Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)

This research is motivated by developments in low cost BCIs and to inspire practical implementations. Such as, single electrode mobile EEGs leveraged in live settings by music listeners and performers. This research aims to provide guidance, to isolating electrode locations and frequency range selec...

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Main Author: Darmalingam, Kumaresh
Other Authors: Guan Cuntai
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/151269
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author Darmalingam, Kumaresh
author2 Guan Cuntai
author_facet Guan Cuntai
Darmalingam, Kumaresh
author_sort Darmalingam, Kumaresh
collection NTU
description This research is motivated by developments in low cost BCIs and to inspire practical implementations. Such as, single electrode mobile EEGs leveraged in live settings by music listeners and performers. This research aims to provide guidance, to isolating electrode locations and frequency range selections for the broader non-academic community. I analysed the publicly available NMED-T dataset of EEG recordings and rhythmic tapping, respectively during music listening. By drawing from Neural Resonance Theory, Dynamic Attending Theory, Neural Entrainment, Beat Perception and MIR methodologies, I deployed a series of predictive models to identify the most competitive single electrode and frequency combination that links to future listening and rhythmic behaviour. The most competitive model used electrode measuring the premotor cortex in the sub-harmonic range of the beat frequency based on the music stimuli, to predict tapping rates of future listening to the same song (Precision=0.74, s=0.19). This suggests that future sensorimotor responses like tapping behaviour can be reliably predicted using responses to neural entrainment. The learnings will hopefully lower the entry barrier for developments within the music community. Findings also highlight that the most informative features were extracted at the sub-harmonics, encouraging research aiming to use entrainment to consider neural harmonics too.
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spelling ntu-10356/1512692021-07-08T16:01:19Z Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics) Darmalingam, Kumaresh Guan Cuntai School of Computer Science and Engineering Kat Agres Steffen Herff CTGuan@ntu.edu.sg, muskra@nus.edu.sg, steffen.herff@epfl.ch Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Social sciences::Psychology::Consciousness and cognition This research is motivated by developments in low cost BCIs and to inspire practical implementations. Such as, single electrode mobile EEGs leveraged in live settings by music listeners and performers. This research aims to provide guidance, to isolating electrode locations and frequency range selections for the broader non-academic community. I analysed the publicly available NMED-T dataset of EEG recordings and rhythmic tapping, respectively during music listening. By drawing from Neural Resonance Theory, Dynamic Attending Theory, Neural Entrainment, Beat Perception and MIR methodologies, I deployed a series of predictive models to identify the most competitive single electrode and frequency combination that links to future listening and rhythmic behaviour. The most competitive model used electrode measuring the premotor cortex in the sub-harmonic range of the beat frequency based on the music stimuli, to predict tapping rates of future listening to the same song (Precision=0.74, s=0.19). This suggests that future sensorimotor responses like tapping behaviour can be reliably predicted using responses to neural entrainment. The learnings will hopefully lower the entry barrier for developments within the music community. Findings also highlight that the most informative features were extracted at the sub-harmonics, encouraging research aiming to use entrainment to consider neural harmonics too. Master of Engineering 2021-06-23T08:52:03Z 2021-06-23T08:52:03Z 2021 Thesis-Master by Research Darmalingam, K. (2021). Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics). Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/151269 https://hdl.handle.net/10356/151269 10.32657/10356/151269 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Social sciences::Psychology::Consciousness and cognition
Darmalingam, Kumaresh
Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title_full Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title_fullStr Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title_full_unstemmed Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title_short Predicting sensorimotor responses to rhythmic events : an EEG study of neuronal entrainment & beat perception (cognizant through harmonics)
title_sort predicting sensorimotor responses to rhythmic events an eeg study of neuronal entrainment beat perception cognizant through harmonics
topic Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Social sciences::Psychology::Consciousness and cognition
url https://hdl.handle.net/10356/151269
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