{"id":179097,"date":"2023-12-25T13:35:29","date_gmt":"2023-12-25T19:35:29","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2023\/12\/psychedelic-concentrations-of-nitrous-oxide-reduce-functional-differentiation-in-frontoparietal-and-somatomotor-cortical-networks"},"modified":"2023-12-25T13:35:29","modified_gmt":"2023-12-25T19:35:29","slug":"psychedelic-concentrations-of-nitrous-oxide-reduce-functional-differentiation-in-frontoparietal-and-somatomotor-cortical-networks","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2023\/12\/psychedelic-concentrations-of-nitrous-oxide-reduce-functional-differentiation-in-frontoparietal-and-somatomotor-cortical-networks","title":{"rendered":"Psychedelic concentrations of nitrous oxide reduce functional differentiation in frontoparietal and somatomotor cortical networks"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/psychedelic-concentrations-of-nitrous-oxide-reduce-functional-differentiation-in-frontoparietal-and-somatomotor-cortical-networks2.jpg\"><\/a><\/p>\n<p>Cortical gradient mapping stands as an innovative analytical tool for exploring the brain\u2019s functional-spatial organization along a continuous spectrum<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Margulies, D. S. et al. Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc. Natl Acad. Sci. USA 113, 12574&ndash;12579 (2016).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR28\" id=\"ref-link-section-d1034414795e629\">28<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Huntenburg, J. M., Bazin, P. L. & Margulies, D. S. Large-scale gradients in human cortical organization. Trends Cogn. Sci. 22, 21&ndash;31 (2018).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR29\" id=\"ref-link-section-d1034414795e629_1\">29<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 30\" title=\"Murphy, C. et al. Distant from input: evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition. Neuroimage 171393&ndash;401 (2018).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR30\" id=\"ref-link-section-d1034414795e632\">30<\/a><\/sup>, distinguishing it from conventional techniques reliant on discrete boundaries, e.g., functional parcellation in neuroimaging. As an intuitive metaphor, consider defining a geographic region by its boundary coordinates, which is akin to functional parcellation, versus describing it by elevation slopes or changes in vegetation types across various topographical axes, which is similar to gradient mapping. These cortical gradients span a wide spectrum of functions and networks, ranging from perception and action to higher-order cognitive processes<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 28\" title=\"Margulies, D. S. et al. Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc. Natl Acad. Sci. USA 113, 12574&ndash;12579 (2016).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR28\" id=\"ref-link-section-d1034414795e636\">28<\/a><\/sup>. Notably, Gradient-1, known as the unimodal to transmodal gradient, enables the integration of sensory signals with non-sensory data, transforming them into abstract content. Gradient-2, the visual to somatomotor gradient, represents the specialization of different sensory modalities. Lastly, Gradient-3 spans functional distinctions ranging from regions typically deactivated during task performance (i.e., task-negative) to those activated in frontoparietal and attention networks (i.e., task-positive)<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 31\" title=\"Smallwood, J. et al. The neural correlates of ongoing conscious thought. iScience 24, 102132 (2021).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR31\" id=\"ref-link-section-d1034414795e640\">31<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 32\" title=\"Cross, N. et al. Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation. Neuroimage 226, 117547 (2021).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR32\" id=\"ref-link-section-d1034414795e643\">32<\/a><\/sup>. Despite promising foundations, the potential of gradients as a framework for analyzing and conceptualizing non-ordinary states of consciousness induced by psychedelics remains ripe for exploration.<\/p>\n<p>In addition to the brain\u2019s functional geometry, dynamic processes continuously mold and reconfigure functional arrangements, leading to the evolution of brain activity patterns over time<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 33\" title=\"Huang, Z., Zhang, J., Wu, J., Mashour, G. A. & Hudetz, A. G. Temporal circuit of macroscale dynamic brain activity supports human consciousness. Sci. Adv. 6, 1&ndash;15 (2020).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR33\" id=\"ref-link-section-d1034414795e650\">33<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 34\" title=\"Singleton, S. P. et al. Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain\u2019s control energy landscape. Nat. Commun. 13, 1&ndash;13 (2022).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR34\" id=\"ref-link-section-d1034414795e653\">34<\/a><\/sup>. Recent empirical investigations have highlighted the intricate interplay between the spatial and temporal characteristics of brain activity, emphasizing that a comprehensive understanding necessitates the consideration of both aspects. Notably, transient fMRI co-activations<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 33\" title=\"Huang, Z., Zhang, J., Wu, J., Mashour, G. A. & Hudetz, A. G. Temporal circuit of macroscale dynamic brain activity supports human consciousness. Sci. Adv. 6, 1&ndash;15 (2020).