Publications related to Early left anterior negativity

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

Movement-Related Cortical Potentials in Embodied Virtual Mirror Visual Feedback

Gangadhar Garipelli, Tamara Rossy

Background: Mirror therapy is thought to drive interhemispheric communication, resulting in a balanced activation. We hypothesized that embodied virtual mirror visual feedback (VR-MVF) presented on a computer screen may produce a similar activation. In thi ...

FRONTIERS MEDIA SA2021

Sparse non-negative super-resolution - simplified and stabilised

Armin Eftekhari, Hemant Tyagi

We consider the problem of non-negative super-resolution, which concerns reconstructing a non-negative signal x = Sigma(k )(i=1)a(i)delta(ti) from m samples of its convolution with a window function phi(s - t), of the form y(s(j)) = Sigma(k)(i=1) a(i) phi( ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

Neural dynamics of the competition between grouping organizations

Michael Herzog, Ophélie Gladys Favrod, Einat Rashal

Neural dynamics of the competition between grouping organizations have been studied to a limited extent. The paradigms used so far confounded grouping operations with task demands, using explicit reports of the predominantly perceived organization and bias ...

SAGE PUBLICATIONS LTD2019

Time course of prediction errors in sequential decision making

Michael Herzog, He Xu

In reinforcement learning, an agent makes sequential decisions to maximize reward. During learning, the actual and expected outcome are compared to tell whether a decision was good or bad. The difference between the actual outcome and expected outcome is t ...

2018

Neural Correlates of Sequential Decision Making

Michael Herzog, He Xu

In chess, a series of moves is made until a delayed sparse feedback (win, loss) is issued, which makes it impossible to evaluate the value of a single move. There are powerful reinforcement learning (RL) algorithms, which can cope with these sequential dec ...

2017

Neural Correlates of Sequential Decision Making

Michael Herzog, He Xu

In chess, a series of moves is made until a delayed sparse feedback (win, loss) is issued, which makes it impossible to evaluate the value of a single move. There are powerful reinforcement learning (RL) algorithms, which can cope with these sequential dec ...

2017

Spatiotemporal Dynamics of the Cortical Responses Induced by a Prolonged Tactile Stimulation of the Human Fingertips

Silvestro Micera, Fiorenzo Artoni

The sense of touch is fundamental for daily behavior. The aim of this work is to understand the neural network responsible for touch processing during a prolonged tactile stimulation, delivered by means of a mechatronic platform by passively sliding a ridg ...

2017

Hyperdimensional computing for blind and one-shot classification of EEG error-related potentials

José del Rocio Millán Ruiz

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as “hypervectors,” is a brain-inspired alternative to computing with numbers. HD computing ...

Springer Verlag2020

Inverse solutions for brain-computer interfaces: Effects of regularisation on localisation and classification

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Mohit Kumar Goel

Estimation of intracranial sources, using inverse solutions methods, has been proposed as a mean to improve performance in non-invasive brain-computer interfaces. These methods estimate the activity of a large number of neural sources from a smaller number ...

2017

Hyperdimensional computing for noninvasive brain-computer interfaces: Blind and one-shot classification of EEG error-related potentials

José del Rocio Millán Ruiz

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as "hypervectors," is a brain-inspired alternative to computing with numbers. HD computing ...

2017

Electroencephalogram (EEG) Frontal Asymmetry and Error-Related Signals Are Potential Markers of Internalizing and Externalizing Behaviors in Children: A Meta-Analysis

Michael Herzog, Ophélie Gladys Favrod

Objectives: The frontal hemispheric asymmetry and error-related components, as measured by EEG, are often considered to be biological correlates or “indicators of risk” for psychopathology. Here, we performed a meta-analysis to define specific patterns of ...

2017

BCI based on Neural Correlates of Anticipatory Behavior during Driving

Zahra Khaliliardali

Anticipation of events such as, changes in traffic light signals and preparing to brake or accelerate are critical behaviors during driving. Smart vehicles, equipped with on-board Brain-Computer Interface (BCI), could decode the driver's intention to perfo ...

EPFL2016

Simultaneous EEG-fMRI at ultra-high field for the study of human brain function

João Pedro Forjaco Jorge

Scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have highly complementary domains, and their combination has been actively sought within neuroscience research. The important gains in fMRI sensitivity achieved with higher ...

EPFL2016

Decoding Fast-Paced Error-Related Potentials in Monitoring Protocols

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil, Quentin Olivier Pierre Wannebroucq

Error-related EEG potentials (ErrP) can be used for brain-machine interfacing (BMI). Decoding of these signals, indicating subject's perception of erroneous system decisions or actions can be used to correct these actions or to improve the overall interfac ...

2015

Asynchronous Decoding of Error Potentials During the Monitoring of a Reaching Task

Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil

Brain-machine interfaces (BMIs) have demonstrated how they can be used for reaching tasks with both invasive and non-invasive signal recording methods. Despite the constant improvements in this field, there still exist diverse factors to overcome before ac ...

2015

Simultaneous EEG–fMRI at ultra-high field: Artifact prevention and safety assessment

Rolf Gruetter, Wietske Van der Zwaag, João Pedro Forjaco Jorge, Özlem Ipek, Patricia Figueiredo

The simultaneous recording of scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide unique insights into the dynamics of human brain function, and the increased functional sensitivity offered by ultra-high field fM ...

Elsevier2015

The electrophysiological effects of the serotonin 1A receptor agonist buspirone in emotional face processing

Fosco Bernasconi

Emotional face processing is critically modulated by the serotonergic system, and serotonin (5-HT) receptor agonists impair emotional face processing. However, the specific contribution of the 5-HT1A receptor remains poorly understood. Here we investigated ...

Elsevier Science Bv2015

Different colors of light lead to different adaptation and activation as determined by high-density EEG

Jean-Louis Scartezzini, Michael Herzog, Mirjam Münch, Gijs Plomp, Yvonne Evelina Thunell

Light adaptation is crucial for coping with the varying levels of ambient light. Using high-density electroencephalography (EEG), we investigated how adaptation to light of different colors affects brain responsiveness. In a within-subject design, sixteen ...

Elsevier2014

Latency Correction of Event-Related Potentials Between Different Experimental Protocols

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil

Objective: A fundamental issue in EEG event-related potentials (ERPs) studies is the amount of data required to have an accurate ERP model. This also impacts the time required to train a classifier for a brain-computer interface (BCI). This issue is mainly ...

Institute of Physics2014