Gaëtan Sanchez

Gaëtan Sanchez
Lyon Neuroscience Research Center · DYCOG Team

PhD

About

16
Publications
5,976
Reads
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351
Citations
Additional affiliations
January 2018 - present
Lyon Neuroscience Research Center
Position
  • PostDoc Position
Description
  • Measuring neurophysiological signals in military machine driving context for the assessment of mental workload in order to infer optimal design/environment adaptation. Real time mental workload and stress monitoring using EEG.
January 2016 - present
University of Salzburg
Position
  • Lecturer
Description
  • - Application of Decoding approaches to M/EEG Data - The Bayesian Brain: including a guide to DCM for MEG - MEG : Acquisition, Analysis, Visualization - From connectivity to Graphs: a Hands-On introduction
November 2015 - December 2017
University of Salzburg
Position
  • PostDoc Position
Description
  • Investigate macroscopic neural processes supporting conscious perception: a realtime and decoding approach
Education
January 2011 - June 2014
Claude Bernard University Lyon 1
Field of study
  • Neuroscience
September 2008 - June 2010
Claude Bernard University Lyon 1
Field of study
  • Physiology & Neuroscience
September 2005 - June 2008
Claude Bernard University Lyon 1
Field of study
  • Biology/Physiology

Publications

Publications (16)
Article
Full-text available
An increasing number of studies highlight common brain regions and processes in mediating conscious sensory experience. While most studies have been performed in the visual modality, it is implicitly assumed that similar processes are involved in other sensory modalities. However, the existence of supramodal neural processes related to conscious pe...
Article
Full-text available
Prior experience enables the formation of expectations of upcoming sensory events. However, in the auditory modality, it is not known whether prediction-related neural signals carry feature-specific information. Here, using magnetoencephalography (MEG), we examined whether predictions of future auditory stimuli carry tonotopic specific information....
Article
Full-text available
Muscular activity recording is of high basic science and clinical relevance and is typically achieved using electromyography (EMG). While providing detailed information about the state of a specific muscle, this technique has limitations such as the need for a priori assumptions about electrode placement and difficulty with recording muscular activ...
Article
Brain-machine interfaces (BMIs) use brain signals to control closed-loop systems in real-time. This comes with substantial challenges, such as having to remove artifacts in order to extract reliable features, especially when using electroencephalography (EEG). Some approaches have been described in the literature to address online artifact correcti...
Preprint
Full-text available
Muscular activity recording is of high basic science and clinical relevance and is typically achieved using electromyography (EMG). While providing detailed information about the state of a specific muscle, this technique has limitations such as the need for a-priori assumptions about electrode placement and difficulty with recording muscular activ...
Preprint
Full-text available
Prior experience shapes sensory perception by enabling the formation of expectations with regards to the occurrence of upcoming sensory events. Especially in the visual modality, an increasing number of studies show that prediction­related neural signals carry feature­specific information about the stimulus. This is less established in the auditory...
Preprint
An increasing number of studies highlight the role of fronto-parietal brain structures in mediating conscious sensory experience. While most studies have been performed in the visual modality, it is implicitly assumed that similar processes are involved in other sensory modalities. However, the existence of supramodal neural processes related to co...
Article
Full-text available
The fairly young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two development...
Poster
Full-text available
Introduction Perceptual decisions are known to reflect sensory evidence, contextual information and inner priors (1). Bayesian modelling provides a powerful framework to formulate and compare alternative computational hypotheses about how behavior emerges from the combination of those different influences. In Autism Spectrum Disorders (ASD), it has...
Poster
Full-text available
Background According to Bayesian theories, our perception is influenced by priors we have on the incoming sensation. Priors correspond to our internal references, which are built up through perceptual learning. It was suggested that peculiarities in the functioning of the Bayesian brain in autism spectrum disorder (ASD) could explain many of the au...
Poster
Full-text available
Background Recently, some Bayesian theories were suggested to explain how our perception of the world emerges and how it could be altered in Autism Spectrum Disorders (ASD)1,2. In these theories, the representation of a stimulus would be influenced by both the precision of the encoding of the stimulus and the priors we have on incoming sensations....
Article
Full-text available
Congenital amusia is a neuro-developmental disorder that primarily manifests as a difficulty in the perception and memory of pitch-based materials, including music. Recent findings have shown that the amusic brain exhibits altered functioning of a fronto-temporal network during pitch perception and short-term memory. Within this network, during the...
Article
Full-text available
Today, psychological as well as physiological models of perceptual learning and decision-making processes have recently become more biologically plausible, leading to more realistic (and more complex) generative models of psychophysiological observations. In parallel, the young but exponentially growing field of Brain-Computer Interfaces (BCI) prov...
Article
Full-text available
Brain-computer interfaces (BCIs) mostly rely on electrophysiological brain signals. Methodological and technical progress has largely solved the challenge of processing these signals online. The main issue that remains, however, is the identification of a reliable mapping between electrophysiological measures and relevant states of mind. This is wh...
Article
Full-text available
Congenital amusia is a lifelong disorder of music perception and production. The present study investigated the cerebral bases of impaired pitch perception and memory in congenital amusia using behavioural measures, magnetoencephalography and voxel-based morphometry. Congenital amusics and matched control subjects performed two melodic tasks (a mel...
Article
Full-text available
We present a brain-computer interface (BCI) version of the famous “Connect Four”. Target selection is based on brain event-related responses measured with nine EEG sensors. Two players compete against each other using their brain activity only. Importantly, we turned the general difficulty of producing a reliable BCI command into an advantage, by e...

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