000			06129nam a22004095i 4500
988			_aSpringer_BiomedLife_2019
999			_c116810 _d116810 _x1
001			116810
003			ES-MaUEC
005			20230104140206.0
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007			cr nn nnnaamaa
008			191011s2019 gw | s |||| 0|eng d
020			_a9783030188306
024	7		_a10.1007/978-3-030-18830-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRC386.2 _b2019 EB
245	0	0	_aMultiscale Models of Brain Disorders _cedited by Vassilis Cutsuridis.
250			_a1st ed. 2019.
264		1	_aCham, Switzerland _bSpringer International Publishing _c2019
300			_a1 recurso en línea (XIV, 222 páginas) _b62 ilustraciones, 52 ilustraciones
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
490	0		_aSpringer Series in Cognitive and Neural Systems _x2363-9105 _v13
490	0		_aBiomedical and Life Sciences (Springer-11642)
505	0		_aPart I Movement Disorders -- A neuro-computational model of Pallidal vs. Subthalamic Deep Brain Stimulation Effect on synchronization at Tremor frequency in Parkinson's disease, Alekhya Mandali, Srinivasa Chakravarthy V, Ahmed A. Moustafa -- Dynamics of Basal Ganglia and Thalamus in Parkinsonian Tremor, Jan Moren, Jun Igarashi, Osamu Shouno, Junichiro Yoshimoto, and Kenji Doya -- A neural mass model for abnormal beta-rebound in schizophrenia, Aine Byrne, Stephen Coombes, and Peter F Liddle -- Basal ganglio-thalamo-cortico-spino-muscular model of Parkinson's disease bradykinesia, Vassilis Cutsuridis -- Network Models of the Basal Ganglia in Parkinson's Disease: Advances in Deep Brain Stimulation through Model-Based Optimization, Karthik Kumaravelu1, Warren M. Grill -- Neural synchronization in Parkinson's disease on different time-scales, Sungwoo Ahn, Choongseok Park, Leonid L. Rubchinsky -- Obsessive compulsive tendencies and action sequence complexity: An Information Theory Analysis, Mustafa Zeki, Fuat Balcı, Tutku Öztel, Ahmed A. Moustafa -- Part II Cognitive Disorders -- Cortical disinhibition, attractor dynamics and belief updating in schizophrenia, Rick A Adams -- Modelling cognitive processing of healthy controls and obsessive compulsive disorder subjects in the antisaccade task, Vassilis Cutsuridis -- Simulating cognitive deficits in Parkinson's disease, Sébastien Hélie and Zahra Sajedinia -- Attentional deficits in Alzheimer's disease: investigating the role of acetylcholine with computational modelling, Eirini Mavritsaki, Howard Bowman, Li Su -- A computational hypothesis on how serotonin regulates catecholamines in the pathogenesis of depressive apathy, Massimo Silvetti, Gianluca Baldassarre, Daniele Caligiore -- Autism Spectrum Disorder and deep attractors in neurodynamics, Włodzisław Duch -- Part III Memory Disorders -- Alzheimer's disease: rhythms, local circuits and model-experiment interaction, Frances K Skinner, Alexandra Chatzikalymniou -- Using A Neurocomputational Autobiographical Memory Model to Study Memory Loss, Di Wang, Ahmed A. Moustafa, Ah-Hwee Tan, Chunyan Miao -- Part IV Epilepsy and Consciousness Related Disorders -- How can computer modeling help understanding the dynamics of absence epilepsy?, Piotr Suffczynski, Stiliyan Kalitzin, Fernando H. Lopes da Silva -- a-driven modeling of normal and pathological oscillations in the hippocampus, Ivan Raikov, Ivan Soltesz -- Shaping brain rhythms: dynamic and control-theoretic perspectives on periodic brain stimulation for treatment of neurological disorders, John D. Griffiths, Jérémie Lefebvre -- Brain connectivity reduction reflects disturbed self-organisation of the brain: Neural disorders and General Anesthesia -- Axel Hutt. Index.
520	3		_aSignificant progress has been made in recent years in studying the dynamics of the diseased brain at both microscopic and macroscopic levels. Electrical recordings of the diseased brain activity show (in)-coherent dynamic phenomena at scales ranging from local networks (thousands of neurons) to entire brain regions (millions of neurons). Our understanding of these spatial and temporal scales and resolutions continues to increase as evidence suggests close relationships between local field potentials recorded in the cortex (with electroencephalography or multi-unit recordings) and blood flow signals (measured with fMRI). Application of multi-scale computational models as integrative principles that bridge the single neuron dynamics (monitored with intracellular recordings) with the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI can further enhance our understanding of the diseased brain dynamics. The goal of this book is to provide a focused series of papers on computational models of brain disorders combining multiple levels and types of computation with multiple types of data in an effort to improve understanding, prediction and treatment of brain and mental illness. The volume aims to bring together physiologists and anatomists studying cortical circuits, cognitive neuroscientists studying brain dynamics and behaviour via EEG and functional magnetic resonance imaging (fMRI), and computational neuroscientists using neural modelling techniques to explore local and large-scale disordered brain dynamics. The thematic focus is expected to be appealing to a diverse group of investigators and have a high impact on the medical, neuroscience and computer science fields.
650		7	_2embne _aCerebro _xEnfermedades _9185363
700	1		_aCutsuridis, Vassilis _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030188290
776	0	8	_iPrinted edition: _z9783030188313
776	0	8	_iPrinted edition: _z9783030188320
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-18830-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b01/2020 _ek _zSI