MATLAB for Neuroscientists

An Introduction to Scientific Computing in MATLAB
2. Auflage 2013
ISBN: 978-0-12-383836-0
Verlag: Elsevier Science

Buch, Englisch, 570 Seiten, Format (B × H): 191 mm x 238 mm, Gewicht: 1274 g

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment.

This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels-advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills-will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners.

Zielgruppe

Undergraduate and graduate students in systems, cognitive, and behavioral neuroscience, cognitive psychology, and related fields, as well as researchers in these fields who use Matlab.

Autoren/Hrsg.

Wallisch, Pascal

Lusignan, Michael E

Benayoun, Marc D

Baker, Tanya I

Dickey, Adam Seth

Hatsopoulos, Nicholas G

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft
• Sozialwissenschaften Psychologie Allgemeine Psychologie Biologische Psychologie, Neuropsychologie

Inhaltsverzeichnis

PrefacePart I: FundamentalsIntroductionTutorialPart II: Data Collection with MatlabVisual Search and Pop OutAttentionPsychophysicsSignal Detection Theory Part III: Data Analysis with MatlabFrequency Analysis Part IFrequency Analysis Part II: Non-stationary Signals and SpectrogramsWaveletsConvolutionIntroduction to Phase Plane AnalysisExploring the Fitzhugh-Nagumo ModelNeural Data Analysis: EncodingPrincipal Components AnalysisInformation TheoryNeural Decoding: Discrete variablesNeural Decoding: Continuous variablesFunctional Magnetic ImagingPart IV: Data Modeling with MatlabVoltage-Gated Ion ChannelsModels of a Single NeuronModels of the RetinaSimplified Models of Spiking NeuronsFitzhugh-Nagumo Model: Traveling WavesDecision TheoryMarkov ModelModeling Spike Trains as a Poisson ProcessSynaptic TransmissionNeural Networks: Unsupervised learningNeural Network: Supervised LearningAppendicesAppendix 1: Thinking in MatlabAppendix 2: Linear Algebra Review

Über Autor(innen)

Wallisch, Pascal
Pascal Wallisch received his PhD from the University of Chicago, did postdoctoral work at the Center for Neural Science at New York University, and currently serves as a clinical assistant professor of Psychology at New York University. His research interests are at the intersection of Psychology and Neuroscience, specifically Cognitive and Computational Neuroscience. His current work focuses on motion perception, autism and the appraisal of film.