Publications associées à BrainGate

Customizing 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, Thibault Serge Mario Porssut

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 ...

2024

Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

Claudia Bigoni

"Ensure healthy lives and promote well-being for all at all ages" is the third sustainable development goal for the United Nations Agenda of 2030. This doctoral thesis fully embodied this objective by targeting stroke, a leading cause of death and disabili ...

EPFL2023

A digital bridge between brain and spinal cord restores walking after paralysis

Grégoire Courtine, Jocelyne Bloch

Spinal-cord injury interrupts communication between the brain and spinal cord, leading to paralysis. An implant that decodes the brain signals that control movements and drives electrical stimulation of the spinal cord re-establishes this communication, en ...

NATURE PORTFOLIO2023

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Marcello Ienca

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinica ...

ELSEVIER SCIENCE INC2023

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

Nicolas Clairis

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/d ...

Oxford Univ Press2023

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

Alessandra Griffa, Enrico Amico, Ekansh Sareen

The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques

Mahsa Shoaran, Bingzhao Zhu

Objective. Accurate decoding of individual finger movements is crucial for advanced prosthetic control. In this work, we introduce the use of Riemannian-space features and temporal dynamics of electrocorticography (ECoG) signal combined with modern machine ...

IOP Publishing Ltd2022

The present and future of neural interfaces

Marcello Ienca

The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring ...

FRONTIERS MEDIA SA2022

Sense of agency for intracortical brain-machine interfaces

Olaf Blanke, Andrea Serino, Tommaso Enrico Bertoni, Nathan Quentin Faivre, Marco Solcà, Pavo Orepic, Gaurav Sharma

Intracortical brain-machine interfaces decode motor commands from neural signals and translate them into actions, enabling movement for paralysed individuals. The subjective sense of agency associated with actions generated via intracortical brain-machine ...

NATURE PORTFOLIO2022

Decoding of error-related potentials in continuous feedback protocols for personalized human computer interaction

Fumiaki Iwane

The ability to notice erroneous behavior is crucial for effective training. Within the framework of neuroprosthetics, numerous studies in electroencephalography (EEG) confirm the existence of neural correlates when humans perceive the erroneous actions of ...

EPFL2021

Adaptive Wireless Power Transfer and Backscatter Communication for Perpetual Operation of Wireless Brain-Computer Interfaces

James Daniel Rosenthal

Brain-computer interfaces (BCIs) are neural prosthetics that enable closed-loop electrophysiology procedures. These devices are currently used in fundamental neurophysiology research, and they are moving toward clinical viability for neural rehabilitation. ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Surprise-based model estimation in reinforcement learning: algorithms and brain signatures

Vasiliki Liakoni

Learning how to act and adapting to unexpected changes are remarkable capabilities of humans and other animals. In the absence of a direct recipe to follow in life, behaviour is often guided by rewarding and by surprising events. A positive or a negative o ...

EPFL2021

Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation

Andrea Lozzi

Implanted microelectrode arrays sense local neuronal activity, signals which are used as control commands for brain computer interface (BCI) technology. Patients with tetraplegia have used BCI technology to achieve an extraordinary degree of interaction wi ...

2020

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

Silvestro Micera, Fiorenzo Artoni, Stefano Tortora

Objective.Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. ...

IOP PUBLISHING LTD2020

Towards everyday brain-computer interfacing through decoding visual cognition

Ruslan Aydarkhanov

Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...

EPFL2020

All-Printed Electrocorticography Array for In Vivo Neural Recordings

Diego Ghezzi, Eleonora Borda, Laura Ferlauto, Fabian Michael Lütolf, Nenad Marjanovic

Bioelectronic and neuroprosthetic interfaces rely on implanted microelectrode arrays (MEAs) to interact with the human body. Printing techniques, such as inkjet and screen printing, are attractive methods for the manufacturing of MEAs because they allow fl ...

2020

Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation

Nicolas Julien Roussel, Camille Marie Jeunet

Brain-Computer Interfaces (BCIs) enable users to interact with computers without any dedicated movement, bringing new hands-free interaction paradigms. In this paper we study the combination of BCI and Augmented Reality (AR). We first tested the feasibilit ...

2020

Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers

Silvestro Micera, Fiorenzo Artoni, Luca Tonin, Stefano Tortora

Despite the advances in the field of brain computer interfaces (BCI), the use of the sole electroencephalography (EEG) signal to control walking rehabilitation devices is currently not viable in clinical settings, due to its unreliability. Hybrid interface ...

2020

A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information

Jean-Philippe Thiran, Alessandro Daducci, Muhamed Barakovic, Maxime Descoteaux

Diffusion magnetic resonance imaging is a noninvasive imaging modality that has been extensively used in the literature to study the neuronal architecture of the brain in a wide range of neurological conditions using tractography. However, recent studies h ...

AMER ASSOC ADVANCEMENT SCIENCE2020

The Human-Computer Connection An Overview Of Brain-Computer Interfaces

José del Rocio Millán Ruiz

This article introduces the field of brain-computer interfaces (BCI), which allows the control of devices without the generation of any active motor output but directly from the decoding of the user's brain signals. Here we review the current state of the ...

2019