cupula to deflect the stereocilia, in which vestibular nerve fibers transmit information regarding movement to the VN (Cullen, 2014). This electrophysiological information is crucial in how the vestibular system 7 informs the brain about how this type of motion is perceived. As previously mentioned, the vestibular system’s threshold for perception of whole-body rotation has been shown to be frequency dependent. Previous work has demonstrated that varying frequencies of translation or rotation will not yield equal levels of perception. Grabherr and colleagues (2008) showed that rotational velocity thresholds varied based on the frequency of the stimulation being applied. They found that rotational velocity thresholds dropped from 2.8 degrees per second at 0.05 Hz to 0.7 degrees per second at 0.5 Hz, with the velocity threshold response reaching an asymptote at frequencies above 0.5 Hz. This asymptotic tapering of the velocity threshold during yaw rotation suggests that testing vestibular perception below 0.5 Hz is sufficient with solely vestibular inputs. Mergner and colleagues (1991) further support this frequency range as they found that during a tracking task in between the frequency range of 0.025-0.4 Hz, the phase response of the participant to the chair rotation was accurate and ideal for studying perception. The type of stimulation being delivered will also affect how vestibular perception of rotation is interpreted. Most of the previous work assessing vestibular perception of rotation has used methods of real stimulation such as raised-cosine bell curves (Peters et al., 2015), sinusoids (Mergner et al., 1991), and even constant velocity profiles. St. George and colleagues (2011) used a constant horizontal rotation velocity profile of 20 degrees per second for 16 seconds and found that the participant’s ability to discriminate the rotation decayed exponentially, likely due to the adaptation of the duct-cupula system. This highlights the importance of selecting a rotation profile that is not composed of a constant velocity stimulus. This is also likely why much of the real stimulation research has utilized non-constant or variable stimulation profiles to assess perception of rotation. Profiles such a bell curves or sinusoids have been shown to limit the 8 velocity storage mechanism of the vestibular system (Mallery et al., 2010), preventing potential issues of adaptation of the fluid dynamics of the vestibular end-organs. Electrical or virtual stimulation has also been used as a mean to probe vestibular perception of rotation. This method bypasses the end organs and electrically stimulates the primary vestibular afferents to generate a sensation of virtual rotation. This could be useful as a means of assessing pure vestibular perception without stimulating any non-vestibular cues or influenced by changes at the level of the vestibular receptors. Peters and colleagues (2015) utilized galvanic vestibular stimulation at a frequency range of 0.05-2 Hz in both bell-curve and sinusoidal stimulation profiles and found that virtual and real rotations were roughly identical at a frequency of 1 Hz, but at frequencies above 1 Hz in the virtual rotation protocol, there was a phase shift between the perceived velocity and the actual velocity of the electrical signal of which was not seen in the real rotations. This could be due to the electrical signal being not perceived as angular velocity (Peters et al., 2015), and the issue that electrical vestibular stimulation will undoubtedly stimulate afferents from the otoliths and all three semicircular ducts (Fitzpatrick & Day, 2004), which can further complicate the interpretation of yaw rotation since the head is tilted down by 85 degrees. This suggests that real stimulation of the vestibular system is still quite useful for assessing perception of rotation. 1.2 The Aging Sensorimotor System The global population is aging at a rapid rate. Data have suggested that approximately 11% of the global population is over the age 60, with that rate growing to approximately 22% by the year 2050 (Newgard & Sharpless, 2013). As individuals get older, functionality of the sensorimotor system can begin to deteriorate. This is a normal occurrence in both healthy aging and in older adults with disorders that affect their sensory systems, such as dizziness (Ishiyama et 9 al., 2009). Notable decreases in function have been observed in visual acuity (Maki & McIlroy, 1996), vibration sensitivity (Peters, McKeown, et al., 2016) and thresholds (Johnson et al., 2020) and vestibular perception thresholds (Baloh et al., 1993; Roditi & Crane, 2012; Seemungal et al., 2004). Central and peripheral nervous system deficits have also been seen in aging. Aging causes atrophy and reduced white matter activity in the central nervous system (Goble et al., 2010; Johnson et al., 2020), as well as reduced sensitivity and density of sensory cutaneous receptors in the peripheral nervous system (Johnson et al., 2020; Maki & McIlroy, 1996; Peters, McKeown, et al., 2016). 1.2.1 Aging and the Vestibular System Aging affects the vestibular system. The physiological decline in vestibular functioning has been well documented in older adults. The saccule and utricle experience a 25% decrease in hair cells, while the semicircular ducts experience closer to a 40% reduction. This reduction in otolith hair cells results in decreased sensitivity to translational accelerations and gravity, which could result in issues such as stabilizing gaze during a linear acceleration, such as riding a bus or walking (Day & Fitzpatrick, 2004). Type I hair cell receptors in the vestibular end organs decrease at a higher rate than type II hair cell receptors. Neurons in Scarpa’s ganglion decrease with age, resulting in reduction of the VOR (Ishiyama et al., 2009). Peripheral afferent and vestibular sensory cell reduction result in a decrease of vestibular signaling to the central nervous system (Anson & Jeka, 2016; Ishiyama et al., 2009). Anatomical vestibular deterioration seen in aging also influences issues with dizziness. It has been reported that 24% of the population in the eight-decade experience dizziness lasting at least 1 month, with the prevalence of dizziness increasing to 50% in older adults over the age of 85 (Ishiyama et al., 2009). It has also been reported that 30-35% of older adults experience some 10 sort of vestibular dysfunction (Anson & Jeka, 2016). This typically comes in the form of diagnoses of Meniere’s disease, vestibular neuritis, and most commonly, benign paroxysmal positional vertigo (BPPV) (Anson & Jeka, 2016; Ishiyama et al., 2009). BPPV occurs due to dislodging of the otoconia of the utricle and saccule, eventually moving into the endolymph of the semicircular ducts, causing abnormal fluid displacement and a sense of vertigo. The incidence of BPPV was found to be seven times higher in older adults in comparison to young adults (Ishiyama et al., 2009). Unlike the typical presentations of BPPV, the characterization of BPPV in older adults is associated with degeneration and decreased density of the otoconia due to their observed abnormal shape and fractures. This otoconia-related implication associates well with increased incidence of BPPV in the older population. Although balance and falls related to aging are multifactorial (i.e., possible involvement of visual, somatosensory and/or vestibular deficiencies), the vestibular system seems to have a considerable impact. A previous study done by Fife and Baloh (1993) found that in a group of patients 70 years of age and older who presented to the emergency room with disequilibrium, over 70% did not perform well on rotational vestibular testing and 58% of the subjects tested had experienced one of more falls in previous year. It was also found that these subjects had much greater sway velocity in their posturography measures in comparison to healthy age-matched controls, which was later correlated to their vestibular functioning (Fife & Baloh, 1993). 1.2.2 Aging and Postural Control As the sensory systems of older adults deteriorate with increasing age, this also subjects them to increased risks of postural instability and falls. Falls are one of the most prevalent causes of visits to the emergency room (Accreditation Canada, 2014) and place a tremendous amount of financial stress on the health care system, costing the Canadian healthcare system $10.3 billion 11 dollars in 2018 (Parachute, 2018). Older adults who have experienced a fall previously are also more likely to experience another fall (Ishiyama et al., 2009). Deterioration of the sensory systems also has psychological implications in the older adult population. Fear of falling has been reported in 12-65% of older adults, increasing to 29-92% when a fall has occurred (Legters, 2002). This fear of falling also negatively affects quality of life, in which it has been reported that older adults who are fearful of falling have decreased confidence in their balance, increased anxiety and depression, slower gait speeds and reduced mobility (Carpenter et al., 2006; Legters, 2002; Maki et al., 1991). This highlights the importance in assessing the effects of sensorimotor functioning in older adults from both a financial and public health perspective. Accompanied by the deterioration of the sensory (visual, somatosensory, and vestibular) and central nervous systems seen in aging, the ability to control posture and balance also deteriorates. It has been previously demonstrated that older adults display much larger sway amplitude and frequency in comparison to younger adults (Prieto et al., 1996). Older adults are more unstable in comparison to younger adults, and require greater corticospinal activity, such as observed greater co-contraction of dorsiflexors and greater plantarflexion. Previous work has demonstrated that older men also show a decreased bandwidth range in their plantar flexors in comparison to younger adults when perturbed with electrical vestibular stimulation (Dalton et al., 2014). This suggests that older adults may have much greater difficulty in detecting higher frequency stimuli in comparison to younger adults. Other work looking at plantar skin sensitivity and its relation to postural stability found significant correlations between decreased plantar skin sensitivity and increased postural sway frequency and amplitude (Peters, McKeown, et al., 2016), which would imply the importance of plantar cutaneous involvement in postural control. Older adults also demonstrate increased cutaneous vibrational thresholds and reduced ankle joint position sense, 12 and rely more heavily on proprioception rather than vestibular or visual cues when adjusting to a platform perturbation in comparison to younger adults (Wiesmeier et al., 2015). These declines in key factors for the maintenance of postural control pose increased risk