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. © 2011 Springer-Verlag.