Spatially distributed computation in cortical circuits
journal contributionposted on 06.05.2022, 09:38 authored by Sergei Gepshtein, Ambarish S Pawar, Sunwoo Kwon, Sergey SavelievSergey Saveliev, Thomas D Albright
The traditional view of neural computation in the cerebral cortex holds that sensory neurons are specialized, i.e., selective for certain dimensions of sensory stimuli. This view was challenged by evidence of contextual interactions between stimulus dimensions in which a neuron’s response to one dimension strongly depends on other dimensions. Here, we use methods of mathematical modeling, psychophysics, and electrophysiology to address shortcomings of the traditional view. Using a model of a generic cortical circuit, we begin with the simple demonstration that cortical responses are always distributed among neurons, forming characteristic waveforms, which we call neural waves. When stimulated by patterned stimuli, circuit responses arise by interference of neural waves. Results of this process depend on interaction between stimulus dimensions. Comparison of modeled responses with responses of biological vision makes it clear that the framework of neural wave interference provides a useful alternative to the standard concept of neural computation.
Neuromorphic memristive circuits to simulate inhibitory and excitatory dynamics of neuron networks: from physiological similarities to deep learning
Engineering and Physical Sciences Research CouncilFind out more...
Salk Institute’s Sloan-Swartz Center for Theoretical Neurobiology
Kavli Institute for Brain and Mind
Conrad T. Prebys Foundation
NIH (R01-EY018613 and R01-EY029117)