to older adults losing their balance and/or sustaining a fall. 1.2.2.1 Aging on Vestibular Functioning and Reflexes Given the previously described anatomical and physiological declines in vestibular functioning with aging, there is also decline in how the vestibular system responds to functional testing of the labyrinthine system. It has been documented that older adults demonstrate a decline in their VOR, with declines being seen as early as the sixth decade (Roditi & Crane, 2012) with larger deficiencies being seen over the age of 70 (Anson & Jeka, 2016; Peterka et al., 1990; Roditi & Crane, 2012; Seemungal et al., 2004). This age-related decline in VOR has been shown to continue to degrade over time, as a study done by Baloh and colleagues (2001) demonstrated in a longitudinal study age-related decreases in both VOR gain and increases in phase lead during a sinusoidal rotational testing after five yearly visits. These age related declines in VOR suggest central deterioration at the level of the vestibular nuclei and of Scarpa’s ganglion (Anson & Jeka, 2016; Ishiyama et al., 2009), which can present issues of increased dizziness or disorientation (Seemungal et al., 2004). A test of otolith functioning through recording a corresponding electromyographical response from a specific muscle (typically sternocleidomastoid (cervical) or inferior oblique (ocular)) after delivering an audible pulse to one ear, known as the vestibular-evoked myogenic potential (VEMP), has been shown to be affected by aging. Previous work has shown significant decreases in VEMP amplitudes and increased latencies with increasing age as early as the fourth decade (Brantberg et al., 2007) and further declines being reported starting from the age of 60 13 (Ishiyama et al., 2009; Maes et al., 2010). Su and colleagues (2004) also found that after the age of 60, VEMP amplitudes decline significantly. It has also been shown that there is a correlation between VEMP amplitudes and hearing loss in individuals over the age 70 (Zuniga et al., 2012). These related declines in VEMP amplitude with increasing age may imply deterioration of the saccule and the inferior vestibular nerve (Ishiyama et al., 2009). It has also been suggested that previous work demonstrating irregular VEMPs in association with BPPV and Meniere’s disease may be a potential indication of the sources of such disorders being a saccule-related issue (Akkuzu et al., 2006). Declining performance in other types of vestibular testing has also been seen with aging. Previous work has demonstrated increasing slow-component velocity in caloric testing in older adults (Maes et al., 2010), which could be attributed to deterioration in central inhibitory mechanisms, implying more excessive reactions to such tests of vestibular functioning. It has also been shown that performance of the subjective visual vertical test declines with age in both clockwise and counterclockwise rotations of the subjective visual vertical device when the visual reference was altered (Abdul Razzak et al., 2020; Kobayashi et al., 2002). This aligns with age related declines in visual-vestibular functioning (Ishiyama et al., 2009), visual acuity with head rotation (Roditi & Crane, 2012) and an impaired ability of their central mechanisms to integrate sensory information when certain sensory cues are unreliable (Maki & McIlroy, 1996). 1.2.3 Testing of Vestibular Functioning & Perceptual Thresholds in Older Adults Assessing vestibular functioning in older adults has also been examined by using more robust stimulation profiles, such as sinusoidal rotation tests. Baloh and colleagues (1993) found that by using a 0.05 Hz sinusoidal rotation test, older adults demonstrated decreased VOR gain and increased VOR phase shift, which became more pronounced with increasing age. Chang and 14 colleagues (2014) also found that using a seated 0.5 Hz sinusoidal rotation test that older adults had higher mean VOR and velocity detection thresholds compared to younger adults, however this result was non-significant. They also found no significant difference in VOR gain and phase in comparison to younger adults using this sinusoidal rotation test. Seemungal and colleagues (2004) also found that despite differences in VOR thresholds, they observed no significant differences with aging in perceptual thresholds. These non-significant findings could imply central compensation of the peripheral deficits, as Peters and colleagues (2016) found that when replicating the 0.1 Hz raised-bell cosine curve perception task using virtual stimulation (i.e., electrical vestibular stimulation), older adults actually demonstrated lower detection thresholds in comparison to younger adults. It has also been hypothesized that since the neural pathways that encode for perception and nystagmus (i.e., VOR) are functionally different, it would explain why vestibular perception work assessing detection thresholds in comparison to reflexive thresholds have conflicting results (Anson & Jeka, 2016; Ishiyama et al., 2009; Seemungal et al., 2004). When sensory systems begin to degrade with aging, it is reasonable to imply that this may affect how motion, either self-generated or induced passively, is perceived. It has been shown that older adults have greater difficulty with navigating throughout the world in comparison to younger adults (Anson & Jeka, 2016) which is typically due to older adults either not properly weighting available sensory information, inducing a protective balance strategy, or even both. These difficulties are exacerbated through deterioration of the sensory systems involved in perception of self-motion. Due to the well-known anatomical and physiological deficiencies in the aging vestibular system, it is reasonable to assume that this will have an effect on vestibular perception thresholds. Kingma (2005) found that older adults had higher perceptual 15 thresholds using 1 Hz linear translations at a velocity of 40 degrees per second, with these observed thresholds advancing linearly with increased age. Bermudez Rey and colleagues (2016) demonstrated that older adults exhibited higher detection thresholds for translations in all planes (yaw, roll, and translation at 1 Hz), with changes in detection thresholds being observed as early as the age of 40. Roditi and Crane (2012) also found that perceptual detection thresholds above 0.5 Hz using a raised-bell cosine paradigm were affected by age in participants 50 years of age and older. Peters and colleagues (2016) demonstrated similar threshold differences when using a protocol involving a 0.1 Hz raised-cosine bell curve, in which older adults had higher detection thresholds in comparison to younger adults. 1.2.4 Considerations Regarding Vestibular Functioning & Perception Methodology Researchers have been attempting to find a reliable method of assessing vestibular perception for decades. Much of the vestibular perception work that has been published consists of a variety of both subjective (e.g., SVV, direction estimation) and physiological reflex (e.g., VOR, VEMPs) measures to determine how the vestibular system interprets and centrally integrates rotational motion. Grabherr and colleagues (2008) attempted to create a type of frequency-dependent ‘vestibulogram’ for perception of yaw rotation in healthy young adults to be used as a potential clinical tool for threshold inconsistencies. This work, however, does not necessarily translate well to the older adult population, as it has been argued that assessments using minimal detection thresholds are not sensitive enough to show age-related vestibular deterioration (Maes et al., 2010), as well as previous reports determining no significant differences between detection thresholds in young and older adults (Baloh et al., 1993; Chang et al., 2014; Peterka et al., 1990; Seemungal et al., 2004). It has been suggested that these low frequency stimuli are not strong enough to be able to demonstrate age-related changes in the 16 vestibular system (Maes et al., 2010), likely due to adaptation of the central vestibular system to compensate for peripheral deterioration (Peters, Blouin, et al., 2016). Maes and colleagues (2010) discuss that there is need for a standardized practice of assessing vestibular functioning, in which they propose different techniques to possibly evaluate age-related vestibular deficiencies. While they found no significant difference in their sinusoidal harmonic acceleration test at varying frequencies between 0.01 and 0.2 Hz, they did see significant decreases in VOR gain and increases in VOR phase shift in older adults compared to young adults by using a pseudorandom rotational test composed of a summation of the individual frequencies in between 0.01 and 0.2 Hz. This supports the notion that a more robust rotational test could be useful in assessing vestibular functioning in older adults using suprathreshold signals. It could also be beneficial to assess vestibular functioning by having participants track a sinusoidal signal to see if peripheral deterioration of the vestibular system is also seen at a more central level. Looking more broadly at visual tracking of a sinusoid, Jagacinski and colleagues (1993, 1995) found that older adults demonstrated decreased gain in tracking both a sinusoidal (1995) and modulated sinusoidal (1993) signal when the frequency of the signal was steadily increased. This could be characterized by issues of integrating proprioceptive and visual cues to match the output of the tracked signal but could also involve deterioration of visual-vestibular interactions. Colino and colleagues (2017) also found that in a task involving participants being instructed to maintain a visual cursor between two barriers using a steering wheel, older adults made considerably more tracking errors than young adults. Maki and colleagues (2001) also found that during the tracking of sum of sines signal with or without a platform perturbation being induced, older adults demonstrated increased onset of tracking deviation and onset time relative to platform acceleration in comparison to younger adults, suggesting that older adults potentially exhibit 17 limitation in attentional processing capacity. Anson and colleagues (2021) have further emphasized lower attentional processing by demonstrating that older individuals with low VOR gain and/or deteriorated otolith functioning were found to make significantly larger spatial orientation errors. These tracking tasks could also be useful in showing slowing and impaired ability to adjust to changing conditions that is seen in older adults, notably in their postural reactions (Maki & McIlroy, 1996) and could be integrated to assess vestibular functioning in older adults as a part of a potential “dual-task” paradigm, which could look at both how older adults utilize vestibular information to cognitively track a