Publication

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future

Publications associées (32)

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Aude Billard, José del Rocio Millán Ruiz, Fumiaki Iwane

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

Nature Portfolio2023

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

Neuroengineering of hallucinations through fMRI neurofeedback: Understanding and modulating neural dynamics for the control of hallucinations in health and disease

Herberto Dhanis Pedro De Barros Camacho

Recent years have seen considerable progress in understanding brain function, and in modulating it through real-time fMRI neurofeedback (NF). Inspired by these advances, paired with the unique possibility of inducing the clinically relevant Presence Halluc ...

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

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Kseniia Korchagina

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Portfolio2023

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

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

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

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

A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC

Mahsa Shoaran, Cong Ding, Uisub Shin

Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter therefore presents a low-power SoC with both neural connectivity extraction ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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, Marco Solcà, Nathan Quentin Faivre, Pavo Orepic, Tommaso Enrico Bertoni, 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