{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T21:03:51Z","timestamp":1768511031411,"version":"3.49.0"},"posted":{"date-parts":[[2024,3,29]]},"group-title":"Neuroscience","reference-count":68,"publisher":"openRxiv","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,3,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Identifying biomarkers that predict substance use disorder (SUD) propensity may better strategize anti-addiction treatment. The melanin-concentrating hormone (MCH) neurons in the lateral hypothalamus (LH) critically mediates interactions between sleep and substance use; however, their activities are largely obscured in surface electroencephalogram (EEG) measures, hindering the development of biomarkers.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    Surface EEG signals and real-time Ca\n                    <jats:sup>2+<\/jats:sup>\n                    activities of LH MCH neurons (Ca\n                    <jats:sup>2+<\/jats:sup>\n                    <jats:sub>MCH<\/jats:sub>\n                    ) were simultaneously recorded in male and female adult rats. Mathematical modeling and machine learning were then applied to predict Ca\n                    <jats:sup>2+<\/jats:sup>\n                    <jats:sub>MCH<\/jats:sub>\n                    using EEG derivatives. The robustness of the predictions was tested across sex and treatment conditions. Finally, features extracted from the EEG-predicted Ca\n                    <jats:sup>2+<\/jats:sup>\n                    <jats:sub>MCH<\/jats:sub>\n                    either before or after cocaine experience were used to predict future drug-seeking behaviors.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    An EEG waveform derivative \u2013 a modified theta-to-delta ratio (EEG Ratio) \u2013 accurately tracks real-time Ca\n                    <jats:sup>2+<\/jats:sup>\n                    <jats:sub>MCH<\/jats:sub>\n                    in rats. The prediction was robust during rapid eye movement sleep (REMS), persisted through REMS manipulations, wakefulness, circadian phases, and was consistent across sex. Moreover, cocaine self-administration and long-term withdrawal altered EEG Ratio suggesting shortening and circadian redistribution of synchronous MCH neuron activities. In addition, features of EEG Ratio indicative of prolonged synchronous MCH neuron activities predicted lower subsequent cocaine seeking. EEG Ratio also exhibited advantages over conventional REMS measures for the predictions.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>\n                    The identified EEG Ratio may serve as a non-invasive measure for assessing MCH neuron activities\n                    <jats:italic>in vivo<\/jats:italic>\n                    and evaluating REMS; it may also serve as a potential biomarker predicting drug use propensity.\n                  <\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2024.03.27.586887","type":"posted-content","created":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T18:50:13Z","timestamp":1711738213000},"source":"Crossref","is-referenced-by-count":0,"title":["An EEG Signature of MCH Neuron Activities Predicts Cocaine Seeking"],"prefix":"10.64898","author":[{"given":"Yao","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danyang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph","family":"Widjaja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongzhen","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sahin","family":"Ozsoy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giancarlo","family":"Allocca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jidong","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5447-1014","authenticated-orcid":false,"given":"George C.","family":"Tseng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengcheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1770-0196","authenticated-orcid":false,"given":"Yanhua H.","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2024040209351478000_2024.03.27.586887v1.1","first-page":"415","article-title":": Precision in Addiction Care: Does It Make a Difference?","volume":"88","year":"2015","journal-title":"Yale J Biol Med"},{"key":"2024040209351478000_2024.03.27.586887v1.2","unstructured":"Collins FS , Brown MK (2021): National Institutes of Health Sleep Research Plan. 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