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Jonathan D. Victor

Researcher at Cornell University

Publications -  319
Citations -  15134

Jonathan D. Victor is an academic researcher from Cornell University. The author has contributed to research in topics: Receptive field & Retinal ganglion. The author has an hindex of 63, co-authored 303 publications receiving 14025 citations. Previous affiliations of Jonathan D. Victor include NewYork–Presbyterian Hospital & Rockefeller University.

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Behavioural improvements with thalamic stimulation after severe traumatic brain injury

TL;DR: It is shown that bilateral deep brain electrical stimulation of the central thalamus modulates behavioural responsiveness in a patient who remained in MCS for 6 yr followingtraumatic brain injury before the intervention, providing evidence that DBS can promote significant late functional recovery from severe traumatic brain injury.
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Nature and precision of temporal coding in visual cortex: a metric-space analysis.

TL;DR: To examine the nature and precision of temporal coding, individual responses elicited by each set of stimuli were compared in terms of two families of metrics, which provided a possible mechanism for the simultaneous representation of multiple stimulus attributes in one spike train.
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The effect of contrast on the transfer properties of cat retinal ganglion cells.

TL;DR: Direct proof was found that modulation at one frequency modifies the response at other frequencies, and this implied that stimulus energy at one temporal frequency could affect the response amplitude and phase shift at another temporal frequency.
Posted Content

Metric-space analysis of spike trains: theory, algorithms, and application

TL;DR: The mathematical basis of a new approach to the analysis of temporal coding is the construction of several families of novel distances (metrics) between neuronal impulse trains that formalize physiologically based hypotheses for those aspects of the firing pattern that might be stimulus dependent and make essential use of the point-process nature of neural discharges.
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Metric-space analysis of spike trains: theory, algorithms and application

TL;DR: In this article, the authors proposed a new approach to the analysis of temporal coding, which does not attempt to embed impulse trains in a vector space, and does not assume a Euclidean notion of distance.