Generalized ORGaNICs: Towards a Unifying Framework for Neural Dynamics

It has been hypothesized that complex functions across different brain areas are accomplished through a set of canonical neural computations of the same form. Yet, a theoretical framework that employs these computational motifs to explain neural activity across different neural systems remains unknown. Oscillatory Recurrent Gated Neural Integrator Circuits (ORGaNICs) is a recently proposed framework capable of simulating key neurophysiological, cognitive and perceptual phenomena including working memory, sensory processing and attention, and motor control. Here, we derive a generalized class of ORGaNICs, enabling us to broaden the range of cognitive and perceptual phenomena that can be recapitulated by this framework under realistic biophysical constraints. We show that these circuits can simulate stochastic gamma-band oscillatory activity in primary visual cortex and the stimulus-dependence of oscillation amplitude and frequency. We also characterize the complex dynamics of working memory delay period activity in the prefrontal cortex (PFC). We show that generalized ORGaNICs can replicate brief bursts of narrow-band gamma oscillations in the PFC while maintaining self-sustained attractor states, and assess the circuit’s robustness with respect to noise.