Predicting proprioceptive cortical anatomy and neural coding with topographic autoencoders
Proprioception is fundamental for the control of movement, its loss producing profound motor deficits. Yet basic questions of how pose and movement are represented, as well as how these representations are arranged across the somatosensory cortex, are unclear. To this end, we adopt a task-driven modelling approach, using a spiking variational autoencoder to approximate a population of cortical neurons. We optimize the model to encode natural movement stimuli derived from recordings of human kinematics and impose biological constraints which we hypothesise to be important for reproducing charac
Fri, Mar 10, 2023