Oscillatory Recurrent Gated Neural Integrator Circuits (ORGaNICs): A Unifying Theoretical Framework for Neural Dynamics
We introduce a theoretical framework for neural dynamics, based on a family of recurrent neural circuits called ORGaNICs (Oscillatory Recurrent Gated Neural Integrator Circuits). This talk will focus on applying the theory to simulate key phenomena of working memory and motor control. Working memory is a cognitive process that is responsible for temporarily holding and manipulating information. Most of the empirical neuroscience research on working memory has focused on measuring sustained activity and sequential activity in prefrontal cortex and/or parietal cortex during simple delayed-response tasks, and most of the models of working memory have been based on neural integrators. But working memory means much more than just holding a piece of information online. ORGaNICs simulate neural activity with complex dynamics, including sequential activity and traveling waves of activity, that manipulate (as well as maintain) information during working memory. Derivative-like recurrent connectivity, in particular, serves to manipulate and update internal models. In addition, these circuits incorporate recurrent normalization, to ensure stability over time and robustness with respect to perturbations of synaptic weights. The exact same circuits (with the same synaptic weights) convert spatial patterns of premotor activity to temporal profiles of motor control activity, and they are controllable to manipulate (e.g., time warp) the dynamics. These circuits can be implemented with a simplified biophysical (equivalent electrical circuit) model of pyramidal cells. Time permitting, I’ll also say a few words about inference, exploration, prediction, and the role of feedback (top-down) in the brain.