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008			220611s2022 xxua s |||| 0|eng d
020			_a9781071610060
024	7		_a10.1007/978-1-0716-1006-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP357.5 _b2022 EB
245	0	0	_aEncyclopedia of Computational Neuroscience _cedited by Dieter Jäger, Ranu Jung
250			_a2nd edition 2022
264		1	_aNew York, NY _bSpringer International Publishing _c2022
300			_a1 recurso en línea _b318 ilustraciones
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_aAstrocyte Models -- Auditory Sensing Systems -- Basal Ganglia -- Bayesian Approaches in Computational Neuroscience -- Biochemical Signaling Pathways and Diffusion -- Brain Imaging -- Brain Machine Interface -- Cable Theory -- Cerebellum -- Compartmental Modeling -- Computational Neuroanatomy -- Cortex -- Databases in Computational Neuroscience -- Decision Making -- Deep Brain Stimulation (Models, Theory, Techniques) -- Dynamical Systems -- Dynamics of Disease States -- Gamma and Theta Oscillations, Hippocampus -- Information Theory -- Invertebrate Pattern Generation -- Invertebrate Sensory Systems -- Ion Channel Types and Modeling -- Learning Rules -- LFP Analysis -- Low Frequency Oscillations (Anesthesia and Sleep) -- Model Reproducibility -- Modeling of Disease - Molecular Level -- Modeling Software Tools -- Motoneurons and Neuromuscular Systems -- Multistability in Neurodynamics -- Neural Population Models and Cortical Field Theory -- Neuromodulation -- Neuromorphic Engineering -- Neuronal Model Optimization -- Olfaction -- Peripheral Nerve Interfaces -- Phase Response Curves -- Retinal/Visual Interfaces (Models, Theory, Techniques) -- Somatosensory System -- Spectral Methods in Neural Data Analysis -- Spike Train Analysis -- Spinal and Neuromechanical Integration -- Spinal Interfaces -- Synaptic Dynamics -- Vertebrate Pattern Generation -- -- Vestibular System -- Visual System.
520			_aThe annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation. Riding on the success of several seminal papers, physicists had made "Neural Networks" fashionable, and soon the quantitative methods used in these abstract model networks started permeating the methods and ideas of experimental neuroscientists. Although experimental neurophysiological approaches provided many advances, it became increasingly evident that mathematical and computational techniques would be required to achieve a comprehensive and quantitative understanding of neural system function. "Computational Neuroscience" emerged to complement experimental neurophysiology. The Encyclopedia of Computational Neuroscience, published in conjunction with the Organization for Computational Neuroscience, will be an extensive reference work consultable by both researchers and graduate level students. It will be a dynamic, living reference, updatable and containing linkouts and multimedia content whenever relevant.
988			_aSpringer_BiomedLife_2022
650		7	_2embne _9481390 _aNeurociencia computacional
700	1		_aJäger, Dieter. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aJung, Ranu. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer Nature eReference
776	0	8	_iPrinted edition: _z9781071610053
776	0	8	_iPrinted edition: _z9781071610046
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-1006-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b09/2022 _dz _ek _zSI