Brain in the loop: Assessing learning using fNIR in cognitive and motor tasks

Patricia A. Shewokis, Hasan Ayaz, Meltem Izzetoglu, Scott Bunce, Rodolphe J. Gentili, Itamar Sela, Kurtulus Izzetoglu, Banu Onaral

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

The skill acquisition process and learning assessments are dependent upon the quality and extent of practice of the tasks. Typically, learning is inferred from behavioral and cognitive results without taking into account the role of the brain in the learning loop. In this paper we discuss the neural mechanisms of learning and skill acquisition using fNIR with 3D spatial navigation tasks (e.g., MazeSuite), a center-out reaching movement task during which adaptation to new tool use was performed and mathematical problem solving tasks. Further, this research study compared and contrasted multiple analysis methods, which include general linear models of repeated measures during acquisition, retention and transfer phases of learning, learning curve analyses, the testing of fit of various learning models (i.e., power, exponential or other non-linear functions) and relationships between neural activation and behavioral measures.

Original languageEnglish (US)
Title of host publicationFoundations of Augmented Cognition
Subtitle of host publicationDirecting the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings
Pages240-249
Number of pages10
DOIs
StatePublished - Jul 19 2011
Event6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011 - Orlando, FL, United States
Duration: Jul 9 2011Jul 14 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6780 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011
CountryUnited States
CityOrlando, FL
Period7/9/117/14/11

Fingerprint

Brain
Navigation
Chemical activation
Testing
Learning Curve
Repeated Measures
Nonlinear Function
Learning
Activation
Linear Model
Dependent
Acquisition
Skills

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Shewokis, P. A., Ayaz, H., Izzetoglu, M., Bunce, S., Gentili, R. J., Sela, I., ... Onaral, B. (2011). Brain in the loop: Assessing learning using fNIR in cognitive and motor tasks. In Foundations of Augmented Cognition: Directing the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings (pp. 240-249). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6780 LNAI). https://doi.org/10.1007/978-3-642-21852-1_30
Shewokis, Patricia A. ; Ayaz, Hasan ; Izzetoglu, Meltem ; Bunce, Scott ; Gentili, Rodolphe J. ; Sela, Itamar ; Izzetoglu, Kurtulus ; Onaral, Banu. / Brain in the loop : Assessing learning using fNIR in cognitive and motor tasks. Foundations of Augmented Cognition: Directing the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings. 2011. pp. 240-249 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{5f1d946d55c649579da42dd0cbaf5ae6,
title = "Brain in the loop: Assessing learning using fNIR in cognitive and motor tasks",
abstract = "The skill acquisition process and learning assessments are dependent upon the quality and extent of practice of the tasks. Typically, learning is inferred from behavioral and cognitive results without taking into account the role of the brain in the learning loop. In this paper we discuss the neural mechanisms of learning and skill acquisition using fNIR with 3D spatial navigation tasks (e.g., MazeSuite), a center-out reaching movement task during which adaptation to new tool use was performed and mathematical problem solving tasks. Further, this research study compared and contrasted multiple analysis methods, which include general linear models of repeated measures during acquisition, retention and transfer phases of learning, learning curve analyses, the testing of fit of various learning models (i.e., power, exponential or other non-linear functions) and relationships between neural activation and behavioral measures.",
author = "Shewokis, {Patricia A.} and Hasan Ayaz and Meltem Izzetoglu and Scott Bunce and Gentili, {Rodolphe J.} and Itamar Sela and Kurtulus Izzetoglu and Banu Onaral",
year = "2011",
month = "7",
day = "19",
doi = "10.1007/978-3-642-21852-1_30",
language = "English (US)",
isbn = "9783642218514",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "240--249",
booktitle = "Foundations of Augmented Cognition",

}

Shewokis, PA, Ayaz, H, Izzetoglu, M, Bunce, S, Gentili, RJ, Sela, I, Izzetoglu, K & Onaral, B 2011, Brain in the loop: Assessing learning using fNIR in cognitive and motor tasks. in Foundations of Augmented Cognition: Directing the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6780 LNAI, pp. 240-249, 6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011, Orlando, FL, United States, 7/9/11. https://doi.org/10.1007/978-3-642-21852-1_30

Brain in the loop : Assessing learning using fNIR in cognitive and motor tasks. / Shewokis, Patricia A.; Ayaz, Hasan; Izzetoglu, Meltem; Bunce, Scott; Gentili, Rodolphe J.; Sela, Itamar; Izzetoglu, Kurtulus; Onaral, Banu.

Foundations of Augmented Cognition: Directing the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings. 2011. p. 240-249 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6780 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Brain in the loop

T2 - Assessing learning using fNIR in cognitive and motor tasks

AU - Shewokis, Patricia A.

AU - Ayaz, Hasan

AU - Izzetoglu, Meltem

AU - Bunce, Scott

AU - Gentili, Rodolphe J.

AU - Sela, Itamar

AU - Izzetoglu, Kurtulus

AU - Onaral, Banu

PY - 2011/7/19

Y1 - 2011/7/19

N2 - The skill acquisition process and learning assessments are dependent upon the quality and extent of practice of the tasks. Typically, learning is inferred from behavioral and cognitive results without taking into account the role of the brain in the learning loop. In this paper we discuss the neural mechanisms of learning and skill acquisition using fNIR with 3D spatial navigation tasks (e.g., MazeSuite), a center-out reaching movement task during which adaptation to new tool use was performed and mathematical problem solving tasks. Further, this research study compared and contrasted multiple analysis methods, which include general linear models of repeated measures during acquisition, retention and transfer phases of learning, learning curve analyses, the testing of fit of various learning models (i.e., power, exponential or other non-linear functions) and relationships between neural activation and behavioral measures.

AB - The skill acquisition process and learning assessments are dependent upon the quality and extent of practice of the tasks. Typically, learning is inferred from behavioral and cognitive results without taking into account the role of the brain in the learning loop. In this paper we discuss the neural mechanisms of learning and skill acquisition using fNIR with 3D spatial navigation tasks (e.g., MazeSuite), a center-out reaching movement task during which adaptation to new tool use was performed and mathematical problem solving tasks. Further, this research study compared and contrasted multiple analysis methods, which include general linear models of repeated measures during acquisition, retention and transfer phases of learning, learning curve analyses, the testing of fit of various learning models (i.e., power, exponential or other non-linear functions) and relationships between neural activation and behavioral measures.

UR - http://www.scopus.com/inward/record.url?scp=79960297558&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960297558&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-21852-1_30

DO - 10.1007/978-3-642-21852-1_30

M3 - Conference contribution

AN - SCOPUS:79960297558

SN - 9783642218514

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 240

EP - 249

BT - Foundations of Augmented Cognition

ER -

Shewokis PA, Ayaz H, Izzetoglu M, Bunce S, Gentili RJ, Sela I et al. Brain in the loop: Assessing learning using fNIR in cognitive and motor tasks. In Foundations of Augmented Cognition: Directing the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings. 2011. p. 240-249. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-21852-1_30