Gaia

XSLaren edukia

Neuroirudimetodo aurreratuak

Gaiari buruzko datu orokorrak

Modalitatea
Ikasgelakoa
Hizkuntza
Ingelesa

Irakasgaiaren azalpena eta testuingurua

Basis of electrophysiological signal and synchrony; Sensor-level analysis, Component analysis; Source reconstruction: Dipole modeling, Distributed approaches, Frequency-domain methods, functional and effective connectivity

Irakasleak

IzenaErakundeaKategoriaDoktoreaIrakaskuntza-profilaArloaHelbide elektronikoa
RICHTER , CRAIGBCBL- Basque Center on Cognition, Brain and LanguageBesteakDoktoreac.richter@bcbl.eu
SOTO BLANCO, DAVIDBCBL- Basque Center on Cognition, Brain and LanguageBesteakDoktoread.soto@bcbl.eu

Gaitasunak

IzenaPisua
CE1. Adquisición de conocimientos avanzados sobre métodos de investigación avanzados en electrofisiología50.0 %
CE2. Aplicar los conocimientos adquiridos de forma creativa para identificar problemas y plantear analisis de datos con las técnicas de electroencefalografía y magnetoencefalografía.50.0 %

Irakaskuntza motak

MotaIkasgelako orduakIkasgelaz kanpoko orduakOrduak guztira
Magistrala101020
Laborategiko p.101020
Ordenagailuko p.102535

Ebaluazio-sistemak

IzenaGutxieneko ponderazioaGehieneko ponderazioa
Bertaratzea eta Parte-hartzea20.0 % 20.0 %
Lanak proiektuak80.0 % 80.0 %

Irakasgai-zerrenda

This course will introduce the fundamental methods for the analysis of functional MRI, and electrophysiological (i.e. EEG and MEG) data.

The goal is to provide the students with the core ideas necessary to understand current data analysis methods used in the literature from a critical point of view, and provide sufficient hands-on experience on relevant software packages that implement them. The course is divided into three sections. The first part will consist of hands-on sessions covering the essentials of MRI data processing, using a standard neuroimaging software packages. There will be practical sessions on the analysis of electrophysiological data, mainly using BrainVision Analyzer and EEGlab.

In addition, the course will describe the basic theoretical background of the most common methods for analysis of functional MRI data, such as the general linear model and independent component analysis, the main software packages (AFNI, FSL), also with an introduction to multivariate pattern analyses (MVPA).



Bibliografia

Nahitaez erabili beharreko materiala

- FSL (see http://fsl.fmrib.ox.ac.uk/fslcourse), AFNI, Brain Vision Analyzer 2. User Manual - User Manual of EEGLab (http://sccn.ucsd.edu/eeglab/) - Statistical Parametric Mapping: The analysis of functional brain images. Edited by K. J. Friston, J.T. Ashburner, S. J. Kiebel, T. E. Nichols and W.E. Penny. Elsevier 2008. - Statistical analysis of fMRI data. F. G. Ashby. MIT Press 2011. - Handbook of functional MRI data analysis. R.A. Poldrack, J. A. Mumford and T.E. Nichols. Cambridge University Press 2011.

Oinarrizko bibliografia

Hansen, P.C., et al. MEG: An Introduction to Methods (selected chapters)

Friston, K. J. et al. Statistical Parametric Mapping, The Analysis of Functional Brain Images (selected chapters)



XSLaren edukia

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