{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:21:10Z","timestamp":1785435670061,"version":"3.56.0"},"posted":{"date-parts":[[2022,8,3]]},"group-title":"Neuroscience","reference-count":64,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T00:00:00Z","timestamp":1659484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.biorxiv.org\/about\/FAQ#license"}],"funder":[{"name":"NIH","award":["T32DA024635"],"award-info":[{"award-number":["T32DA024635"]}]},{"name":"National Science Foundation","award":["Chemical, Bioengineering, Environmental, and Transport Systems Grant 1263785"],"award-info":[{"award-number":["Chemical, Bioengineering, Environmental, and Transport Systems Grant 1263785"]}]},{"name":"Republic of Korea Ministry of Science Information and Communications Technology \/ National Research Foundation","award":["Brain Pool Fellow Program Grant #2021H1D3A2A02082997"],"award-info":[{"award-number":["Brain Pool Fellow Program Grant #2021H1D3A2A02082997"]}]},{"DOI":"10.13039\/501100003693","name":"The Korea Institute of Science and Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003693","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/052csg198","id-type":"ROR","asserted-by":"publisher"}]},{"name":"McKnight Technical Innovations in Neuroscience Award"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,7,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Self-organized criticality is a hallmark of complex dynamic systems at phase transitions. Systems that operate at or near criticality have large-scale fluctuations or \u201cavalanches\u201d, the frequency and duration power of which are best fit with a power law revealing them to be scale-free and fractal, and such power laws are ubiquitous. It is an attractive concept in neuroscience since spiking avalanches are exhibited by neural tissue, and may underpin how minuscule events could scale up to circuits and provide adaptive psychobiological function. Much is yet to be understood about criticality\n                  <jats:italic>in vivo<\/jats:italic>\n                  in the healthy brain and in disorders such as addiction, as drugs may alter the critical state\u2019s \u201ctuning\u201d to generate drug seeking and dysphoria. Thus, here a novel toolset was developed to use neural avalanches and their self-similarity, rather than power law fit slope exponents as is canonically done, to quantify criticality in a previously collected high-density electrophysiological\n                  <jats:italic>in vivo<\/jats:italic>\n                  corticostriatal dataset from a mouse model of early cocaine abstinence. During behavioral quiescence, in the prefrontal cortex but not ventral striatum of cocaine-dosed mice, it was found that critical tuning is enhanced compared to drug-free controls. Additionally, an empirical biological demonstration of complexity\u2019s theoretical correlation to criticality was shown in drug-free mice, was exponentially enhanced in drug-treated cortex, but was absent in the drug-treated striatum. As shown, quantifying criticality grants experimental support for the \u201ccritical brain hypothesis\u201d and allows for statistical interpretation of inter-subject variability and development of further testable hypotheses in systems neuroscience.\n                <\/jats:p>\n                <jats:sec>\n                  <jats:title>Significance Statement<\/jats:title>\n                  <jats:p>\n                    The \u201ccritical brain hypothesis\u201d asserts neural networks are comparable to material in phase transitions at a critical point, their \u201cavalanches\u201d of system-wide spike bursts best seen in log-log plots of probability vs. avalanche size or duration, with slope following a scale-free or fractal power law. In discussing criticality, \u201ccritical tuning\u201d is mentioned but quantification thereof left for later experimentation, despite being necessary for a scientific hypothesis. Presented are methods to quantify critical tuning through assessing similarity or fractalness among corticostriatal avalanches collected using high-density electrophysiology in cocaine-conditioned mice, along with an empirical\n                    <jats:italic>in vivo<\/jats:italic>\n                    confirmation of the mathematical concept that data complexity correlates with criticality. Interestingly, cocaine enhances critical tuning in cortex and aberrantly modifies complexity in a region-specific manner.\n                  <\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2022.08.02.501652","type":"posted-content","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T16:25:13Z","timestamp":1659543913000},"source":"Crossref","is-referenced-by-count":2,"title":["In vivo Quantification of Neural Criticality and Complexity in Mouse Cortex and Striatum in a Model of Cocaine Abstinence"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7361-7760","authenticated-orcid":false,"given":"Wesley C.","family":"Smith","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2025073001350469000_2022.08.02.501652v3.1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1195870"},{"key":"2025073001350469000_2022.08.02.501652v3.2","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2010.01.003"},{"key":"2025073001350469000_2022.08.02.501652v3.3","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2017.07.002"},{"key":"2025073001350469000_2022.08.02.501652v3.4","first-page":"163","article-title":"Being critical of criticality in the brain","volume":"3","year":"2012","journal-title":"Frontiers in physiology"},{"key":"2025073001350469000_2022.08.02.501652v3.5","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1216855110"},{"key":"2025073001350469000_2022.08.02.501652v3.6","first-page":"166","article-title":"Self-organized criticality as a fundamental property of neural systems","volume":"8","year":"2014","journal-title":"Frontiers in systems neuroscience"},{"issue":"2","key":"2025073001350469000_2022.08.02.501652v3.7","doi-asserted-by":"crossref","first-page":"e1004698","DOI":"10.1371\/journal.pcbi.1004698","article-title":"Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network","volume":"12","year":"2016","journal-title":"PLoS computational biology"},{"key":"2025073001350469000_2022.08.02.501652v3.8","doi-asserted-by":"publisher","DOI":"10.1038\/35065675"},{"key":"2025073001350469000_2022.08.02.501652v3.9","doi-asserted-by":"crossref","unstructured":"Markovic D & Gros C (2013) Power laws and Self-Organized Criticality in Theory and Nature.","DOI":"10.1016\/j.physrep.2013.11.002"},{"key":"2025073001350469000_2022.08.02.501652v3.10","doi-asserted-by":"crossref","unstructured":"Virkar Y & Clauset A (2014) Power-law distributions in binned empirical data. 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