Computational Neurology

Computational neuroscience is the study of brain characteristic in terms of the facts processing properties of the systems that make up the nervous system. It is an interdisciplinary technology that links the various fields of neuroscience, cognitive science and psychology with electrical engineering, computer science, mathematics and physics. Computational neuroscience is wonderful from psychological connectionism and machine learning in that it emphasizes descriptions of functional and biologically sensible neurons (and neural structures) and their physiology and dynamics. Those models seize the essential capabilities of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations, columnar and topographic structure and gaining knowledge of and memory. Those computational models are used to frame hypotheses that can be directly examined by modern-day or future biological and/or psychological experiments.

 

  • Single-neuron modeling
  • Development, axonal patterning, and guidance
  • Sensory processing
  • Memory and synaptic plasticity
  • Computational clinical neuroscience

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