scispace - formally typeset
J

Jacques Pernier

Researcher at French Institute of Health and Medical Research

Publications -  89
Citations -  11876

Jacques Pernier is an academic researcher from French Institute of Health and Medical Research. The author has contributed to research in topics: Auditory cortex & Stimulus (physiology). The author has an hindex of 32, co-authored 89 publications receiving 11206 citations. Previous affiliations of Jacques Pernier include Centre national de la recherche scientifique.

Papers
More filters
Journal ArticleDOI

The combined monitoring of brain stem auditory evoked potentials and intracranial pressure in coma. A study of 57 patients.

TL;DR: Continuous monitoring of brainstem auditory evoked potentials provided a useful physiological counterpart to physical parameters such as ICP and Serial recording of cortical EPs should be added to BAEP monitoring to permit the early detection of rostrocaudal deterioration.
Journal ArticleDOI

Computer-assisted placement of electrodes on the human head.

TL;DR: Improved reproducibility of the assisted procedure of the described system is 3 times better than in the manual procedure.
Journal ArticleDOI

Task-dependent activation latency in human visual extrastriate cortex.

TL;DR: The results indicate that dynamic stimuli may activate (at least partly) different pathways and processes in extrastriate cortex according to the nature of the task required on these stimuli.
Journal ArticleDOI

Selective auditory attention effects in tonotopically organized cortical areas: A topographic ERP study

TL;DR: The hypothesis that auditory attention can exert a selective control over the sensory processing of acoustic stimuli in tonotopic auditory cortex at an early stage of sensory processing is supported, even in low attentional load conditions.
Journal ArticleDOI

Fast realistic modeling in bioelectromagnetism using lead-field interpolation.

TL;DR: Cropping grids by removing shallow points lead to a much better estimation of the dipole orientation in EEG than when solving the forward problem classically, providing an efficient alternative to locally refined models.