Publications by Inaki Asier Iturrate Gil

Invariability of EEG error-related potentials during continuous feedback protocols elicited by erroneous actions at predicted or unpredicted states

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

Objective. When humans perceive an erroneous action, an EEG error-related potential (ErrP) is elicited as a neural response. ErrPs have been largely investigated in discrete feedback protocols, where actions are executed at discrete steps, to enable seamle ...

2021

The Confidence Database

Michael Eric Anthony Pereira, Xiao Hu, Inaki Asier Iturrate Gil, Nathan Quentin Faivre, Caroline Peters

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence stud ...

NATURE PUBLISHING GROUP2020

Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging

José del Rocio Millán Ruiz, Dimitri Nestor Alice Van De Ville, Michael Eric Anthony Pereira, Olaf Blanke, Arnaud Marc Desvachez, Stéphanie Martin, Inaki Asier Iturrate Gil, Nathan Quentin Faivre, Marco Wirthlin

The human capacity to compute the likelihood that a decision is correct—known as metacognition—has proven difficult to study in isolation as it usually cooccurs with decision making. Here, we isolated postdecisional from decisional contributions to metacog ...

2020

A Rapid Form of Offline Consolidation in Skill Learning

Inaki Asier Iturrate Gil

The brain strengthens memories through consolidation, defined as resistance to interference (stabilization) or performance improvements between the end of a practice session and the beginning of the next (offline gains) [1]. Typically, consolidation has be ...

CELL PRESS2019

Inferring subjective preferences on robot trajectories using EEG signals

Aude Billard, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Inaki Asier Iturrate Gil, Iason Batzianoulis, Fumiaki Iwane

Cognitive information has been exploited in non-invasive Brain Computer Interface (BCI) scenarios to provide autonomous external agents with additional information. In this context, Error-related potentials (ErrPs), temporal deflections in electroencephalo ...

IEEE2019

Human EEG reveals distinct neural correlates of power and precision grasping types

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Michael Eric Anthony Pereira, Robert Leeb, Huaijian Zhang, Inaki Asier Iturrate Gil, Tiffany Corbet

Hand grasping is a sophisticated motor task that has received much attention by the neuroscientific community, which demonstrated how grasping activates a network involving parietal, pre-motor and motor cortices using fMRI, ECoG, LFPs and spiking activity. ...

2018

Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

José del Rocio Millán Ruiz, Dragana Viceic, Hua Zhang, Serafeim Perdikis, Robert Leeb, Andrea Biasiucci, Inaki Asier Iturrate Gil, Thomas Schmidlin, Tiffany Corbet

Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals into intended movements of the paralyzed limb. However, the efficacy and mechanisms of BCI-based therapies remain unclear. Here we show that BCI coupled to functio ...

Nature Research2018

Closed-loop electrical neurostimulation: Challenges and opportunities

José del Rocio Millán Ruiz, Michael Eric Anthony Pereira, Inaki Asier Iturrate Gil

Non-invasive and invasive electrical neurostimulation are promising tools to better understand brain function and ultimately treat its malfunction. In current open-loop approaches, a clinician chooses a fixed set of stimulation parameters, informed by obse ...

2018

Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Stéphanie Martin, Robert Leeb, Inaki Asier Iturrate Gil, Aleksander Sobolewski, Jocelyne Bloch

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson’s Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, quest ...

2018

Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance

José del Rocio Millán Ruiz, Michael Eric Anthony Pereira, Serafeim Perdikis, Inaki Asier Iturrate Gil, Tiffany Corbet

Motor imagery (MI) has been largely studied as a way to enhance motor learning and to restore motor functions. Although it is agreed that users should emphasize kinesthetic imagery during MI, recordings of MI brain patterns are not sufficiently reliable fo ...

2018

Decoding Inner Speech Using Electrocorticography: Progress and Challenges Toward a Speech Prosthesis

José del Rocio Millán Ruiz, Stéphanie Martin, Inaki Asier Iturrate Gil

2018

mano: A Wearable Hand Exoskeleton for Activities of Daily Living and Neurorehabilitation

José del Rocio Millán Ruiz, Serafeim Perdikis, Inaki Asier Iturrate Gil, Luca Randazzo

Hand sensorimotor impairments are among the most common consequences of injuries affecting the central and peripheral nervous systems, leading to a drastic reduction in the quality of life for affected individuals. Combining wearable robotic exoskeletons a ...

Ieee-Inst Electrical Electronics Engineers Inc2018

Workshops of the Sixth International Brain–Computer Interface Meeting: brain–computer interfaces past, present, and future

Ricardo Andres Chavarriaga Lozano, Anton Nijholt, Inaki Asier Iturrate Gil

Brain–computer interfaces (BCI) (also referred to as brain–machine interfaces; BMI) are, by definition, an interface between the human brain and a technological application. Brain activity for interpretation by the BCI can be acquired with either invasive ...

2017

Spatial filters yield stable features for error-related potentials across conditions

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

Error-related potentials (ErrP) have been increasingly studied in psychophysical experiments as well as for brain-machine interfacing. In the latter case, the generalisation capabilities of ErrP decoders is a crucial element to avoid frequent recalibration ...

2016

First steps towards adaptive deep brain stimulation in Parkinson’s disease

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Robert Leeb, Inaki Asier Iturrate Gil, Aleksander Sobolewski, Jocelyne Bloch

2016

Word pair classification during imagined speech using direct brain recordings

José del Rocio Millán Ruiz, Stéphanie Martin, Inaki Asier Iturrate Gil

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used ...

Nature Research2016

Decoding of two hand grasping types from EEG

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

2016

Robust, accurate spelling based on error-related potentials

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

2016

Detecting intention to grasp during reaching movements from EEG

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Robert Leeb, Inaki Asier Iturrate Gil, Luca Randazzo

Brain-computer interfaces (BCI) have been shown to be a promising tool in rehabilitation and assistive scenarios. Within these contexts, brain signals can be decoded and used as commands for a robotic device, allowing to translate user’s intentions into mo ...

2015

Teaching brain-machine interfaces as an alternative paradigm to neuroprosthetics control

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

Brain-machine interfaces (BMI) usually decode movement parameters from cortical activity to control neuroprostheses. This requires subjects to learn to modulate their brain activity to convey all necessary information, thus imposing natural limits on the c ...

Nature Publishing Group2015