Critical revision of the neurophysiology of tracking eye movements - Archive ouverte HAL
Poster De Conférence Année : 2018

Critical revision of the neurophysiology of tracking eye movements

Résumé

The abstract is located at the page 44 of the program booklet (a search with the word "Goffart" does not function) : During the last decades, multiple studies supposed that kinematic parameters of tracking eye movements were encoded in the neuronal processes underlying their generation. From time series of measured angular deviations, magnitudes such as movement amplitude, duration and their ratio (speed) were calculated and models proposed the existence, in the brain, of processes which would reduce a difference between gaze and target directions (for guiding the saccade) or between the eye and target speeds (for accelerating the slow eye movement), and maintain the eye speed despite target stabilization within the central visual field. This parallelism made between the relative motions of rigid bodies (eyeball and target) and hypothetical processes led neurophysiologists to search for correlations between the neurons' activity and kinematic parameters (position, speed and acceleration) and to propose that their firing rate could be predicted by their linear combination. Such a "neuronalization" of behavioral parameters is questionable for a safe advancement of the neurophysiology of visually-guided movements (Goffart, Bourrelly and Quinton 2018). Instead of plunging within the brain medium, notions which were actually designed to quantify the motion of rigid bodies in the physical world, we propose to use principles that are intrinsic to the brain functioning (parallel flows of activity constrained by the connectivity, population coding, multiplicity of transmission delays, synchrony of neuronal discharges, heterogeneity of neurons, etc.).
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Dates et versions

hal-03654901 , version 1 (29-04-2022)

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  • HAL Id : hal-03654901 , version 1

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Laurent Goffart. Critical revision of the neurophysiology of tracking eye movements. GDR conference NeuralNet 2018, Dec 2018, Paris, France. ⟨hal-03654901⟩
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