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Silvia Marchesotti

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Related publications (7)

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Sensorimotor Induction of Auditory Misattribution in Early Psychosis

Olaf Blanke, Andrea Serino, Alessandra Griffa, Fosco Bernasconi, Patric Hagmann, Kim Do, Roy Salomon, Giulio Rognini, Silvia Marchesotti, Pierre Progin

Dysfunction of sensorimotor predictive processing is thought to underlie abnormalities in self-monitoring producing passivity symptoms in psychosis. Experimentally induced sensorimotor conflict can produce a failure in bodily self-monitoring (presence hall ...

2020

Imagined paralysis alters somatosensory evoked-potentials

Olaf Blanke, Fred Mast, Christophe Lopez, Estelle Palluel, Silvia Marchesotti

Recent studies employing body illusions have shown that multisensory conflict can alter body representations and modulate low-level sensory processing. One defining feature of these body illusions is that they are sensory driven and thus passive on behalf ...

2020

Sensorimotor Induction of Auditory Misattribution in Psychosis is Linked to Neural Disconnectivity

Olaf Blanke, Andrea Serino, Alessandra Griffa, Patric Hagmann, Kim Do, Roy Salomon, Giulio Rognini, Silvia Marchesotti, Pierre Progin

Background: Schneiderian first rank symptoms (FRS) are characterized by a diminished demarcation of self-other boundaries, causing misattribution of self-generated thoughts and actions to external sources. We have shown that introducing sensorimotor predic ...

2018

Motor and cognitive brain circuits of brain-machine interactions

Silvia Marchesotti

Brain-machine interfaces (BMIs) allow the user to control an external device such as a robotic arm, a cursor, or an avatar in a virtual world through the real-time decoding of brain signals and without the involvement of the musculoskeletal system. Althoug ...

EPFL2016

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Despite technical advances in brain machine interfaces (BMI), for as-yet unknown reasons the ability to control a BMI remains limited to a subset of users. We investigate whether individual differences in BMI control based on motor imagery (MI) are related ...

2016

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Humans can learn under a wide variety of feedback conditions. Reinforcement learning (RL), where a series of rewarded decisions must be made, is a particularly important type of learning. Computational and behavioral studies of RL have focused mainly on Ma ...

Public Library of Science2015

Both a large lesion volume and abnormalities in diffusion tensor imaging are independently associated with a poor prognosis after cerebral infarctions. Therefore, we assume that they are associated. This study assessed the associations between lesion volum ...

BioMed Central2010