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Computational neuroscience is an interdisciplinary field that combines engineering, biology, control systems, brain functions, physical sciences, and computer science. It has fundamental development models done at the lower levels of ions, neurons, and synapses, as well as information propagation between neurons.
By 1950, Sherrington, Papez, and MacLean had identified many of the brainstem and limbic system functions. [251] [252] The capacity of the brain to re-organise and change with age, and a recognised critical development period, were attributed to neuroplasticity, pioneered by Margaret Kennard, who experimented on monkeys during the 1930-40s. [253]
Raichle coined the term "default mode" in 2001 to describe resting state brain function; [19] the concept rapidly became a central theme in neuroscience. [20] Around this time the idea was developed that this network of brain areas is involved in internally directed thoughts and is suspended during specific goal-directed behaviors.
The salience network is theorised to mediate switching between the default mode network and frontoparietal network (central executive network). [1] [2] [3]The frontoparietal network (FPN), generally also known as the central executive network (CEN) or, more specifically, the lateral frontoparietal network (L-FPN) (see Nomenclature), is a large-scale brain network primarily composed of the ...
The dynamical systems approach to neuroscience is a branch of mathematical biology that utilizes nonlinear dynamics to understand and model the nervous system and its functions. In a dynamical system, all possible states are expressed by a phase space . [ 1 ]
The resulting model had more than 140,000 neurons with over 50 million synapses. [21] From the model, research expect to identify how the brain creates new connections for functions such as vision, creating digital twin equivalents to track how segments of the neuron connection map interact to external signals, including the nervous system. [22]