Computational Neurology and Neuroinformatics

Computational neuroscience is distinct from psychological connectionism and machine learning in that it emphasizes descriptions of functional and biologically realistic neurons (and neural systems) and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations, columnar and topographic architecture and learning and memory. These computational models are used to frame hypotheses that can be directly tested by current or future biological and/or psychological experiments.

Neuroinformatic is an examination field worried with the association of neuroscience information using computational models and explanatory apparatuses. These territories of research are critical for the coordination and investigation of progressively extensive volume, high-dimensional, and fine-grain exploratory information. Neuroinformaticians give computational instruments, scientific models, and make interoperable databases for clinicians and research researchers.

 

  • Single neuron modelling
  • Development, axonal patterning, and guidance
  • Sensory processing
  • Memory and synaptic plasticity
  • Behaviours of networks Neural Computation
  • Neuroengineering
  • Brain Informatics
  • Analysis and modelling of CNS and neuronal system

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