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Comput. Eng."],"published-print":{"date-parts":[[2025,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This work introduces a neuromorphic compression based neural sensing architecture with address-event representation inspired readout protocol for massively parallel, next-gen wireless implantable brain machine interface (iBMI). The architectural trade-offs and implications of the proposed method are quantitatively analyzed in terms of compression ratio (CR) and spike information preservation. For the latter, we used metrics such as root-mean-square error and correlation coefficient (CC) between the original and recovered signals to assess the effect of neuromorphic compression on the spike shape. Furthermore, we use accuracy, sensitivity, and false detection rate to understand the effect of compression on downstream iBMI tasks, specifically, spike detection. We demonstrate that a data CR of 15\u2013265 per channel can be achieved by transmitting address-event pulses for two different biological datasets. The CR further increases to 200\u2013<jats:inline-formula>\n                     <jats:tex-math\/>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                           <mml:mn>50<\/mml:mn>\n                           <mml:mrow>\n                              <mml:mi mathvariant=\"normal\">K<\/mml:mi>\n                           <\/mml:mrow>\n                        <\/mml:mrow>\n                     <\/mml:math>\n                  <\/jats:inline-formula> per channel, 50\u2009\u00d7 more than in prior works, by the selective transmission of event pulses corresponding to neural spikes. A CC of \u22480.9 and spike detection accuracy of over 90% were obtained for the worst-case analysis involving <jats:inline-formula>\n                     <jats:tex-math\/>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                           <mml:mn>10<\/mml:mn>\n                           <mml:mrow>\n                              <mml:mi mathvariant=\"normal\">K<\/mml:mi>\n                           <\/mml:mrow>\n                        <\/mml:mrow>\n                     <\/mml:math>\n                  <\/jats:inline-formula>-channel simulated recording and typical analysis using 100 or 384-channel real neural recordings. We also analyzed the collision handling capability for up to 10K channels and observed no significant error, indicating the scalability of the proposed pipeline. We also present initial results to show the ability of intention decoders to work directly on the events generated by the neuromorphic front-end.<\/jats:p>","DOI":"10.1088\/2634-4386\/adad10","type":"journal-article","created":{"date-parts":[[2025,1,22]],"date-time":"2025-01-22T22:52:23Z","timestamp":1737586343000},"page":"014004","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Towards neuromorphic compression based neural sensing for next-generation wireless implantable brain machine interface"],"prefix":"10.1088","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0248-6417","authenticated-orcid":true,"given":"Vivek","family":"Mohan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1543-195X","authenticated-orcid":false,"given":"Wee Peng","family":"Tay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1035-8770","authenticated-orcid":false,"given":"Arindam","family":"Basu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,1,31]]},"reference":[{"key":"nceadad10bib1","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.cell.2020.04.033","article-title":"Dynamic stimulation of visual cortex produces form vision in sighted and blind humans","volume":"181","author":"Beauchamp","year":"2020","journal-title":"Cell"},{"key":"nceadad10bib2","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1038\/s41586-023-06377-x","article-title":"A high-performance speech neuroprosthesis","volume":"620","author":"Willett","year":"2023","journal-title":"Nature"},{"key":"nceadad10bib3","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1126\/science.abd0380","article-title":"A brain-computer interface that evokes tactile sensations improves robotic arm control","volume":"372","author":"Flesher","year":"2021","journal-title":"Science"},{"key":"nceadad10bib4","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1038\/s41551-023-01021-5","article-title":"Translational opportunities and challenges of invasive electrodes for neural interfaces","volume":"7","author":"Shen","year":"2023","journal-title":"Nat. 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