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR33\" id=\"ref-link-section-d1034414795e657\">33<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 35\" title=\"Liu, X., Zhang, N., Chang, C. & Duyn, J. H. Co-activation patterns in resting-state fMRI signals. Neuroimage 180485&ndash;494 (2018).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR35\" id=\"ref-link-section-d1034414795e660\">35<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 36\" title=\"Liu, X. & Duyn, J. H. Time-varying functional network information extracted from brief instances of spontaneous brain activity. Proc. Natl Acad. Sci. USA 110, 4392&ndash;4397 (2013).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR36\" id=\"ref-link-section-d1034414795e663\">36<\/a><\/sup> spanning the entire cortex have been observed to propagate like waves, following the spatially defined cortical gradients<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Gu, Y. et al. Brain activity fluctuations propagate as waves traversing the cortical hierarchy. Cereb. Cortex 31, 3986&ndash;4005 (2021).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR37\" id=\"ref-link-section-d1034414795e667\">37<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Raut, R. V. et al. Global waves synchronize the brain\u2019s functional systems with fluctuating arousal. Sci. Adv. 7, 1&ndash;16 (2021).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR38\" id=\"ref-link-section-d1034414795e667_1\">38<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 39\" title=\"Yousefi, B. & Keilholz, S. Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain. Neuroimage 231, 117827 (2021).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR39\" id=\"ref-link-section-d1034414795e670\">39<\/a><\/sup>. Consequently, temporal dynamics are likely to be influenced by the underlying functional geometry. Exploring the co-variation between these spatial and temporal factors holds the potential to offer deeper insights into the neural underpinnings of psychedelic effects.<\/p>\n<p>The objective of this study was to apply advanced cortical gradient mapping and co-activation pattern analysis to dissect the brain\u2019s spatiotemporal reconfiguration during the psychedelic experience induced by nitrous oxide. Building upon previous research findings<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 16\" title=\"Dai, R. et al. Classical and non-classical psychedelic drugs induce common network changes in human cortex. Neuroimage https:\/\/doi.org\/10.1016\/j.neuroimage.2023.120097 (2023).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR16\" id=\"ref-link-section-d1034414795e677\">16<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 25\" title=\"Girn, M. et al. Serotonergic psychedelic drugs LSD and psilocybin reduce the hierarchical differentiation of unimodal and transmodal cortex. Neuroimage 256, 119220 (2022).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR25\" id=\"ref-link-section-d1034414795e680\">25<\/a><\/sup>, we tested the hypothesis that nitrous oxide could diminish functional differentiation within the human cortex, as evidenced by a contraction in functional geometry and a disruption in temporal dynamics. We reanalyzed a neuroimaging dataset of healthy human volunteers, who were assessed by fMRI before and during exposure to psychedelic concentrations of nitrous oxide (35%, in oxygen) and who completed a validated altered states of consciousness questionnaire<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 40\" title=\"Studerus, E., Gamma, A. & Vollenweider, F. X. Psychometric evaluation of the altered states of consciousness rating scale (OAV). PLoS ONE 5, e12412 (2010).\" href=\"https:\/\/www.nature.com\/articles\/s42003-023-05678-1#ref-CR40\" id=\"ref-link-section-d1034414795e684\">40<\/a><\/sup> before and after drug exposure. We quantified the changes of neural activity in cortical gradients and co-activations; we also performed correlation analyses to explore the relationship between subjective psychedelic experience and these brain measures. We demonstrate that nitrous oxide flattens the functional geometry of the cortex and disrupts related temporal dynamics, particularly within the frontoparietal and somatomotor networks, in association with the psychedelic experience.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cortical gradient mapping stands as an innovative analytical tool for exploring the brain\u2019s functional-spatial organization along a continuous spectrum28,29,30, distinguishing it from conventional techniques reliant on discrete boundaries, e.g., functional parcellation in neuroimaging. As an intuitive metaphor, consider defining a geographic region by its boundary coordinates, which is akin to functional parcellation, versus describing it [\u2026]<\/p>\n","protected":false},"author":661,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,385,47],"tags":[],"class_list":["post-179097","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-evolution","category-neuroscience"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/179097","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/661"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=179097"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/179097\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=179097"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=179097"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=179097"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}