typos and stats added

README.md

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 ## Neuroimaging and Machine Learning for Biomedicine
 This is a repository containing seminars and lecture materials for the Skoltech course on Machine Learning in Neuroimaging data, Fall 2020.
 
-Course by NeuroML ADASE lab: http://adase.group/neuro/ 
+Course by NeuroML ADASE lab: http://adase.group/neuro/
 
 ## Course description:
 This course is specifically aimed at MSc and PhD students with basic knowledge of Machine Learning techniques pursuing further growth in neuroimaging data analysis, either in clinical practice or in neuroscience research. The course will provide you with training in the aspects of human neuroimaging methods, data properties and applied Machine Learning techniques. The course is focused on brain biophysics, scanning techniques and methods of data analysis. Students will develop a broad set of skills that are essential to study brain function, brain pathology and solve biomedical tasks with state-of-the-art Machine Learning and Computer Vision techniques.​
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 ### The list of the current seminars published (will be updated with time):
 * SEMINAR 0 (04.09) BASH for Engeneering pipelines, CometML
  * Before seminar you are to install Docker https://www.docker.com/
-* SEMINAR 1 (04.09) EEG analysis, Machine Learning in EEG
-* SEMINAR 2 (04.09) MRI data analysis, sources, databases, tools 
+* SEMINAR 1 (07.09, 11.09) EEG analysis, Machine Learning in EEG
+* SEMINAR 2 (14.09) MRI data analysis, sources, databases, tools 
   * Before seminar, please, do the following:
     1) Install Docker https://docs.docker.com/get-docker/
     2) Download `data` folder from link https://drive.google.com/drive/folders/12FAfkKwGVsz0nYjkodvXMLtqtoWlEtIq?usp=sharing
@@ -29,14 +29,16 @@ This course is specifically aimed at MSc and PhD students with basic knowledge o
 * SEMINAR 4 (04.09) fMRI data preprocessing, analysis, GLM
 * SEMINAR 5 (04.09) Functional connectivity analysis and Machine Learning modelling
 * SEMINAR 6 (04.09) Deep Learning models and fMRI data analysis
-* SEMINAR 7 (04.09) Advanced topics: ML engeneering pipelines, domain adaptation, brain visualization 
+* SEMINAR 7 (04.09) Advanced topics: ML engeneering pipelines, domain adaptation, brain visualization
 
 #### Datasets used (please get a personal account and complete data use agreement):
 * Human Connectome Project https://db.humanconnectome.org/data/projects/HCP_1200
 * UCLA Consortium for Neuropsychiatric Phenomics LA5c Study https://openneuro.org/datasets/ds000030/versions/1.0.0
 * Autism Brain Imaging Data Exchange http://fcon_1000.projects.nitrc.org/indi/abide/
+* EEG Motor Movement/Imagery Dataset https://www.physionet.org/content/eegmmidb/1.0.0/
 
 #### Software used (please get a personal account and complete usage agreement):
 * FreeSurfer https://surfer.nmr.mgh.harvard.edu/
 * FmriPrep https://fmriprep.org/en/stable/
 * Docker https://www.docker.com/
+* MNE python library https://mne.tools/stable/index.html