How Much Does Movement and Location Encoding Impact Prefrontal Cortex Activity? An Algorithmic Decoding Approach in Freely Moving Rats
| Autor: | Jamie J. S. Grewal, Barak F. Caracheo, Daniel Leibovitz, Adrian J. Lindsay, Jeremy K. Seamans |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
random forests
Male Computer science Prefrontal Cortex ENCODE Convolutional neural network Machine Learning 03 medical and health sciences 0302 clinical medicine Encoding (memory) medicine Premovement neuronal activity Animals recurrent neural networks Rats Long-Evans Prefrontal cortex ensemble encoding 030304 developmental biology Neurons 0303 health sciences Behavior Animal Movement (music) General Neuroscience Electroencephalography General Medicine New Research Regression 1.1 Rats medicine.anatomical_structure nervous system Cognition and Behavior Space Perception Convolutional neural networks Neuron Nerve Net Neuroscience psychological phenomena and processes 030217 neurology & neurosurgery Locomotion |
| Zdroj: | eNeuro |
| ISSN: | 2373-2822 |
| Popis: | 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. 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 200 ms as rats freely roamed in an experimental enclosure. Regression analyses using generalized linear models revealed that more than 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 ( |
| Databáze: | OpenAIRE |
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