95 research outputs found
The Motor System at the heart of Decision-Making and Action Execution
In this Thesis, I synthesize 10 years of work on the role of the motor system
in sensorimotor decision-making. First, a large part of the work we initially
performed questioned the functional role of the motor system in the integration
of so-called decision variables such as the reward associated with different
actions, the sensory evidence in favor of each action or the level of urgency
in a given context. To this end, although the exact methodology may have
varied, the approach exploited has been to study either the impact of a
perturbation of the primary motor cortex (M1) on the integration of such
decision variables in decision behavior, or the influence of these variables on
changes in M1 activity during the decision. More recently (2020 - present), we
have been investigating the neural origin of some of the changes in M1 activity
observed during decision-making. To answer this question, a
"perturbation-and-measurement" approach is exploited: the activity of a
structure at a distance from M1 is perturbed, and the impact on the changes in
M1 activity during decision-making is measured. The thesis ends up with a
personal reflection on this paradigmatic evolution and discusses some key
questions to be addressed in our field of research.Comment: This is an Habilitation Thesis, written in Frenc
Methods of pattern classification for the design of a NIRS-based brain computer interface.
Brain-Computer Interface (BCI) is a communication system that offers the
possibility to act upon the surrounding environment without using our nervous systems
efferent pathways. One of the most important parts of a BCI is the pattern classification system
which allows to translate mental activities into commands for an external device. This work
aims at providing new pattern classification methods for the development of a Brain Computer
Interface based on Near Infrared Spectroscopy. To do so, a thorough study of machine learning
techniques used for developing BCIs has been conducted
Methods of pattern classification for the design of a NIRS-based brain computer interface.
Brain-Computer Interface (BCI) is a communication system that offers the
possibility to act upon the surrounding environment without using our nervous systems
efferent pathways. One of the most important parts of a BCI is the pattern classification system
which allows to translate mental activities into commands for an external device. This work
aims at providing new pattern classification methods for the development of a Brain Computer
Interface based on Near Infrared Spectroscopy. To do so, a thorough study of machine learning
techniques used for developing BCIs has been conducted
Il processo per la canonizzazione di San Nicola da Tolentino
Focused attention represents a high-level cognitive function enabling humans to selectively
facilitate specific actions and perceptions. In a world full of choices of action, and of perceptual
possibilities, focused attention appears to be a vital component of human cognition. One
observation however, is worth making: human-beings are unable to maintain stable states of focused
attention indefinitely. This inability manifests during sustained attention tasks with the progressive
occurrence of sensory-motor deficiencies with time-on-task. The phenomenon - called attention
decrement - is characterized by increases in motor impulsivity and in response times to imperative
events, and by a reduction in perceptual sensitivity. So far, the neural underpinnings of attention
decrement have not been fully elucidated and this lack of knowledge is clearly palpable within two
disciplinary fields: Cognitive Neuroscience and Cognitive Engineering. In Cognitive Neuroscience,
the associated question is why are human-beings unable to maintain an optimal sensory-motor
performance during sustained attention tasks? In Cognitive Engineering, the lack of a complete
scientific understanding of attentional issues impacts the development of efficient passive Brain-
Computer interfaces (BCI), capable of detecting the occurrence of potentially dangerous attention
decrements during the performance of everyday activities. Both issues have been addressed in this
thesis.
In terms of Cognitive Neuroscience, I demonstrate that sustaining focused attention on a visual
stimulation rapidly leads to an inhibition of the visual cortices. This sensory inhibition can be causally
related to the lack of changes in perceptual stimulation typically characterizing sustained attention
tasks. While the mechanism may be beneficial during visual search tasks as it helps humans avoid
processing the same stimulus, the same object, the same location several times, it can lead to the
occurrence of sensory deficiencies when sustained attention is required. As such, the sensory
inhibition provides a compelling explanation as to the decrease in perceptual sensitivity and to the
increase in reaction time that typify attention decrement. I show in a second study that attention
decrement is associated with an increase in the activity of motor- and attention-related neural
structures (i.e., cortico-spinal tract, primary motor, prefrontal and right parietal cortices). This
excessive engagement reflects a compensatory process occurring in response to the sensory
disengagement already highlighted and to the related degradation of the quality of perceptual
representations. It is notable that the excessive engagement of the motor neural structures with timeon-
task provides a potential explanation for the increase in motor impulsivity typifying attention
decrement.
In terms of application of these new findings, I investigated the potential of exploiting these
neural correlates of attention decrement to discriminate between two different attentional states (i.e.,
with or without attention decrement) through a passive BCI system. To do so, we applied supervised
classification analyses on near-infrared spectroscopy signals reflecting the hemodynamic activity of
prefrontal and parietal cortices as recorded during a sustained attention task. We achieved relatively
promising classification performance results which bode well for the future development of passive
BCI. When considered together, the results described in this thesis contribute towards a better
understanding of the neural correlates of attention decrement and demonstrate how this novel
knowledge can be exploited for the future development of systems which may enable a reduction in
accidents and human error-driven incidents in real world environments
Global and Specific Motor Inhibitory Mechanisms during Action Preparation
Global and Specific Motor Inhibitory Mechanisms during Action Preparatio
Tuning the corticospinal system - How distributed brain circuits shape our actions
Interactive behaviors rely on the operation of several processes allowing the control of actions, including their selection, withholding and abortion. The corticospinal tract provides a unique route through which brain circuits can exert such control over bodily motor acts. In humans, the activity of the corticospinal tract can be probed through the quantification of motor-evoked potentials, which can be elicited in targeted effectors by applying single-pulse transcranial magnetic stimulation (TMS) over the contralateral primary motor cortex. Using this approach, a compendium of studies has shown that the corticospinal tract exhibits dynamic increases and decreases in excitability during action selection, withholding and stopping, reflecting the implementation of the underlying control processes at the motor level. In this review, we highlight neural data from TMS studies revealing the causal role played by multiple intra-cortical, trans-cortical and subcortico-cortical circuits in these changes in corticospinal excitability. An emerging picture is that these distributed circuits cooperate through a parallel brain architecture to tune corticospinal excitability in a continuous and dynamic way, helping to determine what, when and whether actions must be executed, depending on the state of the external world
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