Brainstorm

Import patient's MEG/EEG data into Brainstorm.

Preprocess the data by filtering and removing artifacts.

Perform source modeling to estimate the location of seizure activity.

Visualize the source activity on the patient's MRI.

Identify the seizure onset zone based on the spatiotemporal patterns of activity.

Import EEG data recorded during a working memory task.

Perform time-frequency analysis to examine oscillatory activity.

Identify frequency bands associated with working memory processes.

Assess functional connectivity between brain regions involved in working memory.

Statistically compare activity patterns across different task conditions.

Record EEG data while the subject performs motor imagery tasks.

Extract relevant features from the EEG signals.

Train a machine learning classifier to discriminate between different motor intentions.

Test the classifier's performance on new EEG data.

Implement the classifier in a real-time BCI system.

Import overnight EEG recordings.

Preprocess the data by filtering and artifact removal.

Perform automatic sleep stage scoring using established criteria.

Review and correct the automatic scoring manually.

Analyze the sleep architecture and identify any abnormalities.

Record EEG data before, during, and after TMS.

Preprocess the data by removing TMS artifacts.

Perform time-frequency analysis to examine changes in oscillatory activity.

Assess changes in functional connectivity between brain regions.

Correlate the changes in brain activity with behavioral outcomes.