TY - GEN
T1 - Brain in the loop
T2 - 6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011
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
N1 - Funding Information:
Acknowledgments. The spatial navigation task was funded in part by the Commonwealth of Pennsylvania # 4100037709 subcontract #240468 and Drexel University subcontract #280773.
PY - 2011
Y1 - 2011
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
Y2 - 9 July 2011 through 14 July 2011
ER -