rotational signal/profile. While there have been many methods of assessing vestibular perception in both young and older adults, most of the studies conducted rely on minimum detection thresholds, vestibular reflex responses, subjective measures of perception (i.e., SVV), or fail to utilize a signal with enough complexity to overcome the adaptive central compensatory mechanisms involved in the aging vestibular system (Maes et al., 2010). What is most notable, however, is there is little to no research that has looked at how participants, both young and old, perceive rotation while standing. Zanelli and colleagues (2011) have looked at vestibular perception of rotation while standing, however their methods relied on previously used techniques of minimal detection thresholds and angle perception using raised cosines, which have been shown to potentially not be enough of a stimulus to demonstrate age-related vestibular deterioration (Maes et al., 2010). It has also been shown that central processing of vestibular stimulation only occurs when there is a task requiring the head and/or trunk to be supported upright (Luu et al., 2012), as well as vestibular-evoked muscle reflexes not being seen during a seated task of lower leg muscle co-contraction (Fitzpatrick et al., 1994). While there is reason to believe that in order to perform perceptual tests of vestibular functioning, other sources of conflicting sensory information need 18 to be eliminated as they will likely outweigh vestibular cues. It could be argued, however, that many of the previous studies using padded chairs are still providing proprioceptive cues to participants regarding their position, in which proprioceptive cues will outweigh vestibular cues regarding position (Fitzpatrick & McCloskey, 1994). Standing balance has been shown to involve vestibular input through corticospinal pathways, and participants with vestibular deficits demonstrate increased sway compared to those with normal vestibular functioning (Allum et al., 1994), as well as older adults demonstrating increased postural sway compared to younger adults (Maki & McIlroy, 1996). It is therefore valuable to assess how both young and older adults perform in vestibular perception during standing, as these results may translate better to those who suffer from vestibular disorders that cause dizziness (e.g., BPPV) and the effects of aging on how older adults integrate vestibular cues to maintain postural control. 1.3 Summary The vestibular system plays a key role in interpreting how we move about in the world and how we perceive movement. Much of the previous literature assessing vestibular perception of rotation has focused on minimal reflex or detection thresholds, such as the VOR and VEMP responses and estimates of amplitude or direction discrimination, subjective measures such as the SVV, and through the use of repeated stimulation profiles, such as sinusoids. These methods may be useful in assessing detection thresholds in healthy young adults but are typically not robust enough to demonstrate changes in vestibular deterioration that is well-known in older adults. There is a gap in the literature to find a novel technique that does not rely on minimum threshold values and that can assess perceptual differences in how young and older adults evaluate motion. There is also little to no research that has shown reliability of demonstrating central processing of vestibular information using suprathreshold stimulation, as much of the 19 previous literature has focused on functioning/perception of the peripheral vestibular system by using tests of perceptual thresholds or assessing peripheral/brainstem reflex pathways such as the VOR. Moreover, much of the vestibular perception literature performs these assessments while seated, which presents an issue of ecological validity to how perception would be altered when participants are standing or even locomoting throughout the world when the vestibular system is actively processing information. It is also known that young and older adults utilize different strategies and sources of sensory information to maintain postural control. 1.4 Aim & Hypothesis The aim of this thesis was to examine the effects of aging on the vestibular perception of rotation using a suprathreshold stimulation paradigm, while also assessing both peripheral and central vestibular functioning. We hypothesized that older adults would demonstrate decreased ability to match the rotation of the platform using the rotary dial, as well as an increased in phase shift in tracking the rotation of the platform (Peters et al., 2015). We also hypothesized that older adults would demonstrate decreased gain between rotary dial rotation and platform rotation, in which central gain compensation mechanisms at the level of the periphery/brainstem (Peterka et al., 1990; Peters, Blouin, et al., 2016) would not be reflected in our suprathreshold perception of rotation task. Lastly, we hypothesized that older adults would demonstrate decreased VOR gain (Baloh et al., 1993, 2001; Paige, 1991), signifying deterioration at the periphery that may not necessarily reflect central vestibular processing. 20 Chapter 2: Methods 2.1 Participants Twenty healthy older adults (range: 60-78 years old) and twenty-five healthy young adults (range: 18-29 years old) participated in this study. Participants self-reported having no symptoms or previous diagnoses of any neurological or vestibular disorders that may affect their balance. Prior to commencing data collection, participants were fully informed regarding details of the study and written informed consent was obtained from each participant. Ethics was obtained through the University of British Columbia’s Behavioural Research Ethics Board [H23-01839-A003]. 2.2 Experimental Measures To subjectively assess participant’s confidence to perform daily activities without falling or experiencing unsteadiness, the Activities-specific Balance Confidence (ABC) scale (Powell & Myers, 1995) was used (Appendix A). The ABC scale has been shown to be highly reliable in assessing balance confidence in older adults (Botner et al., 2005). The rotational stimuli were generated using a custom-built horizontal rotating platform which performs rotations in the yaw plane. Rotation of the platform were generated by a stepper motor and controlled using an Arduino board with five different preset stimuli sampled at 100 Hz. To record the trajectory of the platform in real time, a potentiometer was affixed to the underside of the platform to record both clockwise and counterclockwise rotations as corresponding voltages (Figure 2.1). These recorded voltages were recorded and collected in real time and sampled at 100 Hz (Spike2, Cambridge Electronic Designs (CED), Cambridge, UK). Perception of the rotational stimulus was collected from the participant from a handheld device equipped with a rotary dial mounted to an adjustable stand set in front of the participant at 21 approximately the height of the iliac crest or to the point at which elbow flexion angle is approximately 90°. The handheld device was built using a rotary dial that was limited by two lightly tensioned springs to minimize drift (Cleworth et al., 2019; Cleworth & Carpenter, 2016). Perception of the platform movement was recorded and collected as voltage in the same manner as the rotating platform. The rotation profiles provided to the stepper motor were generated and imported into the Arduino board to be controlled with a small breadboard with assigned rotational profiles to an individual button. Five different profiles were used for this study: four different variations of our rotational stimulus and a single calibration profile, with each variant being assigned to its own unique button on the breadboard. The calibration profile consisted of a series of clockwise and counterclockwise single-amplitude movements that always started in the clockwise direction and was of equal magnitude in both directions (Figure 2.2). The amplitudes used were 15°, 30°, and 45°. Located on top of the handheld device is indication of amplitudes of direction for the purpose of ensuring participants are familiar with rotating the rotary dial through each amplitude of the calibration trials (i.e., turning the dial clockwise 15° to match the platform turning clockwise 15°). The trial stimulation profiles included four different variations of a pseudosinusoidal waveform composed of frequencies between 0.02 and 0.11 Hz and a maximum amplitude of 30° in both the clockwise and counterclockwise direction. These frequencies and amplitudes have been found to be reliable for assessing vestibular perception of rotation (Becker et al., 2000; Mergner et al., 1991; Philbeck et al., 2006) and for conducting reliable assessments of gain and phase (Peters et al., 2015). 22 Figure 2.1. Perception of rotation experimental setup. Schematic of the rotating platform, and rotary dial setup. Participants stand in the middle of the platform and rotate the dial in the corresponding direction of the platform in real time. Figure 2.2. Calibration trial profile. Platform rotation profile for perception of rotation calibration trials. Stepwise rotations are indicated by direction and amplitude on y-axis, with rotations in the clockwise direction being positive, and counterclockwise rotations being negative. 