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- Orange Coast College
- Orange Coast College

... Complex computer manipulations of data obtained from x-ray absorption by tissues of different densities. ...
State-Dependent TMS Reveals a Hierarchical
State-Dependent TMS Reveals a Hierarchical

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... could orbit the sun in a different pattern, such as Venus’ or Mars’, its current orbit is ideal for life. If a doomsday asteroid knocked the Earth slightly off track, wouldn’t it be great if the Earth had a natural tendency to fall back into the characteristic orbit that we know and love? Oscillator ...
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Chapter 17 Intrinsic Optical Signal Imaging of Normal and Abnormal
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PDF
PDF

... was once thought to be exclusive to humans, partly because two behaviors that we like to consider as typically human, namely hand usage and language, display sidedness. However, this notion has been dispelled over the last century by an accumulation of data that demonstrates asymmetric behaviors in ...
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292(1):94-106
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The Effect of Slow Electrical Stimuli to Achieve Learning in Cultured
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A Double-labeling Investigation of the Afferent Connectivity to
A Double-labeling Investigation of the Afferent Connectivity to

... neurons were nearly always restricted to the region of overlap of the two populations of single-labeled neurons. We concluded from this observation that the two branches of a bifurcating axon terminate in cortical regions representing the same portion of the visual field. Since then, several experim ...
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Nervous system network models

Network of human nervous system comprises nodes (for example, neurons) that are connected by links (for example, synapses). The connectivity may be viewed anatomically, functionally, or electrophysiologically. These are presented in several Wikipedia articles that include Connectionism (a.k.a. Parallel Distributed Processing (PDP)), Biological neural network, Artificial neural network (a.k.a. Neural network), Computational neuroscience, as well as in several books by Ascoli, G. A. (2002), Sterratt, D., Graham, B., Gillies, A., & Willshaw, D. (2011), Gerstner, W., & Kistler, W. (2002), and Rumelhart, J. L., McClelland, J. L., and PDP Research Group (1986) among others. The focus of this article is a comprehensive view of modeling a neural network (technically neuronal network based on neuron model). Once an approach based on the perspective and connectivity is chosen, the models are developed at microscopic (ion and neuron), mesoscopic (functional or population), or macroscopic (system) levels. Computational modeling refers to models that are developed using computing tools.
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