Materials associated to the the classes given during the master's degree in MATHÉMATIQUES, VISION, APPRENTISSAGE (MVA) - [Functional imaging and BCI](https://www.master-mva.com/cours/imagerie-fonctionnelle-cerebrale-et-interface-cerveau-machine/ - ENS Saclay - Jan-Feb 2024.

To install the packages used in the different notebooks, please do:

pip install -r requirements.txt

• Lesson 1 - M/EEG data: where it all begins! - 18/01 – 9:30-12:30AM

• Lesson 2 - Estimating the sources of M/EEG activity – w/ Théo Papadopoulo (Inria, Sophia-Antipolis) - 25/01 – 9:30-12:30AM

• Lessson 3 - How to further explore M/EEG data to answer scientific questions? – 01/02 – 9:30-12:30AM

• Lesson 4 - How to use real-time M/EEG data for clinical purpose? – 08/02 – 9:30-12:30AM @ Paris Brain Institute! (+visit of the neuroimaging platform)

• Hämäläinen et al, 1993, Reviews of Modern Physics - Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain
• Gross et al, 2013, NeuroImage - Good practices in MEG research
• Puce et Hämäläinen, 2017, Brain Sciences - A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies
• Hari et al, 2018, Clinical Neurophysiology - IFCN-endorsed practical guidelines for clinical magnetoencephalography

• He et al, 2019, IEEE Transactions on Biomedical Engineering - Electrophysiological Brain Connectivity: Theory and Implementation
• Bastos & Schoffelen, 2016, Frontiers in Systems Neuroscience - A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls
• De Vico Fallani et al, , 2014, Philos Trans R Soc Lond B Biol Sci. - Graph analysis of functional brain networks: practical issues in translational neuroscience
• Fornito & Zalesky, 2017 - Fundamentals of Brain Network Analysis
• Boccaletti et al, 2006, Physics Reports - Complex networks: Structure and dynamics
• Rubinov & Sporns, 2010, NeuroImage - Complex network measures of brain connectivity: Uses and interpretations
• Pernet et al, 2015, Journal of Neuroscience Methods - Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study

• McFarland & Wolpaw, 2011, Commun. ACM - Brain-Computer Interfaces for Communication and Control
• McFarland & Vaughan, 2016, Progress in brain research - BCI in practice
• Thompson, 2018, Science and Engineering Ethics - Critiquing the Concept of BCI Illiteracy
• Lotte et al, 2018, JNE - review of classification algorithms used in BCI
• Gonzalez-Astudillo et al, 2020, JNE - review of network-based features in BCI

• OpenViBE - Inria software to perform online experiments
• MOABB - Python package to work with open datasets in order to compare classification pipelines and their replicability
• scikit-learn - Python package to build classification pipelines

• BCI society - international society dedicated to BCI research
• Cybathlons - competitions to promote BCI and to test the finest algorithms with end users!
• CORTICO - French society to promote BCI research