23 To limit any extraneous sources of auditory information from the platform and the surrounding environment, participants were instrumented with noise cancelling headphones that played a noisy white noise signal during the performance of all the experimental trials. To assess whether head motion is aligned with the rotational axis of the platform, inertial measurement units (Noraxon Ultium EMG, Noraxon USA, Ltd.) (IMUs) were placed at the centre of the rotational axis of the platform at the level of the vertex of the cranium. This IMU setup ensured that any acceleration generated by the platform was consistent with what was experienced at the level of the participant’s vestibular system. A third IMU was placed at the level of the seventh cervical vertebra for the purpose of assessing how participants were modulating their sway while on the platform. The IMUs were set up to collect both gravitational acceleration (in units of thousandths of the force of gravity; mG) through its embedded accelerometer and angular velocity through its embedded gyroscope (angular degrees per second). Due to the functional limitations of collecting IMU data in our data collection software (i.e., Spike2), the IMU data was concurrently collected in its proprietary software (Noraxon MyoMuscle, Noraxon USA Ltd.) and sampled at 400 Hz. To limit and account for any data synchronization issues, a 0.5 second, 5 V synchronization pulse originating from Spike2 was sent to the Noraxon receiver as an analog output (Power1401, CED, UK), which was primed to start IMU data collection as soon as the pulse arrived. A second synchronization pulse was sent to the Noraxon receiver at the conclusion of each trial. To assess peripheral vestibular functioning of the SCD, a test of the visual VOR (VVOR) was performed using a rotating chair and the same pseudosinusoidal stimulation profile utilized for the perception of rotation trials. Due to the first twenty participants in our young adult group being collected without testing the VOR, a limited sample of five healthy young adults (age 24 range: 20-27) was used to make group comparisons. Eye movement was recorded using a DC electro-oculography (EOG) system (SC2000/2SP, UFI, Morro Bay, California, USA), in which Ag/AgCl electrodes were placed just outside of the outer canthus of each eye with a ground electrode placed on the forehead. To get baseline recordings of each participant’s eye movements, a EOG calibration trial was performed. Participants were instructed to perform a series of horizontal looks towards set markers to the left (L) and to the right (R) without moving their head. Two markers were placed in either direction (L and R) with amplitudes of 30 and 45 degrees, and were adjusted to be eye-level using a laser pointer. Participants were then instructed to maintain their gaze on a target located directly in front of them. The same pseudosinusoidal rotation profiles used in the perception of rotation task were used for testing the VVOR. Participants performed four consecutive trials lasting approximately 113 seconds in the dark, in which they were asked to let the platform move while maintaining just their gaze on the target. The EOG traces of each trial were recorded and collected at a sampling frequency of 2000 Hz (Spike2 and Power1401, CED, UK). Head position and velocity were recorded using a head-mounted gyroscope from an IMU in Noraxon’s proprietary software and was sampled at 400 Hz. This was the maximum sampling frequency allowed for our gyroscope data due to unmodifiable constraints of the Noraxon software. 2.3 Experimental Protocol Participants were fully informed about the study design and procedure prior to data collection. A safety harness mounted to a climbing rope that was attached securely to the ceiling was fitted to the participant. The amount of tension in the rope was sufficient to prevent a fall from occurring and to limit the amount of sensory and positional cues regarding location of the rotation of the platform. Participants were then instructed to step onto the platform, aligning their 25 medial malleoli to the centre post of the platform with their feet positioned shoulder width apart. A test of participant’s horizontal VVOR was then performed (Figure 2.3), in which calibration values from the series of looks were recorded (Figure 2.4). Following the calibration trial, participants performed four trials of pseudorandom rotations while maintaining their gaze directly at the target located in front of them. Figure 2.3. Horizontal VVOR test setup. Schematic of EOG and head IMU placement on a subject with a representative trace of EOG and head IMU velocity. Figure 2.4. EOG Calibration schematic. Visual representation of the EOG calibration trial and directional magnitudes of the targets. 26 Following the test of the VVOR, participants proceeded into the perception of rotation trials. The handheld device was adjusted to a height in which participants could freely rotate the rotary dial without limitation in either direction. Participants then performed an eyes-open pseudo-calibration trial by turning the rotary dial through each amplitude of the calibration profile without any platform movement. This was to ensure participants were familiar with using the dial and accustomed to how each amplitude in both directions felt. This pseudo-calibration trial was then followed by another eyes open calibration trial, in which participants were instructed to repeat the same method in which they rotated the dial for the pseudo-calibration trial; however, these amplitudes were matched veridically to the rotation of the platform. This was used as a “real practice” trial to ensure participants were now both familiar with using the rotary dial and tracking the rotation of the platform. A final calibration trial was performed following the same method as the previous eyes open calibration trial, except participants were instructed to keep their eyes closed and head level. This was monitored by a spotter who was positioned beside the participant. This trial was used as a final practice for participants to become familiar with the rotary dial and platform, as well as being used as a baseline measure of participants’ ability to track each amplitude of rotation. This was necessary to be able to make comparisons across participants and groups, as not all participants would necessarily perceive (i.e., rotate the rotary dial) the same amplitudes as other participants. During the experimental trials, participants were fitted with noise cancelling headphones that played a noisy white noise signal to limit auditory cues from the surrounding environment and the platform and were informed that the remainder of the study would be performed with their eyes closed. Participants were informed of trial duration and characteristics of the 27 stimulation delivered by the platform, as the maximum amplitude of rotation would be no greater than 30° in either direction in comparison to the calibration trials which reached a maximum amplitude of 45°. To ensure participant safety and comfort, they were informed that trials could be halted at any point during a trial or in between trials if a break was needed. Participants performed the first block of experimental trials, which consisted of one of each variation of the four stimulation profiles for a total of four trials per testing block (Figure 2.5). Each trial lasted approximately 113 seconds, with the first 10 seconds of each trial consisting of a random “waggle” to limit any potential learning effects of stimulation profiles and to ensure participants were not consistently starting each trial rotating in the same direction. After the first block of trials, participants took a mandatory seated break to limit any fatigue from standing on the platform. Figure 2.5. Protocol schematic. Protocol schematic of a single block used for experimental trials. Each profile will introduce a random 10 s “waggle” to limit direction bias and potential learning effects. Representative raw platform stimulation traces are shown on the right, demonstrating four unique stimulation profiles. The same four trials shown will also be used in the second experimental block. Following the first block of experimental trials performed on the platform, participants performed a seated SVV ‘bucket’ test, which consisted of six trials: three clockwise rotation 28 trials and three counterclockwise rotation trials. The SVV test was conducted using a custom-built device composed of a bucket mounted horizontally supported by a wooden frame. The subjective vertical line consisted of a visible strand of tape aligned with the centre of bucket. The experimenter conducted the rotation of the bucket manually and verified the accuracy of each rotation performed using an inclinometer (iPhone 14 Pro; Apple, California, USA) calibrated to the level of the bucket. The experimenter informed the participant that the bucket will be rotated either clockwise or counterclockwise to 30°, in which it will be slowly rotated back towards centre until the participant deemed through their visual perception of the vertical line that they have returned to the initial starting position (i.e., 0°). Participant accuracy of the subjective visual vertical test was recorded manually by the experimenter for each trial performed. A second block of perception of rotation trials was performed following the SVV trials, in which participants returned to the rotating platform and performed four additional trials using the same pseudorandom profiles that were used in the first block. This was done to assess test-re-test reliability across participants and age groups. 2.4 Data Analysis ABC questionnaire data were tallied and scored for each older adult. The total out of 1600 was then converted to a percentage. In the case that participants demonstrated low-level ABC scores (<50% balance confidence), their perception of rotation data was examined individually. Potentiometer data from both the platform and handheld device were exported into MATLAB formatted files for the purpose of analysis. All signal processing and data analysis was performed in MATLAB (MathWorks, USA) using custom-made scripts for this study specifically. The signals from the platform and handheld device from the eyes-closed calibration 29 trial was used to determine the amplitude of rotation collected from the rotary dial and its corresponding relationship to the amplitude of the platform (i.e., participant’s perceived 15° to the actual platform’s 15°). The corresponding values from each rotation were aligned in ascending order to calculate a line of best fit through the values of the handheld device and the platform (Figure 2.6). The slopes of these lines of best fit were used as calibration values for the experimental trials. Figure 2.6. Participant calibration trial line of best fit. Representative participant calibration data from the eyes closed calibration trial. Values from each rotation of the platform (Black) and handheld device (Red) are plotted in ascending order. A linear line of best fit through the calibration data is used to determine the slope. The experimental trial data from the platform and handheld device were unbiased by removing the mean value from each signal and filtered using a 0.5 Hz 2nd order dual pass low-pass Butterworth filter. The signals from the platform and handheld device were multiplied by their calibration values from the calibration trial before then being converted from voltage to degrees by determining the voltage value from a known 30° amplitude in the platform signal. The initial 10 second random “waggle” was removed from each trial, resulting in approximately -15 -30 -45 +15 +30 +45Rotations ( o )-0.8-0.6-0.4-0.200.20.40.60.8Amplitude ( V )Subject Calibration SlopePlatformHand Device30 0 10 20 30 40 50 60 70 80 90 100Time ( s )-50050Degrees ( o )PlatformSubject103 seconds of data per trial being used for analysis. The processed data from each trial were visually inspected in the time domain to detect any significant participant errors or phase lag in the signal and as a visual comparison across trial blocks (Figure 2.7). The time series data from the platform and handheld device were concatenated by block and converted into the frequency domain using a custom-built function that performs a one-sided Fourier transform. The frequency domain data were plotted to look at power across frequencies and trial block by overlaying the handheld device data on top of the platform data (Figure 2.8). The frequency domain data were also used to compare the power difference between young and older adults in how they perceived the rotation of the platform. Figure 2.7. Time domain perception of platform rotation. Representative time domain trace of a single trial. Platform rotation over time shown in degrees (Black) are overlaid with participant’s perception of rotation using the rotary dial (Red). 