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Analysis of Anticipation Related Potentials for Brain Computer Interaction
Publications associées (32)
Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse
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Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...
Ieee-Inst Electrical Electronics Engineers Inc2024Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation
Silvestro Micera, Simone Romeni, Laura Toni, Fiorenzo Artoni
Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...
Aip Publishing2024Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction.
Olaf Blanke, José del Rocio Millán Ruiz, Ronan Boulic, Bruno Herbelin, Ricardo Andres Chavarriaga Lozano, Fumiaki Iwane
Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...
2024Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills
Friedhelm Christoph Hummel, Takuya Morishita, Pierre Theopistos Vassiliadis, Elena Beanato, Esra Neufeld, Fabienne Windel, Maximilian Jonas Wessel, Traian Popa, Julie Duqué
Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...
Nature Portfolio2024Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants
Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...
EPFL2024Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)
Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Farnaz Delavari, Nada Kojovic
The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns ( ...
Wiley2024Subcortical correlates of consciousness with human single neuron recordings
Olaf Blanke, Fosco Bernasconi, Nathan Quentin Faivre, Michael Eric Anthony Pereira
Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...
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Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi
Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...
EPFL Infoscience2024Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization
Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...
EPFL202433.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes
Mahsa Shoaran, Uisub Shin, Gregor Rainer, Mohammad Ali Shaeri, Amitabh Yadav
Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...
IEEE2024