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Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
Neuroimaging software is used to study the structure and function of the brain. To see an NIH Blueprint for Neuroscience Research funded clearinghouse of many of these software applications, as well as hardware, etc. go to the NITRC web site. 3D Slicer Extensible, free open source multi-purpose software for visualization and analysis.
Many neuroscientists believe that the human mind is largely an emergent property of the information processing of its neuronal network. [9]Neuroscientists have stated that important functions performed by the mind, such as learning, memory, and consciousness, are due to purely physical and electrochemical processes in the brain and are governed by applicable laws.
By analyzing different metrics from these connection matrices from the network, one can obtain a topological analysis of the desired graph; and this is referred to as the human brain network in the field of neuroscience. [12] One of the core architectures in brain network models is the "small-world" architecture.
It was developed as part of the Human Brain Project neuromorphic computing platform and is the complement to the SpiNNaker supercomputer (which is based on digital technology). The architecture used in BrainScaleS mimics biological neurons and their connections on a physical level; additionally, since the components are made of silicon, these ...
Here's how that daily crossword puzzle really impacts cognitive functioning.
As a physical system with graph-like properties, [6] a large-scale brain network has both nodes and edges and cannot be identified simply by the co-activation of brain areas. In recent decades, the analysis of brain networks was made feasible by advances in imaging techniques as well as new tools from graph theory and dynamical systems.
The brain and the neural network should be considered as an integrated and self-contained firmware system that includes hardware (organs), software (programs), memory (short term and long term), database (centralized and distributed), and a complex network of active elements (such as neurons, synapses, and tissues) and passive elements (such as ...