31 Figure 2.8. Frequency domain power spectrum of perception of rotation. Representative power spectrum for a single block of four concatenated trials. Platform power spectrum of rotation (Black) is overlaid with participant’s perception of rotation power spectrum (Red). To look at the relationship between the perception of rotation of the participant to the platform, frequency-based measures of coherence, gain and phase were calculated and analyzed using the Neurospec 2.0 signal processing toolbox for MATLAB (Figure 2.9). Coherence is a frequency-based measure between the unitless values of 0 (no correlation) to 1 (completely correlated) that can assess the relationship between two signals at specified frequencies (Halliday et al., 1995). To perform these analyses, the toolbox requires a single matrix of concatenated data therefore participant data from the platform and handheld device were concatenated separately by block, consisting of a matrix of four pseudorandom rotation trials. This matrix of concatenated time series data was passed through a Hanning window, followed by the Neurospec command function (window length: 8192 data points; sampling rate: 100 Hz; frequency resolution: 0.012 Hz) producing matrices of coherence, gain and phase (in units of radians). 0 0.05 0.1 0.15Frequency (Hz)01234567AmplitudePlatformSubject32 Neurospec outputs were analyzed within the frequency range of the pseudorandom stimulation profiles (0.02-0.11 Hz). Any data points in the coherence analysis that failed to reach the level of the 95% confidence interval were not further analyzed, as the gain and phase measures at the frequencies that do not reach this threshold are considered unreliable, in which these values are replaced with NaNs. Figure 2.9. Neurospec analysis for perception of rotation task. Descriptions of coherence, gain and phase analyses used for the perception of rotation task Due to our pseudorandom stimulation profiles containing two significant peaks in their frequency power spectrum, more detailed data analysis was conducted within these frequency bands. These peaks were labelled as a low frequency (LF; 0.02-0.05 Hz) band and a high frequency (HF; 0.09-0.11 Hz) band. Coherence, gain and phase in these bands was used for group averaging analysis, in which frequency-dependent coherence, gain and phase group averages were calculated as a method of comparing between groups (young adults and older adults) as well as trial blocks. 33 A calculation of phase lag was conducted using the frequency-dependent phase values. Phase lag was calculated by using the data points in the LF and HF phase bands by fitting a linear regression model to these values. The slope of the linear regression model represents the phase lag, measured in milliseconds. EOG data collected from the test of the VOR were normalized by removing the mean value from each trial and down sampled from 2000 Hz to 400 Hz so that the sampling frequency of our EOG data matched that of our head-mounted IMU. The EOG and IMU data were filtered using a 0.5 Hz 2nd order dual-pass low pass Butterworth filter, followed by a 0.005 Hz 2nd order dual-pass high pass filter to mitigate any potential drift in the signal. The EOG data were smoothed using a 0.5 Hz 2nd order dual pass Bessel filter to eliminate existing noise from the EOG signal. Due to the collection constraints of our IMU sensors, and the need to use two different collection softwares, our EOG and head IMU data were synchronized to sync pulses delivered prior to the start of a trial and at the end of a trial. These sync pulses were used to align our EOG and IMU data for processing, and to ensure our trials contained the same number of data points. Following synchronization, both EOG and IMU data had the first 10 seconds of the trial cut, as this represented the random “waggle” in our profiles as previously mentioned. A line of best fit was used to calibrate our EOG data and convert the data from voltage (V) to degrees for each participant. The slope of this line of best fit was used as the calibration factor for each subject. Our EOG data were then differentiated from position (degrees) into velocity as degrees per second (deg/s) using a central difference method. Individual inspection of each trial was conducted to ensure no artifacts were visible in the signal. Any potential noise artifacts underwent further processing using an adaptive window based on spike duration, followed by a median filter to reduce noise while preserving the shape of the signal, and Gaussian smoothing to 34 refine the velocity profile. EOG and IMU velocity data were then concatenated and converted into the frequency domain using a similar method to our perception of rotation analysis. Both sets of concatenated data were then run through the Neurospec function to get gain and phase values of our test of the VVOR. Gain represents the ratio of EOG velocity to head velocity, whereas phase represents the phase shift of the EOG signal compared to the head velocity signal. All data analyses discussed were used to assess whether there was a difference in how older adults perceived rotation in comparison to young adults. Group averages on a frequency-dependent basis were calculated for the purpose of performing statistical analyses. 2.5 Statistical Analysis Data analyses were conducted using custom MATLAB scripts and functions, accompanied by the Neurospec 2.0 signal processing MATLAB toolbox for the purpose of frequency-based analysis. Statistical analyses were all performed using SPSS (Version 28, IBM, Chicago, IL). To assess test-re-test reliability across our two blocks of perception of rotation data, parametric and non-parametic correlations were run on coherence, gain and phase measures in both groups, as well as both frequency bands. Significant correlations resulted in blocks being pooled in both groups, in which group averages of coherence, gain and phase would be taken on the pooled block data instead of being analyzed individually. To determine whether there were both within-subject and between-subject differences on our perception of rotation data, a 2x2 mixed analysis of variance (ANOVA) was done on coherence, gain, phase, and phase lag data (Figure 2.9). Our within-subject factor was frequency (LF and HF bands) and our between-subject factor being age (older vs. young adults). Significant 35 main effect interactions of the ANOVA were followed up with post hoc Bonferroni-corrected t-tests, in which contrasts were deemed significant at p£0.0125. Only the HF band of our VVOR data was used for the purpose of statistical analysis due to potential issues with unreliable gain in our LF band caused by gaze drift. Independent samples Welch’s t-tests were done on our VVOR gain and phase data to determine differences between groups. To determine whether there were differences in SVV performance between age groups, independent t-tests were performed on mean SVV error data in both clockwise and counterclockwise directions. Linear regressions were done on perception of rotation gain and VVOR gain to assess whether there was correlation between the two measures across groups. Linear regressions were also done on perception of rotation gain and mean SVV error to see if there was correlation between the two tasks. Statistical significance for all tests was set at p£0.05. 36 Chapter 3: Results 3.1 Age-related vestibular perception Assessment of test-re-test reliability between blocks 1 and 2 of the vestibular perception of rotation task using parametric and non-parametric correlations were found to be statistically significant for gain and phase in both age groups and frequency bands (Appendix B). Coherence was only statistically significant in the older adults’ group and did not reach significance for the young adults’ group (r=0.054, p=0.796), as well as both frequency bands (LF: r=0.112, p=0.593; HF: r=0.179, p=0.391). This was presumed to be due to a lack of variability, rather than poor reliability in the young adult group, as their coherence was very high, at the upper limit of the measure, and had limited variability. As majority of the perceptual measures reached significance, blocks 1 and 2 were pooled together to analyze the effect of frequency and age. The results of the 2 (frequency) by 2 (age) mixed ANOVA (Table 3.1) found a statistically significant main effect of frequency band on coherence (F(1,43)=10.187, p=0.003, hp2=0.192) and gain (F(1,43)=92.631, p<0.001, hp2=0.683), in which there was increased coherence and gain in the HF band compared to the LF band (Figure 3.1). However, there was no significant main effect of frequency on phase (F(1,43)=2.711, p=0.107, hp2=0.059). A main effect of age was significant for coherence (F(1,43)=10.712, p=0.002, hp2=0.199) and phase (F(1,43)=24.661, p<0.001, hp2=0.364), where young adults had increased coherence and decreased phase shift compared to the older adults. There was no significant main effect of age on gain (F(1,43)=3.568, p=0.066, hp2=0.077). Despite a significant main effect of age on phase, there were no significant main effects of frequency or age for phase lag (Table 3.1). A significant frequency x age interaction for coherence was found (F(1,43)=4.033, p=0.05, 37 hp2=0.086), in which post hoc Bonferroni-corrected t-tests (Table 3.2) revealed that coherence in the LF band was significantly lower than coherence in the HF band in older adults (Figure 3.2; t=-3.293, p=0.003) and that older adults had significantly lower coherence in the LF band compared to younger adults (t=-3.200, p=0.005). 3.2 Age-related differences in VVOR One participant was removed from our VVOR dataset due to technical issues with collection of our EOG data, which led to coherence not reaching the 95% confidence interval threshold (Halliday et al., 1995) in the respective HF frequency band that was used for analysis. Therefore, the analysis of our VVOR data contains 19 older adults and 5 young adults (Figure 3.3). A significant difference in VVOR gain was seen between age groups (t=-4.493, p<0.001), where young adults had higher gain values compared to older adults. There was no significant difference in VVOR phase shift between older and young adults (t=-1.301, p=0.208). 