Principles of Computational Neuroscience
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Computational neuroscience is a branch of neuroscience that utilizes theoretical analysis, mathematical models, and abstractions of the brain to comprehend the nervous system. It delves into the study of the nervous system's structure, physiology, cognitive capacities, and development. Models within this sphere aim to encapsulate critical attributes of the biological system across multiple spatial and temporal scales. These models serve to formulate hypotheses that can undergo testing via biological or psychological experiments. Major areas of study within computational neuroscience include si...
Computational neuroscience is a branch of neuroscience that utilizes theoretical analysis, mathematical models, and abstractions of the brain to comprehend the nervous system. It delves into the study of the nervous system's structure, physiology, cognitive capacities, and development. Models within this sphere aim to encapsulate critical attributes of the biological system across multiple spatial and temporal scales. These models serve to formulate hypotheses that can undergo testing via biological or psychological experiments. Major areas of study within computational neuroscience include single-neuron modeling, sensory processing, motor control, discrimination and learning, cognition, synaptic plasticity, memory, and computational clinical neuroscience. This book provides significant information of this discipline to help develop a good understanding of computational neuroscience. It unfolds the innovative aspects of this area which will be crucial for the holistic understanding of the subject matter. This textbook, with its detailed analyses and data, will prove immensely beneficial to students involved in this area at various levels.
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