We introduce a cognitive brain-computer interface based on a continuous performance task for the monitoring of variations of visual sustained attention, i.e. the self-directed maintenance of cognitive focus in non-arousing conditions while possibly ignoring distractors and avoiding mind wandering. We introduce a visual sustained attention continuous performance task with three levels of task difficulty. Pairwise discrimination of these task difficulties from electroencephalographic features was performed using a leave-one-subject-out cross validation approach. Features were selected using the orthogonal forward regression supervised feature selection method. Cognitive load was best predicted using a combination of prefrontal theta power, broad spatial range gamma power, fronto-central beta power, and fronto-central alpha power. Generalization performance estimates for pairwise classification of task difficulty using these features reached 75% for 5 s epochs, and 85% for 30 s epochs.
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http://dx.doi.org/10.1007/s11571-019-09521-4 | DOI Listing |
Sensors (Basel)
December 2024
Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain.
In this paper, a bibliometric review is conducted on brain-computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory and descriptive approach is used in the analysis. Computational tools such as the biblioshiny application for R-Bibliometrix and VOSViewer are employed to generate data on years, sources, authors, affiliation, country, documents, co-author, co-citation, and co-occurrence.
View Article and Find Full Text PDFJ Neurosci
January 2025
Department of Psychology, Chinese University of Hong Kong, Hong Kong SAR, China
The extraction and analysis of pitch underpin speech and music recognition, sound segregation, and other auditory tasks. Perceptually, pitch can be represented as a helix composed of two factors: height monotonically aligns with frequency, while chroma cyclically repeats at doubled frequencies. Although the early perceptual and neurophysiological mechanisms for extracting pitch from acoustic signals have been extensively investigated, the equally essential subsequent stages that bridge to high-level auditory cognition remain less well understood.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125.
Cognition relies on transforming sensory inputs into a generalizable understanding of the world. Mirror neurons have been proposed to underlie this process, mapping visual representations of others' actions and sensations onto neurons that mediate our own, providing a conduit for understanding. However, this theory has limitations.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
Introduction: As brain-computer interfacing (BCI) systems transition fromassistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important. Dynamic stopping methods enhance BCI system speed by deciding at any moment whether to output a result or wait for more information. Such approach leverages trial variance, allowing good trials to be detected earlier, thereby speeding up the process without significantly compromising accuracy.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
This systematic review examines EEG-based imagined speech classification, emphasizing directional words essential for development in the brain-computer interface (BCI). This study employed a structured methodology to analyze approaches using public datasets, ensuring systematic evaluation and validation of results. This review highlights the feature extraction techniques that are pivotal to classification performance.
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