ContextLab / ContextLab/supereeg

predict best locations

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Dominant language
Python
Stars
38
Forks
19
PR merge metrics
No merged PRs in 30d

Description

Use resting state matrix to create synthetic data, parcellate by region (like Bassett paper), and predict values based on many random samples of n electrodes. Average predicted correlations in regions and across samples to generate a 'best electrode configuration' map.

Contributor guide

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Research direction

Start by locating the resting-state matrix, synthetic-data generation, regional parcellation, and electrode-prediction entry points. Clarify the expected inputs, number of sampled electrodes, regional correlation aggregation, and output format; done means producing and validating a best-electrode-configuration map.

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Assessment

Tech stack
python
Domain
data, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
25/100

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