Towards effective musical training neurofeedback: The assessment of cellist expertise with behavioral and electroencephalographic monitoring of auditory decision-making
-
1
US Army Research Laboratory, United States
-
2
Columbia University, United States
The assessment and subsequent training of musical capability is a topic that has covered music education, pedagogy and, lately, neuroscience. In the absence of a consistent biological measurement, musical capability is generally gauged by first-hand observation and instructors already deemed “experts” in music. Here, we take a different approach.
We show in these preliminary results that performance expertise in a particular instrument class – the cello was chosen as the illustrative example of such a class – can be measured using behavioral and electroencephalographic metrics measured during an appropriate auditory decision-making paradigm. For this assessment, we chose the paradigm of anomalous musical event (AME) detection in the form of sporadic key-changes to an otherwise well-known diatonic piece (e.g., J.S. Bach’s Cello Suite, No.1, Prelude).
We examined the behavioral and neural performance of five subject groups as they engaged in this paradigm: cellists, non-cellist string instrumentalists (e.g., violinists), singers, non-string instrumentalists (e.g., trumpeters) and non-musicians. All musician groups were comprised of active professionals whose musical and instrument-specific training were quantified by years of experience (all musician groups significantly greater than that of non-musicians).
We found significant differences in behavioral and neural metrics that differentiated musician and non-musician groups. Furthermore, we found that we could train a naïve classifier to predict group membership only from neural metrics using leave-one-out cross validation. Finally, we found that the “similarity” of a given group to that of the cello group was quantifiable via both neural and behavioral metrics, implying that a gradation towards cellist expertise could be actively tracked using this paradigm/analysis combination.
Looking ahead towards music education possibilities, this assessment provides a foundation for informed neurofeedback that poses the possibility of more targeted instrument training on a cognitive level. Due to the single-trial nature of the EEG analysis, a rapid feedback paradigm for neurofeedback is feasible and could be easily integrated into current music education contexts, especially where instrumental performance training is done. `
Acknowledgements
Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-15-2-0074.
Keywords:
Expertise,
machine learning applied to neuroscience,
Machine learning classification,
music cognition,
music perception,
Learning
Conference:
SAN2016 Meeting, Corfu, Greece, 6 Oct - 9 Oct, 2016.
Presentation Type:
Oral Presentation in SAN 2016 Conference
Topic:
Oral Presentations
Citation:
Sherwin
J,
Sajda
P and
Oie
KS
(2016). Towards effective musical training neurofeedback: The assessment of cellist expertise with behavioral and electroencephalographic monitoring of auditory decision-making.
Conference Abstract:
SAN2016 Meeting.
doi: 10.3389/conf.fnhum.2016.220.00038
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
01 Aug 2016;
Published Online:
01 Aug 2016.
*
Correspondence:
Dr. Jason Sherwin, US Army Research Laboratory, Aberdeen Proving Ground, United States, niceboston@gmail.com