Computational Neuroscience Overview

Computational neuroscience (also theoretical neuroscience) is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.

It is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics.

Computational neuroscience – Scholarpedia

Experimental Neuroscience:
Electrophysiology, Neuron, Synapse, Memory, Conditioning, Consciousness ,Vision,Olfaction , Neuroimaging

Theoretical Neuroscience:
Models of Neurons , Spiking Networks, Network Dynamics, Brain Models

Dynamical Systems:
Oscillators, Synchronization, Pattern Formation, Chaos
Bifurcation, Simulation Environment

Computational Intelligence:
Brain Theory, Recurrent Networks, Feedforward Networks, Graph Theory, Reinforcement, Learning, Evolutionary Computation, Information Theory, Statistics, Signal Analysis. Pattern, Recognition, Navigation and Control, Robotics

Encyclopedia: Computational Models of brain disorders:
migraine, schizophrenia), stroke, affective disorders), Parkinson's disease, epilepsy....

Data Mining of Neuronal Morphologies

Knowledge Representation and Data Mining of Neuronal Morphologies Using Neuroinformatics tools and Formal Ontologies.

Bayesian Action & Perception (Review)

Representing the World in the Brain

In previous studies, a simple robot equipped with a biomimetic tactile sensor and operated according to Bayesian Exploration performed in a manner similar to and actually better than humans on a texture identification task. The biomimetic design of this mechatronic system may provide insights into the neuronal basis of biological action and perception.

Frontiers in Neuroscience October 2014 by Gerald E. Loeb and Jeremy A. Fishel

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