"Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system."
The study of how the brain performs computations. Learn about the different models and theories of neural computation, their strengths and limitations, and their applications.
"Computational neuroscience employs mathematical models, computer simulations, theoretical analysis, and abstractions of the brain."
"Computational neuroscience can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous."
"Computational neuroscience employs computational simulations to validate and solve mathematical models."
"The term mathematical neuroscience is also used sometimes, to stress the quantitative nature of the field."
"Computational neuroscience focuses on the description of biologically plausible neurons (and neural systems) and their physiology and dynamics."
"Computational neuroscience is not directly concerned with biologically unrealistic models used in connectionism, control theory, cybernetics, quantitative psychology, machine learning, artificial neural networks, artificial intelligence, and computational learning theory."
"Although mutual inspiration exists and sometimes there is no strict limit between fields, with model abstraction in computational neuroscience depending on research scope and the granularity at which biological entities are analyzed."
"Models in theoretical neuroscience are aimed at capturing the essential features of the biological system at multiple spatial-temporal scales."
"Models capture the essential features at multiple spatial-temporal scales, from membrane currents, and chemical coupling via network oscillations, columnar and topographic architecture, nuclei, all the way up to psychological faculties like memory, learning, and behavior."
"Models frame hypotheses that can be directly tested by biological or psychological experiments."
"Computational neuroscience employs mathematical models, computer simulations, theoretical analysis, and abstractions of the brain to understand the principles that govern the development, structure, physiology, and cognitive abilities of the nervous system."
"Computational neuroscience employs mathematical models, computer simulations, theoretical analysis, and abstractions of the brain."
"The term mathematical neuroscience is also used sometimes, to stress the quantitative nature of the field."
"Computational neuroscience focuses on the description of biologically plausible neurons (and neural systems) and their physiology and dynamics, and it is therefore not directly concerned with biologically unrealistic models used in connectionism, control theory, cybernetics, quantitative psychology, machine learning, artificial neural networks, artificial intelligence, and computational learning theory."
"These computational models frame hypotheses that can be directly tested by biological or psychological experiments."
"Models in theoretical neuroscience are aimed at capturing the essential features of the biological system at multiple spatial-temporal scales."
"Models frame hypotheses that can be directly tested by biological or psychological experiments."
"Model abstraction in computational neuroscience depends on research scope and the granularity at which biological entities are analyzed."
"These computational models frame hypotheses that can be directly tested by biological or psychological experiments."