{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T00:20:48Z","timestamp":1793838048392,"version":"4.6.1"},"reference-count":68,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T00:00:00Z","timestamp":1789344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Hum. Neurosci."],"abstract":"<jats:p>\n                    Conventional Brain-Computer Interfaces (BCIs) typically rely on sequential selection mechanisms, limiting communication speed and increasing dependence on preserved sensory or motor pathways. Semantic BCIs (sBCIs) aim to overcome this limitation by decoding concepts directly from neural activity. Owing to the continuous nature of semantic processing, progress in this domain requires a principled characterisation of the electrophysiological contrast between a so-called high-semantic state (meaningful concept retrieval) and low-semantic state (pseudo-word recognition) in scalp EEG. Here, we introduce GRASP (Game of Retrieval and Semantic Processing), a response-locked auditory paradigm involving the identification of concrete concepts from spoken sentence definitions. Our clues relate to three distinct semantic categories: body parts, foods, and musical instruments. Phonologically matched pseudo-word dummy trials preserved sentence-like auditory structure while substantially reducing recoverable lexical-semantic content, providing a controlled low-semantic reference condition. Participants were instructed to press a spacebar when they felt reasonably confident in their answer, focusing the EEG analysis on the pre-response retrieval interval. Data were captured from 13 neurologically healthy British English speakers. Preprocessed 64-channel EEG epochs were analysed using Morlet time-frequency decomposition over 2\u201335\u202fHz. Concept-minus-dummy contrast maps were computed per participant for each category and entered into a whole-scalp three-dimensional Threshold-Free Cluster Enhancement (TFCE)-based permutation analysis across channel \u00d7 frequency \u00d7 time space. All three categories produced significant TFCE-corrected effects in the pre-response interval, consistently located in the low-beta range and peaking at approximately 15\u202fHz. Meaningful concept trials showed lower low-beta power than dummy trials, with complete directional consistency across all 13 participants in all three contrasts. Body and music trial effects were strongest over centro-parietal and posterior scalp regions, whereas food showed a broader frontal-central-posterior distribution. These findings identify a robust, participant-invariant low-beta desynchronisation signature distinguishing meaningful semantic retrieval from a controlled pseudo-word baseline. The consistency of this effect across categories and participants suggests that the high-semantic\n                    <jats:italic>vs<\/jats:italic>\n                    . low-semantic boundary may provide a more cross-participant-stable electrophysiological target than fine-grained concept\n                    <jats:italic>vs<\/jats:italic>\n                    . concept discrimination, providing a principled signal-characterisation framework for future sBCI development.\n                  <\/jats:p>","DOI":"10.3389\/fnhum.2026.1913105","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T05:40:08Z","timestamp":1789364408000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["GRASP: a response-locked paradigm that reveals low-beta desynchronisation is a participant-invariant signature of semantic decoding in EEG"],"prefix":"10.3389","volume":"20","author":[{"given":"Moein","family":"Radman","sequence":"first","affiliation":[{"name":"Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex","place":["Colchester, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua James","family":"Podmore","sequence":"additional","affiliation":[{"name":"Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex","place":["Colchester, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riccardo","family":"Poli","sequence":"additional","affiliation":[{"name":"Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex","place":["Colchester, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silke","family":"Paulmann","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Essex","place":["Colchester, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian","family":"Daly","sequence":"additional","affiliation":[{"name":"Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex","place":["Colchester, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,14]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"011001","DOI":"10.1088\/1741-2552\/aaf12e","article-title":"A comprehensive review of EEG-based brain-computer interface paradigms","volume":"16","author":"Abiri","year":"2019","journal-title":"J. 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