Slowness of thought is not necessarily a handicap but could be a signature of optimal brain function. Emerging evidence shows that neuroanatomical and dynamical constraints of the human brain shape its functionality in optimal ways, characterized by slowness during task-based cognition in the context of spontaneous resting-state activity. This activity can be described mechanistically by whole-...

We study the space complexity of implementing long-lived and one-shot adaptive renaming from multi-reader multi-writer registers, in an asynchronous distributed system with n processes. As a result of an f -adaptive renaming algorithm each participating process gets a distinct name in the range {1, . . . , f (k)} provided k processes participate. Let f : {1, . . . ,n}→N be a non-decreasing func...

We studied 10 subjects each with melancholic depression evidencing significant motor retardation (RM), Parkinson's disease (PD) with bradykinesia, and normal healthy controls (NC), matched closely for age and gender, on measurements of motor function and depression, and their performance of simple and complex ballistic movements. The simple movements involved the execution of 10 degrees, 20 deg...

Slowness in robotic systems is a quality that is typically undervalued. It is our contention that as slowness has utility in animal behavior in certain species that it may also provide useful qualities for robotic implementations in appropriate circumstances. In particular we study mammalian behavior as evidenced in the tree sloth and slow Loris as the basis for the behaviors of a robot capable...

Slow feature analysis (SFA) is an unsupervised-learning algorithm that extracts slowly varying features from a multi-dimensional time series. A supervised extension to SFA for classification and regression is graph-based SFA (GSFA). GSFA is based on the preservation of similarities, which are specified by a graph structure derived from the labels. It has been shown that hierarchical GSFA (HGSFA...