Statistical Parametric Mapping (SPM)

Preprocess fMRI data (realignment, normalization, smoothing).

Define a GLM with regressors for different motor task conditions.

Estimate the model parameters and conduct statistical inference.

Visualize the activation maps to identify brain regions involved in the motor task.

Preprocess PET data (realignment, normalization, smoothing).

Define a GLM with regressors for drug and placebo conditions.

Estimate the model parameters and conduct statistical inference.

Compare the metabolic activity between the drug and placebo groups.

Preprocess EEG data (artifact removal, filtering).

Perform source localization analysis using SPM's EEG module.

Identify the brain region where the seizures originate.

Visualize the source localization results.

Preprocess MEG data (artifact removal, filtering).

Perform time-frequency analysis using SPM's MEG module.

Identify the brain regions and frequency bands involved in the cognitive task.

Visualize the time-frequency results.

Preprocess resting-state fMRI data (realignment, normalization, smoothing).

Perform seed-based correlation analysis or independent component analysis (ICA).

Identify brain networks that are functionally connected.

Visualize the network connectivity results.