Publications by Ricardo Andres Chavarriaga Lozano

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Ronan Boulic, Ricardo Andres Chavarriaga Lozano, Bruno Herbelin, José del Rocio Millán Ruiz, Olaf Blanke, 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

EEG-Based Online Regulation of Difficulty in Simulated Flying

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Ping-Keng Jao

Adaptively increasing the difficulty level in learning was shown to be beneficial than increasing the level after some fixed time intervals. To efficiently adapt the level, we aimed at decoding the subjective difficulty level based on Electroencephalograph ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Aleksander Sobolewski, Fumiaki Iwane

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. ...

Cell Press2023

EEG signature of breaks in embodiment in VR

Ronan Boulic, Ricardo Andres Chavarriaga Lozano, Bruno Herbelin, José del Rocio Millán Ruiz, Olaf Blanke, Fumiaki Iwane, Thibault Serge Mario Porssut

The brain mechanism of embodiment in a virtual body has grown a scientific interest recently, with a particular focus on providing optimal virtual reality (VR) experiences. Disruptions from an embodied state to a less- or non-embodied state, denominated Br ...

2023

Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones

Dario Floreano, Ricardo Andres Chavarriaga Lozano, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

In search and rescue missions, drone operations are challenging and cognitively demanding. High levels of cognitive workload can affect rescuers’ performance, leading to failure with catastrophic outcomes. To face this problem, we propose a machine learnin ...

2022

User Adaptation to Closed-Loop Decoding of Motor Imagery Termination

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Bastien Orset, Kyuhwa Lee

One of the most popular methods in non-invasive brain machine interfaces (BMI) relies on the decoding of sensorimotor rhythms associated to sustained motor imagery. Although motor imagery has been intensively studied, its termination is mostly neglected. O ...

2021

Mobile brain/body imaging of landmark-based navigation with high-density EEG

Ricardo Andres Chavarriaga Lozano

Coupling behavioral measures and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly integrative function encompasses sensorimotor, cognitive, and executive processes that jointly me ...

WILEY2021

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

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

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

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI ...

NATURE PORTFOLIO2021

Closed-loop EEG study on visual recognition during driving

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Ruslan Aydarkhanov

Objective. In contrast to the classical visual brain-computer interface (BCI) paradigms, which adhere to a rigid trial structure and restricted user behavior, electroencephalogram (EEG)-based visual recognition decoding during our daily activities remains ...

2021

Context-Aware Learning for Generative Models

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Serafeim Perdikis, Robert Leeb

This work studies the class of algorithms for learning with side-information that emerges by extending generative models with embedded context-related variables. Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum- ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Uncovering EEG Correlates of Covert Attention in Soccer Goalkeepers: Towards Innovative Sport Training Procedures

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Luca Tonin

Advances in sports sciences and neurosciences offer new opportunities to design efficient and motivating sport training tools. For instance, using NeuroFeedback (NF), athletes can learn to self-regulate specific brain rhythms and consequently improve their ...

Nature Research2020

Spatial covariance improves BCI performance for late ERPs components with high temporal variability

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Marija Uscumlic, Lucian Andrei Gheorghe, Ruslan Aydarkhanov

Objective. Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in brain computer interfaces. ERP waveforms are characterized by a series of components of particular latency and amplitude. The classical ERP dec ...

2020

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

2020

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

Turning negative into positives! Exploiting 'negative' results in Brain-Machine Interface (BMI) research

Ricardo Andres Chavarriaga Lozano, Camille Marie Jeunet

Results that do not confirm expectations are generally referred to as 'negative' results. While essential for scientific progress, they are too rarely reported in the literature - Brain-Machine Interface (BMI) research is no exception. This led us to organ ...

TAYLOR & FRANCIS LTD2019

Reliable decoding of motor state transitions during imagined movement

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Bastien Orset

Current non-invasive Brain Machine interfaces commonly rely on the decoding of sustained motor imagery activity. This approach enables a user to control brain-actuated devices by triggering predetermined motor actions. However, despite of its broad range o ...

IEEE2019

Workshops of the seventh international brain-computer interface meeting: not getting lost in translation

Ricardo Andres Chavarriaga Lozano, Anton Nijholt, Kyuhwa Lee

The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics ...

TAYLOR & FRANCIS LTD2019

Interactions of spatial strategies producing generalization gradient and blocking: A computational approach

Ricardo Andres Chavarriaga Lozano

We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different varia ...

2018

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