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New PDF release: Computational Neuroscience: Theoretical Insights into Brain

By Paul Cisek, Trevor Drew, John Kalaska

ISBN-10: 0444528237

ISBN-13: 9780444528230

Computational neuroscience is a comparatively new yet speedily increasing region of analysis that is turning into more and more influential in shaping the best way scientists take into consideration the mind. Computational ways were utilized in any respect degrees of research, from targeted types of single-channel functionality, transmembrane currents, single-cell electric task, and neural signaling to extensive theories of sensory belief, reminiscence, and cognition. This publication offers a picture of this intriguing new box via bringing jointly chapters on a range of subject matters from a few of its most crucial individuals. This contains chapters on neural coding in unmarried cells, in small networks, and around the complete cerebral cortex, visible processing from the retina to item acceptance, neural processing of auditory, vestibular, and electromagnetic stimuli, development iteration, voluntary move and posture, motor studying, decision-making and cognition, and algorithms for trend popularity. each one bankruptcy offers a bridge among a physique of knowledge on neural functionality and a mathematical technique used to interpret and clarify that information. those contributions exhibit how computational techniques became a vital software that is fundamental in lots of elements of mind technology, from the translation of knowledge to the layout of recent experiments, and to the expansion of our realizing of neural functionality.

• contains contributions by way of one of the most influential humans within the box of computational neuroscience
• Demonstrates how computational techniques are getting used this present day to interpret experimental data
• Covers quite a lot of subject matters from unmarried neurons, to neural structures, to summary versions of studying

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Additional info for Computational Neuroscience: Theoretical Insights into Brain Function

Example text

This remarkable ability is evolutionarily important since it allows us to distinguish friend from foe and identify food targets in complex, crowded scenes. Despite the ease with which we see, visual recognition — one of the key issues addressed in computer vision — is quite difficult for computers. The problem of object ÃCorresponding author. 1016/S0079-6123(06)65004-8 33 34 describe a quantitative theory of object recognition in primate visual cortex that (1) bridges several levels of understanding from biophysics to physiology and behavior and (2) achieves human level performance in rapid recognition of complex natural images.

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H. L. (2002) Spatial frequency and orientation tuning dynamics in area V1. Proc. Natl. Acad. Sci. , 99: 1645–1650. , Shelley, M. and Wielaard, J. (2000) A neuronal network model of sharpening and dynamics of orientation tuning in an input layer of macaque primary visual cortex. Proc. Natl. Acad. Sci. , 97: 8087–8092. J. and Fregnac, Y. (2003) Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning. Neuron, 37: 663–680.

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Computational Neuroscience: Theoretical Insights into Brain Function by Paul Cisek, Trevor Drew, John Kalaska


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