A Real-Time Retinomorphic Simulator Using a Conductance-Based Discrete Neuronal Network

Seungbum Baek, Jason K. Eshraghian, Wesley Thio, Yulia Sandamirskaya, Herbert H.C. Iu, Wei D. Lu

Research output: Chapter in Book/Conference paperConference paper

2 Citations (Scopus)

Abstract

We present an optimized conductance-based retina microcircuit simulator which transforms light stimuli into a series of graded and spiking action potentials through photo transduction. We use discrete retinal neuron blocks based on a collation of single-compartment models and morphologically realistic formulations, and successfully achieve a biologically real-time simulator. This is done by optimizing the numerical methods employed to solve the system of over 270 nonlinear ordinary differential equations and parameters. Our simulator includes some of the most recent advances in compartmental modeling to include five intrinsic ion currents of each cell whilst ensuring real-time performance, in attaining the ion-current and membrane responses of the photoreceptor rod and cone cells, the bipolar and amacrine cells, their laterally connected electrical and chemical synapses, and the output ganglion cell. It exhibits dynamical retinal behavior such as spike-frequency adaptation, rebound activation, fast-spiking, and subthreshold responsivity. Light stimuli incident at the photoreceptor rod and cone cells is modulated through the system of differential equations, enabling the user to probe the neuronal response at any point in the network. This is in contrast to many other retina encoding schemes which prefer to 'black-box' the preceding stages to the spike train output. Our simulator is made available open source, with the hope that it will benefit neuroscientists and machine learning practitioners in better understanding the retina subcircuitries, how retina cells optimize the representation of visual information, and in generating large datasets of biologically accurate graded and spiking responses.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2020
Place of PublicationItaly
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages79-83
Number of pages5
ISBN (Electronic)9781728149226
DOIs
Publication statusPublished - Aug 2020
Event2020 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2020 - Genova, Italy
Duration: 31 Aug 20202 Sep 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2020

Conference

Conference2020 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2020
CountryItaly
CityGenova
Period31/08/202/09/20

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