3.3 SVV Error One participant in our young adults’ group was determined to be a statistical outlier in averaged clockwise rotations, as their z-score exceeded our threshold of ±3.29 (3 SDs). Their data were corrected to the next closest non-outlying value in this direction for the purpose of statistical analysis (Field & Miles, 2010). Older adults and young adults were accurate in detecting true vertical in the SVV task (Table 3.4). There were no significant differences between mean SVV error in either direction of rotation across age groups (counterclockwise error: t=1.249, p=0.220; clockwise error: t=0.512, p=0.612). An important note is some participants had mean errors of 0 degrees in either direction (Figure 3.3; counterclockwise: 12 older, 6 young; clockwise: 9 older, 5 young). 38 3.4 Effect of VVOR gain on perceptual gain To examine whether a participant’s VVOR gain is correlated to perception of rotation gain, a linear regression was performed between VVOR gain and LF and HF perceptual gain (Table 3.5, Figure 3.4). There was no significant correlation between LF perception gain and VVOR gain in both the older (R2=0.012, p=0.652) and young adult groups (R2=0.686, p=0.083). There was also no significant correlation between HF perception gain and VVOR gain in the older adult group (R2=0.005, p=0.773). There was a significant correlation between HF perception gain and VVOR gain in the young adults’ group (R2=0.898, p=0.014). It is important to note, however, that correlations in the young adult group are being performed on five subjects due to the VVOR data in this group being collected as a follow-up analysis. 3.5 Effect of SVV error on perceptual gain To examine whether performance on the SVV task is correlated to the perception of rotation task, linear regressions between mean SVV error and LF and HF perceptual gain were performed (Table 3.5, Figure 3.5). Similar to the results of the VVOR-perceptual regression, there were no significant correlations between mean SVV error and LF perception gain in both the older (R2=0.101, p=0.173) and young (R2=0.157, p=0.083) adult groups. There were also no significant correlations between mean SVV error and HF perception gain in the older (R2=0.137, p=0.108) and young (R2=0.139, p=0.105) adult groups. 39 Table 3.1. Statistical results of the 2 (Frequency band) x 2 (Age) mixed ANOVA. Effect sizes are reported as the partial eta squared (hp2). Significant main effects are indicated in bold (p£0.05). Table 3.2. Post hoc analyses of significant main effects from the mixed ANOVA. Effect sizes are reported as Cohen’s d. Significant differences are indicated in bold (p£0.0125). 40 Figure 3.1. Group-averaged perception of rotation results in the frequency domain. (A) Averaged power spectrum across frequencies for both older (blue) and younger (red) adults. Black line represents the averaged platform power spectrum across all subjects in both groups, indicating two distinct areas of power in the platform signal. (B, Left) Average coherence across individual frequencies. (B, Right) Box plots of averaged coherence data in both frequency ranges. (C, Left) Average gain across individual frequencies. (C, Right) Box plots of averaged gain data in both frequency ranges. (D, Left) Average phase (in radians) across individual frequencies. (D, Right) Box plots of averaged phase data in both frequency ranges. Error bars in the lefthand plots represent standard error of the mean. Asterisks (*) indicate statistically significant differences (p<0.0125).41 Figure 3.2. Average older adult frequency-dependent coherence. Box plots of coherence in both the LF and HF bands in older adults, as indicated by the legend on the far right. Asterisks (*) indicate statistically significant differences (p£0.0125). Figure 3.3. Mean VVOR gain and phase across age groups. Box plots of VVOR gain (left) and phase (right) in both age groups, as indicated by the legend on the far right. Asterisks (**) indicate statistically significant differences (p£0.001). 42 Figure 3.4. SVV error across age groups. Distribution of mean SVV error of both age groups in both directions. ‘Left’ refers to counterclockwise rotations. ‘Right’ refers to clockwise rotations. Each data point represents the mean of three trials per direction. Horizontal red lines indicate mean error values for each group. 43 Table 3.3. Independent t-test results for mean SVV error. Effect sizes are reported as Cohen’s d. Significant differences are indicated by bold type (p£0.05). Table 3.4. Linear regressions of perceptual gain to VVOR gain and SVV mean error. Correlations are reported as the R-value squared (R2). Significant correlations are indicated by bold type (p£0.05).44 Figure 3.5. Linear regressions between frequency-dependent perceptual gain and VVOR gain. Regressions shown by frequency band (columns) and age groups (older: blue; young red). R-squared values of the line of best fit and p-values are reported directly on the plots. Figure 3.6. Linear regressions between frequency-dependent perceptual gain and SVV mean error. Regressions shown by frequency band (columns) and age groups (older: blue; young red). R-squared values of the line of best fit and p-values are reported directly on the plots. 45 Chapter 4: Discussion In this study, we examined the effects of healthy aging on vestibular perception of rotation and peripheral vestibular functioning. We utilized a rotating platform that oscillated in the yaw plane using pseudorandom rotation profiles, in which participants were instructed to track the rotation of the platform using a handheld rotary dial. We employed two standard clinical assessments of vestibular reflexes/functioning, in which we utilized a test of the VVOR to assess peripheral/brainstem functioning of the semicircular ducts, as well as the SVV “bucket” test to look at visual-vestibular functioning of the utricle. We aimed to determine whether central processing of vestibular perception of rotation was affected by healthy aging, and whether these results differed or not from well-established clinical testing of the peripheral/brainstem vestibular mechanisms. Participants in the older adult group demonstrated significantly decreased coherence and increased phase shift irrespective of frequency range in comparison to the young adult group (Table 3.1, Figure 3.1). A significant frequency x age interaction for coherence showed that older adults had significantly lower coherence in the LF frequency range in comparison to the young adults, as well as significantly lower coherence in the LF frequency range in comparison to the HF frequency range (Table 3.1). Older adults also had significantly lower VVOR gain in comparison to young adults (Figure 3.2). There were no significant differences in VVOR phase shift between older and young adults, as well as no significant differences in SVV mean error between groups. When comparing whether vestibular perception of rotation gain was correlated to VVOR gain and SVV mean error, there were no significant correlations across all regressions performed. 46 4.1 Vestibular perception of rotation performance Test-re-test reliability was strong across both age groups. Statistically significant Pearson correlations demonstrate that our perception of rotation task is reliable across repeated blocks for coherence, gain and phase, further reinforcing its potential as a viable tool of assessing vestibular functioning in healthy aging. During the perception of rotation task, a significant main effect of frequency was seen for coherence and gain, in which increased coherence and gain was observed in the HF frequency band compared to our LF band. These results are supported by previous studies utilizing real rotation tracking in similar frequency ranges, in which they saw increased coherence (Peters et al., 2015) and gain (Mergner et al., 1991) with increasing frequency in healthy young adults. Our results further reiterate that vestibular perception is typically tested as a function of frequency. We also found that tracking the rotation of our platform became more accurate at higher frequencies. This is consistent with previous work showing that perceptual thresholds for yaw rotation decrease as frequency increases (Grabherr et al., 2008; Peters et al., 2015; Valko et al., 2012). Significant main effects of age were also seen for both coherence and phase, in which older adults demonstrated decreased coherence and increased phase shift in comparison to our young adult group. The findings are in line with previous studies that looked at phase values during perception of rotation studies, in which increased phase shifts were seen with increased age at various frequencies (e.g., 0.05 Hz) (Baloh et al., 1993; Maes et al., 2010; Peterka et al., 1990). This increase in phase shift is thought to be a component of deterioration of the velocity storage system of the vestibular system, which helps with the processing of low frequency movements (Ishiyama et al., 2009). Our data also demonstrated a significant interaction between 47 frequency and age for coherence, in which simple effects of frequency for the older adult group was significant, and a simple effect of age being significant for LF coherence, in which older adults had significantly lower coherence in the LF band in comparison to the young adult group, as well as HF coherence being significantly greater than LF coherence in the older adult group (Table 3.1). These findings further reinforce the difficulty older adults may have in perceiving low frequency perturbations/rotations, as evident in the vestibular perceptual threshold literature comparing older to young adults where increased perceptual thresholds at low frequency rotations (e.g., 0.1 Hz) are seen with aging (Peters, Blouin, et al., 2016; Seemungal et al., 2004). Although significant main effects of frequency were found for gain, there were no significant differences between our older and young groups for gain, as well as no significant frequency x age interactions for gain (Table 3.1). It is thought that even though there are well-known anatomical deficits of the vestibular periphery and brainstem with aging, there is a frequency-specific central compensation that amplifies vestibular signals to compensate (Anson & Jeka, 2016; Ishiyama et al., 2009). For example, Peters and colleagues (2016) demonstrated that there was no difference in real direction discrimination thresholds between older and young adults at a frequency of 1 Hz, in which they argue that central gain compensation may be playing a role in this finding. An important note, however, is they did see significant differences at a frequency of 0.1 Hz (included in our HF frequency band), yet our results found no main effect of age on gain, nor a significant frequency x age interaction that could be assessed in our HF frequency range for gain. Our results did show a trend towards a significant main effect of age for gain (p=0.066), suggesting that central gain compensation could be reaching a hypothetical limit before it can no longer account for deficits at both the periphery and centrally. It is important to note the assessment of detection thresholds compared to suprathreshold vestibular 48 perception, in which detection thresholds have been suggested to better represent the periphery, whereas suprathreshold perception tasks requiring central vestibular integration of information (Chang et al., 2014). 