Computational neuroscience - WikipediaThe computational neuroscience discipline roughly divides into two subfields. This field contains many aspects of mathematical neuroscience  which employs mathematical techniques to arrive at models. Models in theoretical neuroscience are often aimed at capturing the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, and chemical coupling via network oscillations , columnar and topographic architecture, all the way up to behavior. These computational models frame hypotheses that can often be directly tested by biological or psychological experiments. A second subfield, which is often called neural data science focuses on approaches towards making sense of the progressively larger datasets in neuroscience.
Computational Neuroscience and Cognitive Modelling
The problems and beauty of teaching computational neuroscience are discussed by reviewing three new textbooks. Roughly speaking it has two different meanings. First, how to use computational more precisely theoretical and mathematical methods to understand neural phenomena occurring at different hierarchical levels of neural organization. Second, how the brain computes if at all. The chapters were written by celebrated authors and grouped into sections reflecting the hierarchical organization of the nervous system: Overviews, The Synaptic Level, The Network Level, Neural Maps, Systems. The flagship conference of the emerging discipline was organized by Bower starting in As the Organization of the Computational Neuroscience website www.
Science China Information Sciences. The mechanism of human cognition and its computability provide an important theoretical foundation to intelligent computation of visual media.
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