{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T09:22:19Z","timestamp":1771406539778,"version":"3.50.1"},"posted":{"date-parts":[[2025,9,14]]},"group-title":"Ophthalmology","reference-count":21,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,9,14]],"date-time":"2025-09-14T00:00:00Z","timestamp":1757808000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,2,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>To evaluate the feasibility of detecting single-trial cortical responses to individual microperimetry (MP) stimuli using electroencephalography (EEG) under non-ideal synchronization conditions, and to explore EEG-based stimulus registration independent of patient responses.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>This proof-of-concept study acquired EEG data from two healthy participants (12 trials) during MP testing using low- and high-intensity single-flash stimuli. Occipital EEG signals were recorded with an 8-channel portable system, band-pass filtered (4\u201349 Hz), normalized, and segmented into 600-ms epochs time-locked to MP stimuli using offline synchronization, resulting in an estimated temporal uncertainty of \u223c250 ms. A bidirectional long short-term memory (BiLSTM) deep learning model classified stimulus-present versus stimulus-absent EEG segments. Performance was assessed using accuracy, sensitivity, specificity, and F1-score, with emphasis on feasibility rather than generalizability.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Across trials, EEG-based classification performance exceeded chance levels. For high-intensity stimuli, detection accuracy approached 80%, while low-intensity stimuli demonstrated greater inter-trial variability. Occipital electrode configurations consistently outperformed parietal or combined montages, consistent with visual cortex neuroanatomy. Despite the absence of hardware-level synchronization and single-trial analysis, detectable neural signatures of isolated MP flashes were observed.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>These findings demonstrate the feasibility of detecting single-flash MP stimuli from occipital EEG using deep learning, even under constrained acquisition conditions. While not intended for immediate clinical deployment, this work motivates future studies incorporating precise synchronization, optimized stimulus designs, and larger cohorts to evaluate EEG-augmented microperimetry as a potential objective adjunct to subjective functional testing.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Highlights<\/jats:title>\n                  <jats:list list-type=\"bullet\">\n                    <jats:list-item>\n                      <jats:p>EEG detects single-flash microperimetry stimuli without hardware-level synchronization<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Occipital EEG channels enable stimulus detection independent of patient responses<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>BiLSTM deep learning decodes non-repetitive, long-duration microperimetry flashes<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Detection accuracy approaches 80% for high-intensity microperimetry stimuli<\/jats:p>\n                    <\/jats:list-item>\n                  <\/jats:list>\n                <\/jats:sec>","DOI":"10.1101\/2025.09.12.25335536","type":"posted-content","created":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T02:50:14Z","timestamp":1757904614000},"source":"Crossref","is-referenced-by-count":0,"title":["Feasibility of Electroencephalography-Based Detection of Single-Flash Microperimetry Stimuli: A Proof-of-Concept Study"],"prefix":"10.64898","author":[{"given":"Muhammad Najam","family":"Dar","sequence":"first","affiliation":[{"name":"Research Affiliate, Byers Eye Institute, Stanford University, CA, USA"},{"name":"Senior Data Scientist, Ocular Imaging Research and Reading Center, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio Neto Severo","family":"de Castro","sequence":"additional","affiliation":[{"name":"Research Affiliate, Byers Eye Institute, Stanford University, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zoha Zahid","family":"Fazal","sequence":"additional","affiliation":[{"name":"Visiting Instructor, Byers Eye Institute, Stanford University, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kholood","family":"Janjua","sequence":"additional","affiliation":[{"name":"Visiting Instructor, Byers Eye Institute, Stanford University, CA, USA"},{"name":"Doctoral Candidate, Department of Biomedical Engineering and Sciences, National University of Sciences and Technology, Islamabad, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed Abdul Saqhlain","family":"Shaik","sequence":"additional","affiliation":[{"name":"Data Scientist, Byers Eye Institute, Stanford University, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tehmina","family":"Sheharyar","sequence":"additional","affiliation":[{"name":"Visiting Instructor, Byers Eye Institute, Stanford University, CA, USA"},{"name":"Lecturer, Mirpur University of Science and Technology, Mirpur, AJK, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed Ibrahim","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Executive Director, Ocular Imaging Research and Reading Center, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasir Jamal","family":"Sepah","sequence":"additional","affiliation":[{"name":"Assistant Professor, Byers Eye Institute, Stanford University, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026021800451508000_2025.09.12.25335536v2.1","doi-asserted-by":"publisher","DOI":"10.1159\/000515148"},{"key":"2026021800451508000_2025.09.12.25335536v2.2","doi-asserted-by":"publisher","DOI":"10.1167\/tvst.12.7.11"},{"key":"2026021800451508000_2025.09.12.25335536v2.3","doi-asserted-by":"publisher","DOI":"10.1016\/j.survophthal.2019.01.014"},{"key":"2026021800451508000_2025.09.12.25335536v2.4","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-51539-0"},{"key":"2026021800451508000_2025.09.12.25335536v2.5","doi-asserted-by":"publisher","DOI":"10.1167\/tvst.12.5.21"},{"key":"2026021800451508000_2025.09.12.25335536v2.6","doi-asserted-by":"publisher","DOI":"10.1016\/j.preteyeres.2020.100907"},{"key":"2026021800451508000_2025.09.12.25335536v2.7","unstructured":"Microperimetry in Children\u2019s Practice | Khubieva | Ophthalmology in Russia. 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