Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and speed of saccadic eye movements.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
10 2022
Historique:
received: 21 03 2022
accepted: 13 09 2022
revised: 14 10 2022
pubmed: 5 10 2022
medline: 19 10 2022
entrez: 4 10 2022
Statut: epublish

Résumé

Saccadic eye-movements play a crucial role in visuo-motor control by allowing rapid foveation onto new targets. However, the neural processes governing saccades adaptation are not fully understood. Saccades, due to the short-time of execution (20-100 ms) and the absence of sensory information for online feedback control, must be controlled in a ballistic manner. Incomplete measurements of the movement trajectory, such as the visual endpoint error, are supposedly used to form internal predictions about the movement kinematics resulting in predictive control. In order to characterize the synaptic and neural circuit mechanisms underlying predictive saccadic control, we have reconstructed the saccadic system in a digital controller embedding a spiking neural network of the cerebellum with spike timing-dependent plasticity (STDP) rules driving parallel fiber-Purkinje cell long-term potentiation and depression (LTP and LTD). This model implements a control policy based on a dual plasticity mechanism, resulting in the identification of the roles of LTP and LTD in regulating the overall quality of saccade kinematics: it turns out that LTD increases the accuracy by decreasing visual error and LTP increases the peak speed. The control policy also required cerebellar PCs to be divided into two subpopulations, characterized by burst or pause responses. To our knowledge, this is the first model that explains in mechanistic terms the visual error and peak speed regulation of ballistic eye movements in forward mode exploiting spike-timing to regulate firing in different populations of the neuronal network. This elementary model of saccades could be extended and applied to other more complex cases in which single jerks are concatenated to compose articulated and coordinated movements.

Identifiants

pubmed: 36194625
doi: 10.1371/journal.pcbi.1010564
pii: PCOMPBIOL-D-22-00441
pmc: PMC9565489
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1010564

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Lorenzo Fruzzetti (L)

The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera (Pisa), Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.

Hari Teja Kalidindi (HT)

Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Universite Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium.
Institute of Neuroscience, Universite Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium.

Alberto Antonietti (A)

Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.

Cristiano Alessandro (C)

Department of Brain and Behavioral Sciences, University of Pavia, Italy.
School of Medicine and Surgery/Sport and Exercise Medicine, University of Milano-Bicocca, Milan, Italy.

Alice Geminiani (A)

Department of Brain and Behavioral Sciences, University of Pavia, Italy.

Claudia Casellato (C)

Department of Brain and Behavioral Sciences, University of Pavia, Italy.

Egidio Falotico (E)

The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera (Pisa), Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.

Egidio D'Angelo (E)

Department of Brain and Behavioral Sciences, University of Pavia, Italy.
IRCCS Mondino Foundation, Pavia, Italy.

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