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How much does movement and location encoding impact prefrontal cortex activity? An algorithmic decoding approach in freely moving rats

University of British Columbia

Specialized brain structures encode spatial locations and movements, yet there is growing evidence that this information is also represented in the rodent medial prefrontal cortex (mPFC). Disambiguating such information from the encoding of other types of task-relevant information has proven challenging. In order to determine the extent to which movement and location information is relevant to mPFC neurons, tetrodes were used to record neuronal activity while limb positions, poses (i.e. recurring constellations of limb positions), velocity and spatial locations were simultaneously recorded with two cameras every 200ms as rats freely roamed in an experimental enclosure. Regression analyses using Generalized Linear Models revealed that over half of the individual mPFC neurons were significantly responsive to at least one of the factors and many were responsive to more than one. On the other hand, each factor accounted for only a very small portion of the total spike count variance of any given neuron (<20% and typically <1%). Artificial Neural Networks and Random Forests were used to analyze ensemble activity and revealed that ensembles were usually superior to the sum of the best neurons in encoding movements and spatial locations. These results indicate that movement and location information have a small impact on any individual mPFC neuron, yet because these weak signals are so widely distributed across the population, this information is strongly represented at the ensemble level.

Text

2018-04-09

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/65232

Neuroscience

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/