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Natalizio A, Sieghartsleitner S, Schreiner L, Walchshofer M, Esposito A, Scharinger J, Pretl H, Arpaia P, Parvis M, Solé-Casals J, Sebastián-Romagosa M, Ortner R, Guger C. Real-time estimation of EEG-based engagement in different tasks. J Neural Eng 2024; 21:016014. [PMID: 38237182 DOI: 10.1088/1741-2552/ad200d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/18/2024] [Indexed: 02/01/2024]
Abstract
Objective.Recent trends in brain-computer interface (BCI) research concern the passive monitoring of brain activity, which aim to monitor a wide variety of cognitive states. Engagement is such a cognitive state, which is of interest in contexts such as learning, entertainment or rehabilitation. This study proposes a novel approach for real-time estimation of engagement during different tasks using electroencephalography (EEG).Approach.Twenty-three healthy subjects participated in the BCI experiment. A modified version of the d2 test was used to elicit engagement. Within-subject classification models which discriminate between engaging and resting states were trained based on EEG recorded during a d2 test based paradigm. The EEG was recorded using eight electrodes and the classification model was based on filter-bank common spatial patterns and a linear discriminant analysis. The classification models were evaluated in cross-task applications, namely when playing Tetris at different speeds (i.e. slow, medium, fast) and when watching two videos (i.e. advertisement and landscape video). Additionally, subjects' perceived engagement was quantified using a questionnaire.Main results.The models achieved a classification accuracy of 90% on average when tested on an independent d2 test paradigm recording. Subjects' perceived and estimated engagement were found to be greater during the advertisement compared to the landscape video (p= 0.025 andp<0.001, respectively); greater during medium and fast compared to slow Tetris speed (p<0.001, respectively); not different between medium and fast Tetris speeds. Additionally, a common linear relationship was observed for perceived and estimated engagement (rrm= 0.44,p<0.001). Finally, theta and alpha band powers were investigated, which respectively increased and decreased during more engaging states.Significance.This study proposes a task-specific EEG engagement estimation model with cross-task capabilities, offering a framework for real-world applications.
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Affiliation(s)
- Angela Natalizio
- g.tec medical engineering GmbH, Schiedlberg, Austria
- Augmented Reality for Health Monitoring Laboratory (ARHeMLab), Università degli Studi di Napoli Federico II, Naples, Italy
- Department of Electronics and Telecommunications (DET), Polytechnic of Turin, Turin, Italy
| | - Sebastian Sieghartsleitner
- g.tec medical engineering GmbH, Schiedlberg, Austria
- Institute of Computational Perception, Johannes Kepler University, Linz, Austria
| | - Leonhard Schreiner
- g.tec medical engineering GmbH, Schiedlberg, Austria
- Institute for Integrated Circuits, Johannes Kepler University, Linz, Austria
| | | | - Antonio Esposito
- Augmented Reality for Health Monitoring Laboratory (ARHeMLab), Università degli Studi di Napoli Federico II, Naples, Italy
- Department of Engineering for Innovation University of Salento, Lecce, Italy
| | - Josef Scharinger
- Institute of Computational Perception, Johannes Kepler University, Linz, Austria
| | - Harald Pretl
- Institute for Integrated Circuits, Johannes Kepler University, Linz, Austria
| | - Pasquale Arpaia
- Augmented Reality for Health Monitoring Laboratory (ARHeMLab), Università degli Studi di Napoli Federico II, Naples, Italy
- Department of Electrical Engineering and Information Technology (DIETI), Università degli Studi di Napoli Federico II, Naples, Italy
- Centro Interdipartimentale di Ricerca in Management Sanitario e Innovazione in Sanità (CIRMIS), Università degli Studi di Napoli Federico II, Naples, Italy
| | - Marco Parvis
- Department of Electronics and Telecommunications (DET), Polytechnic of Turin, Turin, Italy
| | - Jordi Solé-Casals
- Data and Signal Processing Research Group, University of Vic-Central, University of Catalonia, Vic, Catalonia, Spain
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | | | - Rupert Ortner
- g.tec medical engineering Spain SL, Barcelona, Spain
| | - Christoph Guger
- g.tec medical engineering GmbH, Schiedlberg, Austria
- g.tec medical engineering Spain SL, Barcelona, Spain
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White E, Dalley JW. Brain mechanisms of temporal processing in impulsivity: Relevance to attention-deficit hyperactivity disorder. Brain Neurosci Adv 2024; 8:23982128241272234. [PMID: 39148691 PMCID: PMC11325328 DOI: 10.1177/23982128241272234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 06/25/2024] [Indexed: 08/17/2024] Open
Abstract
In this article, we critique the hypothesis that different varieties of impulsivity, including impulsiveness present in attention-deficit hyperactivity disorder, encompass an accelerated perception of time. This conceptualisation provides insights into how individuals with attention-deficit hyperactivity disorder have the capacity to maximise cognitive capabilities by more closely aligning themselves with appropriate environmental contexts (e.g. fast paced tasks that prevent boredom). We discuss the evidence for altered time perception in attention-deficit hyperactivity disorder alongside putative underlying neurobiological substrates, including a distributed brain network mediating time perception over multiple timescales. In particular, we explore the importance of temporal representations across the brain for time perception and symptom manifestation in attention-deficit hyperactivity disorder, including a prominent role of the hippocampus and other temporal lobe regions. We also reflect on how abnormalities in the perception of time may be relevant for understanding the aetiology of attention-deficit hyperactivity disorder and mechanism of action of existing medications.
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Affiliation(s)
- Eleanor White
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychiatry, Herschel Smith Building for Brain and Mind Sciences, Cambridge, UK
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