NDLI: Efficient Spiking Neural Network Model of Pattern Motion Selectivity in Visual Cortex

Content Provider	Springer Nature Link
Author	Beyeler, Michael Richert, Micah Dutt, Nikil D. Krichmar, Jeffrey L.
Copyright Year	2014
Abstract	Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.
Starting Page	435
Ending Page	454
Page Count	20
File Format	PDF
ISSN	15392791
Journal	Neuroinformatics
Volume Number	12
Issue Number	3
e-ISSN	15590089
Language	English
Publisher	Springer US
Publisher Date	2014-02-05
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Pattern motion selectivity Spiking neural network MT GPU Real-time CARLsim Neurosciences Bioinformatics Computational Biology/Bioinformatics Computer Application in Life Sciences Neurology
Content Type	Text
Resource Type	Article
Subject	Neuroscience Information Systems Software

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