Embodied cognition analytics: a framework of experimental paradigms and analytics to study agency
Description
TitleEmbodied cognition analytics: a framework of experimental paradigms and analytics to study agency
Date Created2019
Other Date2019-10 (degree)
Extent1 online resource (xiii, 160 pages) : illustrations
DescriptionScientific findings abound with evidence that our behaviors are constrained by processes within our brain and body and by various external factors, leading us to wonder about the origin(s) of our behavior. In this thesis, I define agency as the capacity to change (at will) the immediate environment through one’s behavior; and setting agency as an overarching reflection of many constraining factors, I introduce the embodied cognition analytics (ECA) framework. This framework is a tool to study varying degrees of agency with respect to the processes within the nervous systems.
In a series of three experiments, I demonstrate a set of experimental and analytical paradigms that allow characterizing the dynamic stochasticity and self-emerging cohesiveness of disparate biophysical signals generated by the brain, the body, and the heart during natural, unconstrained actions. The final goal is to characterize the degree of agency, by examining the range of these dynamical changes, and comparing across populations of different agency. In the thesis, I limit the study of agency to the cognitive-motor domain, and compare the characterization across different populations, where the patient populations are assumed to have compromised cognitive/motor capacity, and the neurologically healthy population to have high cognitive-motor agency.
In the first study, I characterize the differing levels of motor control and cognitive load by adapting network analytics methods commonly used in the analyses of cortical signals (generated by the central nervous system; CNS) to the analyses of kinematics signal (generated by the peripheral nervous system; PNS), which were registered from motion sensors positioned across the upper body. In the second study, I extend the previous methods to capture the full CNS-PNS dynamical interactions, by co-registering and analyzing the biophysical signals generated by the CNS (of EEG data), PNS (of acceleration, magnetometer data), and ANS (of EKG data). I report on the changes in patterns of connectivity dynamically evolving across conditions (when the participant exerts control on his/her breathing pace) during naturalistic walking tasks, and compare them between healthy participants and patients with Autism Spectrum Disorder. In the last study, I examine the co-registered signals of the CNS (EEG data), PNS (magnetometer data), and ANS (EKG data), as in the second study, but have the participant perform a variety of tasks involving movements with different cognitive and memory processes. I later translate these tasks to the clinical realm by digitizing neurological diagnostic tests that assess cognition and memory in aging. Here, I present a set of analytics that we found to highlight the difference between Parkinson’s patients and healthy participants, with the aim to understand the interactive nature of the neurobiological system from individuals with varying degrees of cognitive-motor agency. These three experiments and analytics are not exhaustive, but would serve as proof-of-concept examples of the general framework to study agency.
Overall, the protocols and methods offered in this thesis provide a new unifying framework to characterize agency from the dynamical interaction of cognitive and motor processes registered by high resolution biophysical sensors. In this sense, the agency that I characterized is truly embodied, in that it is not a mere cognitive nor a motor capacity, but is a concerted and integrated capacity of both cognitive and motor behaviors. Furthermore, this framework enables an objective physical quantification of naturalistic cognitive activities in the laboratory and within clinical settings, thus providing new ways to connect basic and clinical sciences.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Statistical Profile