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Microstimulation in a spiking neural network model of the midbrain superior colliculus

The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus by recruiting a population of cells in its topographically organized motor map. Supra-threshold electrical microstimulation in the SC reveals that the site of stimulation produces a normometric saccad...

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Autores principales: Kasap, Bahadir, van Opstal, A. John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481873/
https://www.ncbi.nlm.nih.gov/pubmed/30978180
http://dx.doi.org/10.1371/journal.pcbi.1006522
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author Kasap, Bahadir
van Opstal, A. John
author_facet Kasap, Bahadir
van Opstal, A. John
author_sort Kasap, Bahadir
collection PubMed
description The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus by recruiting a population of cells in its topographically organized motor map. Supra-threshold electrical microstimulation in the SC reveals that the site of stimulation produces a normometric saccade vector with little effect of the stimulation parameters. Moreover, electrically evoked saccades (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-saccades). These findings support models in which the saccade vector is determined by a center-of-gravity computation of activated neurons, while its trajectory and kinematics arise from downstream feedback circuits in the brainstem. Recent single-unit recordings, however, have indicated that the SC population also specifies instantaneous kinematics. These results support an alternative model, in which the desired saccade trajectory, including its kinematics, follows from instantaneous summation of movement effects of all SC spike trains. But how to reconcile this model with microstimulation results? Although it is thought that microstimulation activates a large population of SC neurons, the mechanism through which it arises is unknown. We developed a spiking neural network model of the SC, in which microstimulation directly activates a relatively small set of neurons around the electrode tip, which subsequently sets up a large population response through lateral synaptic interactions. We show that through this mechanism the population drives an E-saccade with near-normal kinematics that are largely independent of the stimulation parameters. Only at very low stimulus intensities the network recruits a population with low firing rates, resulting in abnormally slow saccades.
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spelling pubmed-64818732019-05-07 Microstimulation in a spiking neural network model of the midbrain superior colliculus Kasap, Bahadir van Opstal, A. John PLoS Comput Biol Research Article The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus by recruiting a population of cells in its topographically organized motor map. Supra-threshold electrical microstimulation in the SC reveals that the site of stimulation produces a normometric saccade vector with little effect of the stimulation parameters. Moreover, electrically evoked saccades (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-saccades). These findings support models in which the saccade vector is determined by a center-of-gravity computation of activated neurons, while its trajectory and kinematics arise from downstream feedback circuits in the brainstem. Recent single-unit recordings, however, have indicated that the SC population also specifies instantaneous kinematics. These results support an alternative model, in which the desired saccade trajectory, including its kinematics, follows from instantaneous summation of movement effects of all SC spike trains. But how to reconcile this model with microstimulation results? Although it is thought that microstimulation activates a large population of SC neurons, the mechanism through which it arises is unknown. We developed a spiking neural network model of the SC, in which microstimulation directly activates a relatively small set of neurons around the electrode tip, which subsequently sets up a large population response through lateral synaptic interactions. We show that through this mechanism the population drives an E-saccade with near-normal kinematics that are largely independent of the stimulation parameters. Only at very low stimulus intensities the network recruits a population with low firing rates, resulting in abnormally slow saccades. Public Library of Science 2019-04-12 /pmc/articles/PMC6481873/ /pubmed/30978180 http://dx.doi.org/10.1371/journal.pcbi.1006522 Text en © 2019 Kasap, van Opstal http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kasap, Bahadir
van Opstal, A. John
Microstimulation in a spiking neural network model of the midbrain superior colliculus
title Microstimulation in a spiking neural network model of the midbrain superior colliculus
title_full Microstimulation in a spiking neural network model of the midbrain superior colliculus
title_fullStr Microstimulation in a spiking neural network model of the midbrain superior colliculus
title_full_unstemmed Microstimulation in a spiking neural network model of the midbrain superior colliculus
title_short Microstimulation in a spiking neural network model of the midbrain superior colliculus
title_sort microstimulation in a spiking neural network model of the midbrain superior colliculus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481873/
https://www.ncbi.nlm.nih.gov/pubmed/30978180
http://dx.doi.org/10.1371/journal.pcbi.1006522
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