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An EEG-based brain-computer interface for gait training

Related publications (31)

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

This thesis presents an extensive exploration of neuroelectronic interfaces, focusing on microfabrication, in silico modeling, and their applications in designing and fabricating devices for neural interfacing. The research encompasses both peripheral nerv ...

EPFL2024

Unveiling the complexity of learning and decision-making

Wei-Hsiang Lin

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

EPFL2024

Investigating neural resource allocation in the sensorimotor control of extra limbs

Giulia Dominijanni

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

EPFL2024

Thalamic 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 ( ...

Wiley2024

Decoding 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 Publishing2024

Non-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 Portfolio2024

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Maliheh Miri

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organi-zation of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel me ...

Elsevier Sci Ltd2023

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

Carmina Andrea Galvez Solano

Spinal Cord Injury (SCI) affects almost 500,000 people every year, causing complete paralysis of both legs in severe cases, with no current treatment perspective. However, new neuroengineering technologies, such as the Brain Spine Interface (BSI), have eme ...

EPFL2023

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Silvestro Micera, Michael Lassi

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

IOP Publishing Ltd2023

An EEG-based brain-computer interface for gait training

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Unveiling the complexity of learning and decision-making

Investigating neural resource allocation in the sensorimotor control of extra limbs

Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Graph Chatbot

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Unveiling the complexity of learning and decision-making

Investigating neural resource allocation in the sensorimotor control of extra limbs

Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?