Computational Neuroscience

Computational neuroscience is the study of brain function and behavior by using data-driven and mathematical approaches. It combines mathematics, computer science, and neuroscience and applies them to understand the structure and function of the nervous system. Computational neuroscience is used to develop hypotheses and theories that can explain how the brain works, why certain behaviors emerge, and to identify the mechanisms of diseases related to the brain. Some of its applications include the development of artificial intelligence, neural prosthesis, brain-computer interfaces and neuromorphic engineering. This field of research provides important insights into brain function, which can lead to better treatments for neurological and psychiatric disorders, such as Alzheimer’s disease, Parkinson’s disease, and autism.

← International Journal of Neuroinformatics

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Computational EPAS1 rSNP Analysis, Transcriptional Factor Binding Sites and High Altitude Sickness or Adaptation

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Computational STAT4 rSNP Analysis, Transcriptional Factor Binding Sites and Disease

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Retinal and Cortical Contributions to Excessive V1 Neuron Firing Rate Variability in Schizophrenia: A Computational Modeling Analysis

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Neuroscience Theories, Hypothesis and Approaches to ASD Physiopathology. A Review

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Quantitative Computational Prediction of the Consensus B-cell Epitopes of 2019-nCoV

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Computational Systemic Biology for Toxicity Studies: A Mini Review of Previously Published Articles

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