Poster Session A, Saturday, March 23, 1:30 pm - 3:30 pm, Pacific Concourse
Complexity of sequence learning: a mathematical insight into cognitive science
Yuri Dabaghian1, Andrey Tsvetkov2; 1Department of Neurology, The University of Texas in Houston, McGovern Medical School, Houston, TX 77030, 2Department of Neurobiology and Anatomy, The University of Texas in Houston, McGovern Medical School, Houston, TX 77030
Fundamentally, every cognitive test aims at measuring a subject's ability to deal with cognitive and memory tasks of various complexity. However, it has never been clear what precisely the measure of complexity is in each particular test. At the core of the difficulty is the fact that until recently, there existed no abstract concept that could naturally be adopted for describing the kind of tasks used in cognitive and behavioral studies. However, a measure of complexity of finite sequences proposed recently by V. Arnold seems to hold great practical value for developing a fundamentally new tool for cognitive assessments. We tested Arnold measure in a hierarchy of visual, auditory and virtual reality-based navigational learning tests offered to healthy young individuals (between 20 and 40 years of age). Our results suggest that the times required by different subjects to learn a particular task, the amount of errors produced in the process of learning and other characteristics of learning effort correlate with Arnold’s complexity of the underlying sequence, regardless of the task’s modality. The outcome of our study suggests that this apparently abstract mathematical construct—Arnold’s complexity measure—can be used for quantifying human cognitive performance in generic tasks and may lead to a concrete, practical and a general method for objective and transitive cognitive assessment of learning and memory capacity.
Topic Area: PERCEPTION & ACTION: Multisensory