4.2 Age differences of the VVOR In the assessment of the horizontal VVOR, our data showed a significant difference in VVOR gain, in which our older adult group had lower gain in comparison to our young adult group (Figure 3.3). This finding is consistent with previous work at similar frequencies, which also found significant decreases in VOR gain in older adults (Baloh et al., 2001; Peterka et al., 1990; Seemungal et al., 2004). As previously mentioned, the idea of central gain compensation to account for anatomical deficits in the periphery has been thought to potentially occur in the VN in the brainstem (Brooks et al., 2015), an important centre of VOR integration. Previous work has also contradicted previous findings of VOR gain differences in aging, in which no significant differences were seen (Chang et al., 2014), in which it would be assumed that gain compensation is occurring. It has been argued, however, that central gain compensation cannot maintain the VOR as aging continues, in which the periphery will continue to deteriorate (Peterka et al., 1990), leading to differences in VOR gain. Unlike VVOR gain, there was no significant difference in VVOR phase shift between our older and young adult groups (Figure 3.3). Previous work in similar frequency ranges contradict our results, as they have shown significant differences in VOR phase shift comparing older to young adults, with it increasing with age (Baloh et al., 1993, 2001; Paige, 1991; Peterka et al., 1990). A hypothesis as to why our phase values are not different between age groups could come from the question of velocity storage, which deteriorates with healthy aging (Ishiyama et al., 2009). Previous work utilizing similar frequencies to our range used for VOR analysis (i.e., HF 49 band) have used high velocities through rotating chairs (e.g., 60 deg/s; Baloh et al., 1993). High velocity rotations will saturate the velocity storage mechanism of the horizontal SCDs, which typically occurs at 10-20 deg/s in young adults. The role of the velocity storage mechanism of the vestibular system is to reduce phase lead, which could explain why these differences in VOR phase shift between age groups is only being seen in studies that utilize high velocity. Our rotation profiles were not reaching velocities close to a level of saturation, which could be an explanation of our lack of differences in VVOR phase shift between age groups (despite a difference in VVOR gain). 4.3 No effects of aging on SVV performance There was no significant difference between older and young adults for mean SVV error in either direction of rotation (Figure 3.4, Table 3.3). Our mean SVV error was also well within normal range (Table 3.3), as the accepted error for healthy individuals on SVV performance is ±2 degrees (Akin & Murnane, 2009). These results align with previous work utilizing the SVV to compare age groups, which also saw no significant differences between older and young adults using tilts of 30 (Kobayashi et al., 2002) and 18 degrees in either direction (Abdul Razzak et al., 2020). Although there are well known anatomical deficiencies in the utricle (the otolith organ stimulated during the SVV), older adults are still performing well within normal range on this assessment. This could raise the issue of central gain compensation to mitigate the effects of otolith deterioration, or that older adults tend to rely more on vision to maintain balance in comparison to young adults (Madrigal et al., 2023), otherwise downweighing their otolith cues and upweighting visual cues. This is supported by animal work which showed that VN units in the brainstem corresponding to otolith information were active during self-motion translation and translation of a visual field (Daunton & Thomsen, 1979). 50 4.4 Correlation between peripheral and central vestibular processing 4.4.1 Vestibular perception of rotation and VVOR Regressions between both LF and HF perceptual gain and VVOR gain were not correlated in older adults. LF perceptual gain and VVOR gain were also not correlated in young adults (Table 3.4, Figure 3.5), suggesting that participant’s perceptual gains were not influenced by their VOR gains. Correlation between HF perceptual gain and VVOR gain in young adults did reach significance, however due to our low sample size in this group (n=5), this finding is subjected to type I error. The lack of correlation between perceptual and VVOR gains in older adults suggests that vestibular functioning at the level of the periphery/brainstem may not explain what is occurring more centrally in terms of vestibular processing. Chang and colleagues (2014) also argue that the lack of correspondence between VOR and detection thresholds suggest that higher-level functioning is likely responsible regarding how information at the periphery is interpreted/integrated. As previously mentioned, our results suggest differences in how vestibular processing at the level of periphery/brainstem and central vestibular processing are not correlated in healthy aging. This is likely due to mechanisms that maintain the VOR are different from those that project upwards in the vestibulospinal tract (Cullen, 2019; Wagner et al., 2021). After VN integration, second-order processing of the VOR occurs in position vestibular pause (PVP) neurons, whereas self-motion perception gets processed through vestibular only (VO) neurons, which project upwards towards the thalamus and cortex (Cullen, 2019). The key pathway differences diverging from the VN could explain why our results differed, notably in terms of differences seen between perceptual and VOR measures, as well as the lack of correlation between the two. 51 4.4.2 Vestibular perception of rotation and SVV Regressions between both LF and HF perceptual gain were not significantly correlated to mean SVV error in both age groups (Table 3.4, Figure 3.6). The results from these regressions suggest that performance during the SVV tasks may not explain how participants would perform on the perception of rotation task, even though both tasks require some sort of vestibular integration, albeit from different sources of acceleration (SVV: linear; perception of rotation: angular). This lack of correlation is also supported by unequal reductions in hair cells in both the SCDs (40%) and the otoliths (25%), which experience deterioration at different rates (Anson & Jeka, 2016; Ishiyama et al., 2009). If deterioration at the periphery was occurring at an equal rate, we could potentially expect those with increased SVV errors to also perform worse at the perception of rotation task. 4.5 Neural pathways involved in vestibular perception of rotation Our results suggest that central vestibular processing in older adults is different compared to young adults, as shown by the significant differences in coherence and phase shift (Table 3.1). Moreover, we demonstrate that vestibular processing at the level of the periphery/brainstem is affected in older adults, in which we saw significant differences in VOR gain (Figure 3.3). However, these findings were not found to be correlated to one another (Table 3.4, Figure 3.5), suggesting that aging effects at the level of the periphery/brainstem may not be directly proportional to aging effects at the central processing level. The following section discusses neuroanatomical implications of aging on the vestibular system. 4.5.1 Peripheral/brainstem vestibular processing Well-known anatomical deficits associated with the aging vestibular periphery have been documented in several histopathological and animal model studies. Decreases in end-organ hair 52 cells, vestibular afferents, and VN neurons are shown with increased age, beginning as early as the fifth decade (Anson & Jeka, 2016; Ishiyama et al., 2009). Hence it would be reasonable to assume the VOR pathway, which consists of Scarpa’s ganglion, the VN, and the extraocular motor nuclei, would presumably be affected with increased age. Previous work has demonstrated decreased VOR gain with increasing age (Baloh et al., 1993; Paige, 1991), which has been suggested to be an effect of anatomical deterioration of the pathway previously mentioned (Maes et al., 2010; Zalewski, 2015). These decreases in VOR gain have been suggested to be due to a deterioration of the velocity storage mechanism, which has the role of reducing phase lead and the time constant of the VOR (Furman & Redfern, 2001). This mechanism is likely to have afferent connections to the vestibulocerebellum through Scarpa’s ganglion and the VN, and efferent connections through the medial longitudinal fasciculi, which is responsible for controlling extraocular muscles. The age-related decreases in these synaptic connections, as well as deterioration at the level of the VN, could be responsible for an affected VOR in older adults. 4.5.2 Central vestibular processing Accompanied with deterioration of the peripheral/brainstem pathways of the vestibular system, there is also evidence to suggest that central vestibular pathways are also being affected by healthy aging. Perception of self-motion relies on vestibular signals being transmitted from the VN to the thalamus and subsequently to cortical regions such as the parieto-insular vestibular cortex (PIVC) and the temporo-parietal junction (Dieterich & Brandt, 2015). Stimulation of the PIVC has produced vestibular sensation, as well as evidence of perception of motion being impaired through lesions to this area (Cullen, 2019). Both these regions have also been shown to have significant degradation with increased age in fNIRS studies (Karim et al., 2013). Deterioration of this network can manifest as difficulties with spatial updating to self-motion, in 53 which older adults demonstrate issues with adapting their position when only vestibular cues are provided (Cullen, 2019; Dieterich & Brandt, 2015). Our significant difference in phase shift in our older adult group could be a spatial updating issue, in which temporal inaccuracies in neural representation of motion velocity is being represented. Older adults also demonstrate disinhibition of GABA-ergic receptors in the cerebellum, which disrupts vestibular processing through the thalamus (Shaikh et al., 2013). This may lead to increased difficulty in perceiving self-motion as the signal-to-noise ratio deteriorates, in which older adults are more susceptible to self-motion illusions (Zalewski, 2015). Our results demonstrating decreased coherence in our perception of rotation task could represent deterioration of this signal-to-noise ratio at this level. The cerebellum is also likely being affected by aging, and playing a role in our explaining our results. More specifically, the vestibulocerebellum is involved in velocity storage that extends the neural representation of vestibular self-motion from the level of the periphery (Barmack, 2003). Age-related deterioration of this area has been shown to affect the velocity storage mechanism, resulting in a more rapid decay of vestibular perception after passive motion cessation (Barmack, 2003; Shaikh et al., 2013). The fastigial nucleus, one of the key cerebellar output structures that projects to the VN and vestibulo-thalamic regions (Barmack, 2003), also demonstrates deterioration in aging populations. This, accompanied with decreased white matter in the cerebellar peduncles and thalamus, are underlying factors that older adults demonstrate an increased reliance on visual information even when this visual information is erroneous (Jeka et al., 2006). Our decreased coherence in our perception of rotation task could also be explained by this deterioration, as the integrity of white matter is crucial for the neural encoding of rotational signals in this region of the brain (Barmack, 2003). 