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What this survey is about

How researchers in psychology, neuroscience, and cognitive science process and analyze EEG data. Estimated completion time: about 15 minutes. Your responses are anonymous and will be used only in aggregate.

Two terms used throughout

Generative AI assistant: a general-purpose model or coding assistant used to support your work but not embedded in the signal itself, e.g. ChatGPT, Claude, or Gemini for explanation or drafting; GitHub Copilot, Claude Code, or Cursor for writing analysis code; Perplexity, Consensus, or Elicit for literature and method search.

Automated or machine-learning analysis method: an algorithm that operates on the EEG data as part of the analysis, e.g. ICLabel for component classification, Autoreject or ASR for artifact handling, or EEGNet and related networks for decoding.

EEG processing refers to the steps that convert raw recordings into analyzable measures: import and montaging, filtering, bad-channel handling, re-referencing, artifact correction, epoching, baseline correction, time-frequency decomposition, source estimation, and the associated quality-control and statistical procedures.

Background references

Pernet, C.R., Appelhoff, S., Gorgolewski, K.J. et al. EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Sci Data 6, 103 (2019). https://doi.org/10.1038/s41597-019-0104-8
Delorme, A. EEG is better left alone. Sci Rep 13, 2372 (2023). https://doi.org/10.1038/s41598-023-27528-0

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