Investigating Outcome Prediction and Rehabilitation from childhood stroke via the use of EEG brain connectivity assessments

| In Development | Observational | Single Site | Kartik Iyer, Michaela Waak & Karen Barlow |

Predicting clinical recovery in childhood stroke is highly challenging due to the complex nature of injury. Outcomes in these children remain unclear until months after the injury. This research project seeks to improve prediction of clinical recovery in childhood stroke by establishing an emerging, innovative approach known as brain connectivity. Brain connectivity enables us to view and characterize brain function as a network of connections. It is an objective, analytic metric that quantifies the strength of communication arising from various regions to measure how efficiently our brain is optimizing information exchange and maintaining reliable, “neuroplastic” connections. These network connections are significantly damaged following a stroke, and assessing brain connectivity in childhood stroke may inform on the rate of repair of damaged brain connections during recovery. Brain connectivity assessments could offer a timely approach for clinicians in predicting individual recovery and developing early intervention strategies that can improve rehabilitation outcomes.

Brain connectivity can be measured via EEG data at the bedside. EEG now offers more than the assessment of seizure and encephalopathy, but also the ability to measure changes in brain connectivity cost effectively during both acute and chronic stages of recovery. It therefore has the potential to provide important indicators whole-brain reorganization, repair and recovery, and response to rehabilitation strategies. Thus, this could lead to potentially personalizing neurorehabilitation pathways in the future.

Keyword(s): childhood stroke, EEG, brain connectivity, rehabilitation, outcomes

Are you seeking other sites to participate in research study: Yes

If seeking other sites, can international sites participate: Yes

Given that childhood strokes can lead to highly variable injury type and outcomes, this project would benefit from multi-site contributors to collate large EEG datasets in which groups can be further stratified and analyzed.

If potential contributors are interested please email us at: or Kartik Iyer at

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