J3 · University of Sharjah · 2026
Brain networks under sensory challenge
EEG functional connectivity in forward head posture across changes in vision and support-surface stability.
- Status
- In progress
- Role
- Data analyst
- Signals
- EEG · 19 channels · Nexus
- Methods
- wPLI · graph metrics
At a glance
Research question
When vision and support-surface stability change, do people with forward head posture recruit different brain networks to stay balanced?
My role
I was the data analyst on the study, part of the same research programme as J2.
- Acquisition and preprocessing. 19-channel EEG recorded on a Nexus system, segmented by balance condition.
- Connectivity. Weighted phase lag index (wPLI) between every pair of channels, per frequency band.
- Network analysis. Graph metrics from each connectivity matrix, compared between groups and across conditions.
Method
- Raw EEG
- Preprocessing
- 1-s epochs
- wPLI
- 19×19 matrix
- Graph metrics
wPLI measures how consistently two channels keep a phase lead or lag, while discounting zero-lag coupling that volume conduction can produce. Each participant and condition gives a 19 × 19 matrix per band (theta, alpha and beta), summarised as mean wPLI, clustering, global efficiency and local efficiency.
Interpretation
Effects on global efficiency disappeared after adjusting for mean wPLI, so they reflect overall connectivity strength, not a change in network topology independent of it.
This study is still in progress. The full results and figures will be added here when it is complete.
What I learned
Connectivity analysis has a thousand knobs: the metric, the band, the reference, the threshold. Every one of them can manufacture a network. The discipline is deciding them before you look, and checking that an effect survives reasonable alternatives, including adjusting for overall connectivity strength.