ArticleJournal of neuroscience methods2025
ER-detect: A pipeline for robust detection of early evoked responses in BIDS-iEEG electrical stimulation data.
Article in Journal of neuroscience methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methodologies to detect cortico-cortical evoked potentials: a systematic review.Frontiers in human neuroscience · 2025Pooled it
- Adaptive neuromodulation dialogues: navigating current challenges and emerging innovations in neuromodulation system development.Journal of neural engineering · 2025Review
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10 authors.
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Abstract
backgroundHuman brain connectivity can be measured in different ways. Intracranial EEG (iEEG) measurements during single pulse electrical stimulation provide a unique way to assess the spread of electrical information with millisecond precision. However, the methods used for the detection of responses in cortico-cortical evoked potential (CCEP) data vary across studies, from visual inspection with manual annotation to a variety of automated methods. NEW
methodTo provide a robust workflow to process CCEP data and detect early evoked responses in a fully automated and reproducible fashion, we developed the Early Response (ER)-detect toolbox. ER-detect is an open-source Python package and Docker application to preprocess BIDS structured iEEG data and detect early evoked CCEP responses. ER-detect can use three early response detection methods, which were validated against 14 manually annotated CCEP datasets from two different clinical sites by four independent raters. RESULTS AND COMPARISON WITH EXISTING
methodsER-detect's automated detection performed on par with the inter-rater reliability (Cohen's Kappa of ∼0.6). Moreover, ER-detect was optimized for processing large CCEP datasets, to be used in conjunction with other connectomic investigations.
conclusionER-detect provides a highly efficient standardized workflow such that iEEG-BIDS data can be processed in a consistent manner and enhance the reproducibility of CCEP based connectivity results for both research and clinical purposes.
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