ISBN: 9781441956750
Solid and transparent data analysis is the most important basis for reliable interpretation of experiments. The technique of parallel spike train recordings using multi-electrode arrangem… Plus…
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ISBN: 9781441956750
This is the first book to collect the relevant basic knowledge on analysis of parallel spike trains in a single source.Coverage includes the first steps of stochastic point processes (SPP… Plus…
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2010, ISBN: 9781441956750
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2010, ISBN: 9781441956750
eBooks, eBook Download (PDF), 2010, [PU: Springer US], Springer US, 2010
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2010, ISBN: 9781441956750
eBooks, eBook Download (PDF), 2010, [PU: Springer US], Springer US, 2010
| lehmanns.de Frais d'envoiDownload sofort lieferbar. (EUR 0.00) Details... |
ISBN: 9781441956750
Solid and transparent data analysis is the most important basis for reliable interpretation of experiments. The technique of parallel spike train recordings using multi-electrode arrangem… Plus…
ISBN: 9781441956750
This is the first book to collect the relevant basic knowledge on analysis of parallel spike trains in a single source.Coverage includes the first steps of stochastic point processes (SPP… Plus…
2010
ISBN: 9781441956750
eBooks, eBook Download (PDF), Auflage, [PU: Springer-Verlag], [ED: 1], Springer-Verlag, 2010
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Informations détaillées sur le livre - Analysis of Parallel Spike Trains
EAN (ISBN-13): 9781441956750
Date de parution: 2010
Editeur: Springer US
443 Pages
Langue: eng/Englisch
Livre dans la base de données depuis 2011-09-20T15:09:30+02:00 (Paris)
Page de détail modifiée en dernier sur 2024-02-22T23:35:17+01:00 (Paris)
ISBN/EAN: 9781441956750
ISBN - Autres types d'écriture:
978-1-4419-5675-0
Autres types d'écriture et termes associés:
Auteur du livre: rotter, grün, rötter
Titre du livre: trains, parallel, analysis, rat spike
Données de l'éditeur
Auteur: Sonja Grün; Stefan Rotter
Titre: Springer Series in Computational Neuroscience; Analysis of Parallel Spike Trains
Editeur: Springer; Springer US
444 Pages
Date de parution: 2010-08-18
New York; NY; US
Langue: Anglais
213,99 € (DE)
220,00 € (AT)
236,00 CHF (CH)
Available
XX, 444 p.
EA; E107; eBook; Nonbooks, PBS / Medizin/Nichtklinische Fächer; Neurowissenschaften; Verstehen; Computerassistierte Detektion; Radiologieinformationssystem; correlation; neural coding; neural ensembles; point processes; spike patterns; statistics; B; Neuroscience; Biomedical and Life Sciences; BC
Sonja Grün, born 1960, received her MSc (University of Tübingen and Max-Planck Institute for Biological Cybernetics) and PhD (University of Bochum, Weizmann Institute of Science in Rehovot) in physics (theoretical neuroscience), and her Habilitation (University of Freiburg) in neurobiology and biophysics. During her postdoc at the HebrewUniversity in Jerusalem, she performed multiple single-neuron recordings in behaving monkeys. Equipped with this experience she returned back to computational neuroscience to further develop analysis tools for multi-electrode recordings, first at the Max-Planck Institute for Brain Research in Frankfurt/Main and then as an assistant professor at the Freie Universität in Berlin associated with the local Bernstein Center for Computational Neuroscience. Since 2006 she has been unit leader for statistical neuroscience at the RIKEN Brain Science Institute in Wako-Shi, Japan. Her scientific work focuses on cooperative network dynamics relevant for brain function and behavior. Stefan Rotter, born 1961, holds a MSc in Mathematics, a PhD in Physics and a Habilitation in Biology. Since 2008, he has been Professor at the Faculty of Biology and the Bernstein Center Freiburg, a multidisciplinary research institution for Computational Neuroscience and Neurotechnology at Albert-Ludwig University Freiburg. His research is focused on the relations between structure, dynamics, and function in spiking networks of the brain. He combines neuronal network modeling and spike train analysis, often using stochastic point processes as a conceptual link.This first textbook on spike train analysis Supplies the reader with stochastic modeling tools and numerical methods. Highlights various prerequisites and pitfalls to avoid potentially wrong interpretations of data. Includes supplementary material: sn.pub/extras
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