The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics

Filippi, Eleonora De; Uribe, Carme; Avila-Varela, Daniela S.; Martínez‐Molina, Noelia; Gashaj, Venera; Pritschet, Laura; Santander, Tyler; Jacobs, Emily G.; Kringelbach, Morten L.; Perl, Yonatan Sanz; Deco, Gustavo; Escrichs, Anira

doi:10.3389/fnins.2021.753820

Cited by 34 publications

(31 citation statements)

References 46 publications

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“…This scenario is very close to that of the Benjamin-Feir instability in the Ginzburg-Landau system, which was studied by Kuramoto as a main route to turbulence in chemical reaction systems [48,49,56]. Our findings thus align with recent studies that remark the prominence of turbulent dynamics as signature of brain states [8,[98][99][100][101].…”

Section: Discussionsupporting

confidence: 90%

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Clusella

Deco

Kringelbach

et al. 2022

Preprint

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Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next-generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.

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Section: Discussionsupporting

confidence: 90%

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Clusella

Deco

Kringelbach

et al. 2022

Preprint

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“…However, this initiative lacks standard acquisition protocols to reduce the variability among sites that may hamper group discrimination. Second, the menstrual cycle of cis women and trans men was not accounted as a variable of interest, while there is growing evidence of functional dynamic differences between the phases of the menstrual cycle (De Filippi et al, 2021 ). Likewise, the sexual orientation of all participants was not systematically assessed as a variable of interest (Frigerio et al, 2021 ; Guillamon et al, 2016 ; Skorska et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Whole‐brain dynamics differentiate among cisgender and transgender individuals

Uribe

Escrichs

Filippi

et al. 2022

Human Brain Mapping

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How the brain represents gender identity is largely unknown, but some neural differences have recently been discovered. We used an intrinsic ignition framework to investigate whether there are gender differences in the propagation of neural activity across the whole‐brain and within resting‐state networks. Studying 29 trans men and 17 trans women with gender incongruence, 22 cis women, and 19 cis men, we computed the capability of a given brain area in space to propagate activity to other areas (mean‐ignition), and the variability across time for each brain area (node‐metastability). We found that both measurements differentiated all groups across the whole brain. At the network level, we found that compared to the other groups, cis men showed higher mean‐ignition of the dorsal attention network and node‐metastability of the dorsal and ventral attention, executive control, and temporal parietal networks. We also found higher mean‐ignition values in cis men than in cis women within the executive control network, but higher mean‐ignition in cis women than cis men and trans men for the default mode. Node‐metastability was higher in cis men than cis women in the somatomotor network, while both mean‐ignition and node‐metastability were higher for cis men than trans men in the limbic network. Finally, we computed correlations between these measurements and a body image satisfaction score. Trans men's dissatisfaction as well as cis men's and cis women's satisfaction toward their own body image were distinctively associated with specific networks in each group. Overall, the study of the whole‐brain network dynamical complexity discriminates gender identity groups, functional dynamic approaches could help disentangle the complex nature of the gender dimension in the brain.

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“…Can early intervention during the luteal phase, when peak estrogen promotes higher endometrial production of PGE2 relative to PGF2 α in the premenstrual phase, alleviates dysmenorrhea if performed during the luteal phase? Brain dynamics are regulated by rhythmic variations in the concentration of female sex hormones throughout the menstrual cycle [ 63 , 64 ]. The use of acupuncture stimulation during different phases of the menstrual cycle may bring about different changes in the brain that should be fully explored.…”

Section: Discussionmentioning

confidence: 99%

Revealing the Central Mechanism of Acupuncture for Primary Dysmenorrhea Based on Neuroimaging: A Narrative Review

Chen

Guo

Zhang

et al. 2023

Pain Research and Management

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Objective. The central mechanism of acupuncture for primary dysmenorrhea was explored by summarizing the changes in different regional networks of the brain induced by acupuncture stimulation by analyzing the existing studies. Methods. The original studies were collected and selected from three English databases such as PubMed and four Chinese databases as China Knowledge Network (CNKI). The main keyword clusters are neuroimaging, acupuncture, and primary dysmenorrhea. Results. The literature review yielded 130 possibly qualified studies, and 23 articles fulfilled the criteria for inclusion. Regarding the type of acupuncture studies, 6 moxibustion studies and 17 manual acupuncture studies for primary dysmenorrhea were included. Based on functional magnetic resonance imaging (fMRI), perfusion-weighted imaging (PWI), and positron emission tomography-computer tomography techniques (PET-CT), one or more analysis methods such as amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), functional connectivity (FC), and independent components analysis (ICA) were used. The results are summarized. To summarize the high-frequency brain area alterations observed in patients with acupuncture-induced primary dysmenorrhea were the anterior cingulate gyrus, thalamus, insula, precentral gyrus, middle frontal gyrus, postcentral gyrus, putamen, and cerebellum. Conclusion. The results suggest that the mechanism of acupuncture in the treatment of primary dysmenorrhea is the involvement of networks regulating different areas of the brain in the analgesic effects of acupuncture. The brain regions involved in primary dysmenorrhea acupuncture analgesia were mainly located in the pain matrix, default mode network, salience network, and limbic system.

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The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics

Cited by 34 publications

References 46 publications

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Whole‐brain dynamics differentiate among cisgender and transgender individuals

Revealing the Central Mechanism of Acupuncture for Primary Dysmenorrhea Based on Neuroimaging: A Narrative Review

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