P
Peter Ford Dominey
Researcher at French Institute of Health and Medical Research
Publications - 182
Citations - 5398
Peter Ford Dominey is an academic researcher from French Institute of Health and Medical Research. The author has contributed to research in topics: Sentence & Human–robot interaction. The author has an hindex of 40, co-authored 174 publications receiving 4976 citations. Previous affiliations of Peter Ford Dominey include Centre national de la recherche scientifique & University of Burgundy.
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Motor imagery of a lateralized sequential task is asymmetrically slowed in hemi-Parkinson's patients
TL;DR: Data support two related hypotheses: (a) Motor sequence imagery and execution share common neural structures and (b) the frontostriatal system is among these shared structures.
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A model of corticostriatal plasticity for learning oculomotor associations and sequences
TL;DR: Two models that learn context-dependent oculomotor behavior in conditional visual discrimination and sequence reproduction tasks are presented, based on the following three principles: visual input and efferent copies of motor output produce patterns of activity in cortex.
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Neurological basis of language and sequential cognition: evidence from simulation, aphasia, and ERP studies.
TL;DR: The study of sequential cognition will provide a new paradigm for the investigation of the neurophysiological bases of language, as it is predicted that impaired syntactic processing will be associated with impairments in corresponding non-linguistic cognitive sequencing tasks.
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A Cortico-Subcortical Model for Generation of Spatially Accurate Sequential Saccades
TL;DR: A major thesis of this model is that a topography of saccade direction and amplitude is preserved through multiple projections between brain regions until they are finally transformed into a temporal pattern of activity that drives the eyes to the target.
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Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex.
TL;DR: This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task.