Statistical testing framework for brain dynamics: GLHMM statistical protocols

All the data is part of the paper A comprehensive framework for statistical testing of brain dynamics . The full set of Jupyter Notebooks and supporting materials can be found in the associated GitHub repository:
https://github.com/Nick7900/glhmm_protocols

In Protocol 1 (Across-subjects), we analyse resting-state brain activity from 1,001 Human Connectome Project (HCP) participants across four sessions to examine its relationship to 15 traits related to cognitive performance. There will not be any other data besides the Exchangeable Block (EB) file used to account for family relationships between subjects.

In Procedure 2 (Across-trials), we study MEG data from a single person who participated in 15 sessions. During each session, the person watched both animate and inanimate objects while their brain activity in the occipital lobe was recorded. This analysis assesses differences in the brain responses when the person looks at animate objects compared to inanimate ones.

In Procedure 3 (Across-sessions-within-subject), we use the same dataset as in Procedure 2, but this time focus on changes over multiple sessions. This analysis shows whether the person exhibits changes in stimulus processing over time (i.e. across sessions) due for example, to learning, or if their brain representations remain stable.

In Procedure 4 (Across-state-visits), we analyse MEG data from 10 subjects scanned at rest in a dark room. During the scans, pupil size and brain activity were measured concurrently. Nine subjects completed two sessions, and one completed a single session. This analysis explores how changes in brain states, like the default mode network, relate to variations in pupil size