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Updated: Jan 21, 2026
06:50
Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
Published on: October 30, 2018
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Characterising neural plasticity at the single patient level using connectivity fingerprints
Natalie L Voets1, Oiwi Parker Jones2, Rogier B Mars3
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neurosurgery, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK.
Neuroimage. Clinical
|July 30, 2019
Summary
Brain tumor patients exhibit unique functional connectivity "fingerprints" revealing neuroplasticity. This method quantifies individual brain network changes, aiding personalized treatment strategies for brain injury and tumors.
Area of Science:
- Neuroscience
- Medical Imaging
- Brain Plasticity
Background:
- Neuroplasticity after brain injury offers treatment potential.
- Quantifying individual brain reorganization is difficult with population-based methods.
- Brain tumors can impact language networks, necessitating individual assessment.
Purpose of the Study:
- To develop and validate a method for quantifying individual brain functional reorganization.
- To identify biomarkers for personalized treatment in patients with brain tumors.
- To investigate how tumor characteristics influence brain network alterations.
Main Methods:
- Acquired functional MRI scans during a verbal fluency task in 44 brain tumor patients and 23 healthy controls.
- Applied a novel approach to characterize normal functional connectivity patterns in controls.
- Statistically quantified individual deviations from normal connectivity and analyzed influencing factors.
Main Results:
- Functional connectivity "fingerprints" revealed individual brain plasticity not seen in standard analyses.
- Patients with language-dominant hemisphere tumors showed highly variable, individual-specific fingerprints.
- Tumor grade and location significantly influenced atypical connectivity patterns.
Conclusions:
- Connectivity fingerprints offer a statistical metric for individually-specific brain network organization.
- This approach enables quantification and monitoring of behaviorally-relevant adaptations.
- Findings support the use of connectivity fingerprints for personalized neuro-oncology and rehabilitation.
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