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Article

A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity

1
Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain
2
Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid, 28040 Madrid, Spain
3
Laboratory of Clinical Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain
4
Department of Civil Engineering and Computer Science, University of Rome “Tor Vergata”, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Jenny C. A. Read
Biology 2021, 10(8), 801; https://doi.org/10.3390/biology10080801
Received: 8 July 2021 / Revised: 12 August 2021 / Accepted: 16 August 2021 / Published: 19 August 2021
(This article belongs to the Special Issue Information Processing in Neuronal Circuits and Systems)
A computational model of primates’ early visual processing, showing orientation selectivity, is presented. The system importantly integrates two key elements: (1) a neuromorphic spike-decoding structure that considerably resembles the circuitry between layers IV and II/III of the primary visual cortex, both in topology and operation; (2) the plasticity of intrinsic excitability, to embed recent findings about the operation of the same area. The model is proposed as a tool for the analysis and reproduction of the orientation selectivity phenomenon, whose underlying neuronal-level computational mechanisms are today the subject of intense scrutiny. In response to rotated Gabor patches the model is able to exhibit realistic orientation tuning curves and to reproduce responses similar to those found in neurophysiological recordings from the primary visual cortex obtained under the same task, considering different stages of the network. This demonstrates its aptness to capture the mechanisms underlying the evoked response in the primary visual cortex. Our tool is available online, and can be expanded to other experiments using a dedicated software library developed by the authors, to elucidate the computational mechanisms underlying orientation selectivity.
Since the first half of the twentieth century, numerous studies have been conducted on how the visual cortex encodes basic image features. One of the hallmarks of basic feature extraction is the phenomenon of orientation selectivity, of which the underlying neuronal-level computational mechanisms remain partially unclear despite being intensively investigated. In this work we present a reduced visual system model (RVSM) of the first level of scene analysis, involving the retina, the lateral geniculate nucleus and the primary visual cortex (V1), showing orientation selectivity. The detection core of the RVSM is the neuromorphic spike-decoding structure MNSD, which is able to learn and recognize parallel spike sequences and considerably resembles the neuronal microcircuits of V1 in both topology and operation. This structure is equipped with plasticity of intrinsic excitability to embed recent findings about V1 operation. The RVSM, which embeds 81 groups of MNSD arranged in 4 oriented columns, is tested using sets of rotated Gabor patches as input. Finally, synthetic visual evoked activity generated by the RVSM is compared with real neurophysiological signal from V1 area: (1) postsynaptic activity of human subjects obtained by magnetoencephalography and (2) spiking activity of macaques obtained by multi-tetrode arrays. The system is implemented using the NEST simulator. The results attest to a good level of resemblance between the model response and real neurophysiological recordings. As the RVSM is available online, and the model parameters can be customized by the user, we propose it as a tool to elucidate the computational mechanisms underlying orientation selectivity. View Full-Text
Keywords: intrinsic excitability; multi-neural spike detector (MNSD); orientation selectivity; spiking neural network simulation; delay-learning intrinsic excitability; multi-neural spike detector (MNSD); orientation selectivity; spiking neural network simulation; delay-learning
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MDPI and ACS Style

Santos-Mayo, A.; Moratti, S.; de Echegaray, J.; Susi, G. A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity. Biology 2021, 10, 801. https://doi.org/10.3390/biology10080801

AMA Style

Santos-Mayo A, Moratti S, de Echegaray J, Susi G. A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity. Biology. 2021; 10(8):801. https://doi.org/10.3390/biology10080801

Chicago/Turabian Style

Santos-Mayo, Alejandro, Stephan Moratti, Javier de Echegaray, and Gianluca Susi. 2021. "A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity" Biology 10, no. 8: 801. https://doi.org/10.3390/biology10080801

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