Andrew Felch

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Humans outperform computers on many natural tasks including vision. Given the human ability to recognize objects rapidly and almost effortlessly, it is pragmatically sensible to study and attempt to imitate algorithms used by the brain. Analysis of the anatomical structure and physiological operation of brain circuits has led to derivation of novel(More)
Algorithms are often sought whose speed increases as processing elements are added, yet attempts at such parallelization typically result in little speedup, due to serial dependencies intrinsic to many algorithms. A novel class of algorithms have been developed that exhibit intrinsic parallelism, so that when processing elements are added to increase their(More)
The development of connectivity among brain networks (e.g., thalamocortical, cortico-thalamic, cortico-cortical) proceeds via a combination of axon and dendrite growth followed by a later process of synaptic pruning [Purves, D., Lichtman, J.W., 1980. Elimination of synapses in the developing nervous system. Science, 210, 153-157; Oppenheim, R.W., 1991. Cell(More)
Even though computing systems have increased the number of transistors , the switching speed, and the number of processors, most programs exhibit limited speedup due to the serial dependencies of existing algorithms. Analysis of intrinsically parallel systems such as brain circuitry have led to the identification of novel architecture designs, and also new(More)
Ab st ract Cognition is the action and interaction of multiple brain regions, and these are becoming understood computationally. Simulation and analysis has led to derivation of a set of elemental operations that emerge from individual and combined brain circuits, such that each circuit contributes a particular algorithm, and pairs and larger groups(More)
The analysis of particular telencephalic systems has led to derivation of algorithmic statements of their operation, which have grown to include communicating systems from sensory to motor and back. Like the brain circuits from which they are derived, these algorithms (e.g. Granger, 2006) perform and learn from experience. Their perception and action(More)
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