ABSTRACT
This chapter provides examples of new data types to use with the statistical platform for individualized behavioral analysis so as to both simulate important aspects of inherent variations in natural behaviors and test predictions about signal-to-noise ratios and randomness in empirical data. Through several statistical lenses, we “zoom in and out” of deliberate and spontaneous biorhythms generated by the nervous systems during pointing and walking. We study the stochastic properties of these biorhythms with subsecond time precision. We analyze these data with an eye for corrective feedback information of use to the autism spectrum disorder researchers and clinicians alike. The chapter presents new experimental paradigms and methods that, for the first time, begin the challenging path of attempting to connect sociomotor cognition and neuromotor control. These attempts are grounded in the study of self-sensing and self-supervision or corrections of the motions derived from the continuous rhythms caused by the nervous systems.
