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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.
Forensic scientist [4]; Gentleman scientist – A financially independent scientist who pursues scientific study as a hobby [5]; Government scientist; Healthcare science; Hiwi – A German abbreviation for "assistant scientist"
The Biological Computer Laboratory, founded in 1958 and active until the mid-1970s under the direction of Heinz von Foerster at the University of Illinois at Urbana–Champaign, was a major incubator of this trend in cybernetics research. [22]
Depolarization of the membrane past its threshold potential generates an action potential, which is the main source of signal transmission, known as neurotransmission of the nervous system. An action potential results in a cascade of ion flux down and across an axonal membrane, creating an effective voltage spike train or "electrical signal ...
There are three main directions where neuroinformatics has to be applied: [2] the development of computational models of the nervous system and neural processes; the development of tools for analyzing and modeling neuroscience data; and; the development of tools and databases for management and sharing of neuroscience data at all levels of ...
Neurotechnology encompasses any method or electronic device which interfaces with the nervous system to monitor or modulate neural activity. [1] [2]Common design goals for neurotechnologies include using neural activity readings to control external devices such as neuroprosthetics, altering neural activity via neuromodulation to repair or normalize function affected by neurological disorders ...
Laboratory informatics is the specialized application of information technology aimed at optimizing and extending laboratory operations. [1] It encompasses data acquisition (e.g. through sensors and hardware [2] or voice [3] [4] [5]), instrument interfacing, laboratory networking, data processing, specialized data management systems (such as a chromatography data system), a laboratory ...