54 4.6 Potential clinical implications The results of this thesis demonstrate clear differences between perception of rotation, the VOR and visual-vestibular interactions. It has been demonstrated that reflex-based (i.e., VOR) and perceptual-based neural pathways are governed by partially independent neural mechanisms. This revelation is particularly important in the context of healthy aging, where older adults have shown clear anatomical and physiological vestibular deficiencies (Anson & Jeka, 2016; Ishiyama et al., 2009), accompanied by declines in vestibular functioning. Despite these well-established shortcomings in older adults, clinical testing remains largely reflex-based. The absence of correlation between our perception of rotation and VOR measures in particular suggest that reflexive assessments alone may not address perceptual dysfunction, which could contribute to disorientation, dizziness, and even fall risk in older adults. Moreover, the lack of correlation between our perception of rotation task and SVV performance suggests that visual-vestibular interactions to support spatial orientation is possibly governed by independent pathways in the central vestibular system. These findings highlight the need to potentially include vestibular perception as a metric of functioning in both future research and clinical applications. 4.7 Limitations Our study had several limitations that should be addressed when interpreting these results. First, our pseudosinusoidal profiles for our platform rotations were composed of very low frequencies concentrated between two bands: an LF band (0.02-0.05 Hz) and an HF band (0.08-0.12 Hz). Typical vestibular perception of rotation studies are performed within 0.05 and 2 Hz, as this is the natural operating frequency range of the vestibular system (Peters et al., 2015). The SCDs also operate as high pass filters, and become less sensitive at very low frequencies. This could lead to participants, notably our older adult group, to potentially rely more on 55 somatosensory cues rather than vestibular cues (Wiesmeier et al., 2015). Our rotation profiles may also not be robust enough to fully encompass age-related vestibular deterioration, as the adaptive characteristics of the central vestibular system to compensate for peripheral deterioration may be playing a role (Maes et al., 2010), notably in our perceptual gain results. It would be interesting to investigate the effects of aging using a different frequency range, likely one that overcomes central gain compensation. Maes and colleagues (2010) have suggested high velocities (~180 deg/s) are required to see age-related gain differences, as it is possible that at this point central gain amplification can no longer compensate for deficits at the periphery. This, however, would potentially require modifications to our setup, and would subject participants to uncomfortable rotational accelerations. Our study also had participants maintain a head position that was perpendicular to gravity (i.e., 0 degrees), which does not place the horizontal SCDs in the same plane as the rotation of our platform. Future work should instruct participants to maintain their head 17 degrees down, in which the plane of rotation of the platform is perpendicular to the plane of rotation of the horizontal SCDs. We also only collected VVOR data on a group of 5 healthy young adults, in which it is difficult to make conclusions about how our VVOR data compares to our older adult group and is subjected to type I error. Collection of additional young adults would allow for more meaningful comparisons of the VOR between age groups. Lastly, our older adult group was largely (95%) recruited from a local exercise program, in which our participants were mostly healthy and taking part in physical activity weekly, as well as having high confidence in maintaining their balance while performing daily activities (mean 56 ABC scale score: 15.0±0.9). This subgroup may not represent the population when it comes to looking at the effects of aging on vestibular perception of motion. 4.8 Future directions There are a few notable directions that can be taken utilizing this protocol. First, increasing the sample size of our young adult group for assessing the VVOR to make better comparisons across age groups would help increase our statistical power and mitigate type I error. Second, it would be interesting to investigate how patients with vestibular lesions, such as unilateral vestibular loss, perform on our perception of rotation task. Previous work looking at perceptual thresholds in bilateral vestibular ablation patients demonstrated significantly increased perceptual thresholds compared to healthy controls (Valko et al., 2012), and assessing whether central vestibular pathways are also affected in vestibular patients would be valuable. Another clinical population of importance would involve investigating how individuals with mild traumatic brain injuries (mTBI) (e.g., concussions) perform on our perception of rotation task. Individuals with mTBIs often report issues with balance and dizziness, which has been linked to damage at both peripheral and central vestibular system (Akin et al., 2017). Assessing performance on our perception of rotation task can potentially help researchers and clinicians determine to what extent an individual’s mTBI is affecting their central vestibular processing. Lastly, assessing vestibular perception of rotation in individuals with anxiety-linked balance disorders, such as persistent postural-perceptual dizziness (PPPD) would be of interest. PPPD is often onset in individuals who have previously suffered a vestibular event, and can be exacerbated in patients suffering from anxiety (Staab et al., 2013, 2017). Patients with PPPD have also reported having greater difficulty tolerating passive motion (Staab et al., 2013), similar to our perceptual protocol. Our perception of rotation task could be a valuable tool at assessing 57 how patients with PPPD are utilizing central vestibular processing, and if this pathway is affected by fear and/or anxiety. 4.9 Conclusion In conclusion, this thesis provides evidence of differences between peripheral/brainstem vestibular processing and central (i.e., thalamo-cortical, cerebellar) vestibular processing and how healthy aging affects the processing of this information. The findings of this thesis highlight how matching (i.e., coherence) and timing (i.e., phase shift) of a response to a horizontal rotation is potentially affected centrally, in addition to deficits at the periphery, evidenced by our VOR comparison. This thesis opens the door for potentially new strategies of assessing vestibular functioning in aging populations, which can potentially be applied clinically to help mitigate the growing financial and ecological burden of falls and dizziness in older populations. 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Otology and Neurotology, 33(9), 1586–1592. https://doi.org/10.1097/MAO.0B013E31826BEDBC 71 Appendices Appendix A: Activities-specific Balance Confidence (ABC) Scale Patient Name: ____________________________________________ Date: _______________________ The Activities-specific Balance Confidence (ABC) Scale* Instructions to Participants: For each of the following activities, please indicate your level of confidence in doing the activity without losing your balance or becoming unsteady from choosing one of the percentage points on the scale from 0% to 100% If you do not currently do the activity in question, try and imagine how confident you would be if you had to do the activity. If you normally use a walking aid to do the activity or hold onto someone, rate your confidence as if you were using these supports. 0% 10 20 30 40 50 60 70 80 90 100% No Confidence Completely Confident How confident are you that you will not lose your balance or become unsteady when you… 1. …walk around the house? _____% 2. …walk up or down stairs? _____% 3. …bend over and pick up a slipper from the front of a closet floor? _____% 4. …reach for a small can off a shelf at eye level? _____% 5. …stand on your tip toes and reach for something above your head? _____% 6. …stand on a chair and reach for something? _____% 7. …sweep the floor? _____% 8. …walk outside the house to a car parked in the driveway? _____% 9. …get into or out of a car? _____% 10. …walk across a parking lot to the mall? _____% 11. …walk up or down a ramp? _____% 12. …walk in a crowded mall where people rapidly walk past you? _____% 13. …are bumped into by people as you walk through the mall? _____% 14. …step onto or off of an escalator while you are holding onto a railing? _____% 15. …step onto or off an escalator while holding onto parcels such that you cannot hold onto the railing? _____% 16. …walk outside on icy sidewalks? _____% *Powell LE & Myers AM. The Activities-specific Balance Confidence (ABC) Scale. Journal of Gerontology Med Sci 1995; 50(1):M28-34. Total ABC Score: __________ Scoring: _____________ / 16 = Total ABC Score Patient Signature: ___________________________________________ Date: _____________________ Therapist Signature: __________________________________________ Date: _____________________ __________% of self confidence MEDICARE PATIENTS ONLY 100% - _____% Function = _____% Impairment 72 Appendix B: Test-Re-test reliability correlations
Thesis/Dissertation
eng
Kinesiology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Carpenter, Mark G.
Peripheral and central vestibular contributions to perception of rotation in healthy aging
Text