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Poster (Scientific congresses, symposiums and conference proceedings)
Decoding Hypnotic Experience from Raw EEG Data using a Multi-Output Auto-Encoder
Farahzadi, Yeganeh; Ansarinia, Morteza; Kekecs, Zoltan
20232023 Conference on Cognitive Computational Neuroscience


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Keywords :
Deep Learning; Sequence Embedding; Brain-to-Brain Coupling
Abstract :
[en] In this study, we propose a novel approach for quantifying brain-to-brain coupling during a hypnosis induction. Our approach uses a multi-output sequence-to-sequence deep neural network applied to raw EEG data recorded from 51 participants using 59 electrodes. Specifically, we use a long short-term memory (LSTM) encoder to extract an embedding, which is then utilized for two downstream heads: one head to predict the hypnotist's brain activity, and the other head to classify the level of hypnotic depth. We found that removing the head that predicted the hypnotist's brain activity substantially decreased the accuracy of the classification head, indicating that this head plays a critical role in achieving better classification performance. These results highlight the importance of shared representations in shaping social interactions. Ultimately, this work can help us better understand the dynamics of verbal communication.
Disciplines :
Social & behavioral sciences, psychology: Multidisciplinary, general & others
Author, co-author :
Farahzadi, Yeganeh;  Eötvös Loránd University > Department of Cognitive Psychology
Ansarinia, Morteza  ;  University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)
Kekecs, Zoltan;  Eötvös Loránd University > Department of Affective Psychology
External co-authors :
Language :
Title :
Decoding Hypnotic Experience from Raw EEG Data using a Multi-Output Auto-Encoder
Publication date :
August 2023
Number of pages :
Event name :
2023 Conference on Cognitive Computational Neuroscience
Event place :
Oxford, United Kingdom
Event date :
from 24-08-2023 to 27-08-2023
Focus Area :
Computational Sciences
Available on ORBilu :
since 08 June 2023


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