Feifei Zhang, Zhipeng Yang, Kun Qin, J. Sweeney, N. Roberts, Z. Jia, Q. Gong
A long-haul flight across more than five time zones may produce a circadian rhythm sleep disorder known as jet lag. Little is known about the effect of jet lag on white matter (WM) functional connectivity (FC). The present study is to investigate changes in WM FC in subjects due to recovery from jet lag after flying across six time zones. Here, resting-state functional magnetic resonance imaging was performed in 23 participants within 24 hours of flying and again 50 days later. Gray matter (GM) and WM networks were identified by k-means clustering. WM FC and functional covariance connectivity (FCC) were analyzed. Next, a sliding window method was used to establish dynamic WM FC. WM static and dynamic FC and FCC were compared between when participants had initially completed their journey and 50 days later. Emotion was assessed using the Positive and Negative Affect Schedule and the State Anxiety Inventory. All participants were confirmed to have jet lag symptoms by the Columbian Jet Lag Scale. The static FC strengthes of cingulate network (WM7)- sensorimotor network and ventral frontal network- visual network were lower after the long-haul flight compared with recovery. Corresponding results were obtained for the dynamic FC analysis. The analysis of FCC revealed weakened connections between the WM7 and several other brain networks, especially the precentral/postcentral network. Moreover, a negative correlation was found between emotion scores and the FC between the WM7 and sensorimotor related regions. The results of this study provide further evidence for the existence of WM networks and show that jet lag is associated with alterations in static and dynamic WM FC and FCC, especially in sensorimotor networks. Jet lag is a complex problem that not only is related to sleep rhythm but also influences emotion.
{"title":"Effect of jet lag on brain white matter functional connectivity","authors":"Feifei Zhang, Zhipeng Yang, Kun Qin, J. Sweeney, N. Roberts, Z. Jia, Q. Gong","doi":"10.2139/ssrn.3562443","DOIUrl":"https://doi.org/10.2139/ssrn.3562443","url":null,"abstract":"\u0000 \u0000 \u0000 A long-haul flight across more than five time zones may produce a circadian rhythm sleep disorder known as jet lag. Little is known about the effect of jet lag on white matter (WM) functional connectivity (FC).\u0000 \u0000 \u0000 \u0000 The present study is to investigate changes in WM FC in subjects due to recovery from jet lag after flying across six time zones.\u0000 \u0000 \u0000 \u0000 Here, resting-state functional magnetic resonance imaging was performed in 23 participants within 24 hours of flying and again 50 days later. Gray matter (GM) and WM networks were identified by k-means clustering. WM FC and functional covariance connectivity (FCC) were analyzed. Next, a sliding window method was used to establish dynamic WM FC. WM static and dynamic FC and FCC were compared between when participants had initially completed their journey and 50 days later. Emotion was assessed using the Positive and Negative Affect Schedule and the State Anxiety Inventory.\u0000 \u0000 \u0000 \u0000 All participants were confirmed to have jet lag symptoms by the Columbian Jet Lag Scale. The static FC strengthes of cingulate network (WM7)- sensorimotor network and ventral frontal network- visual network were lower after the long-haul flight compared with recovery. Corresponding results were obtained for the dynamic FC analysis. The analysis of FCC revealed weakened connections between the WM7 and several other brain networks, especially the precentral/postcentral network. Moreover, a negative correlation was found between emotion scores and the FC between the WM7 and sensorimotor related regions.\u0000 \u0000 \u0000 \u0000 The results of this study provide further evidence for the existence of WM networks and show that jet lag is associated with alterations in static and dynamic WM FC and FCC, especially in sensorimotor networks. Jet lag is a complex problem that not only is related to sleep rhythm but also influences emotion.\u0000","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"20 1","pages":"55-65"},"PeriodicalIF":0.0,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75234899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Huiru Li, Huawei Zhang, L. Yin, Feifei Zhang, Ziqi Chen, Taolin Chen, Z. Jia, Q. Gong
Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images. This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality. Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients. Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores. Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.
{"title":"Altered cortical morphology in major depression disorder patients with suicidality","authors":"Huiru Li, Huawei Zhang, L. Yin, Feifei Zhang, Ziqi Chen, Taolin Chen, Z. Jia, Q. Gong","doi":"10.2139/ssrn.3546027","DOIUrl":"https://doi.org/10.2139/ssrn.3546027","url":null,"abstract":"\u0000 \u0000 \u0000 Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images.\u0000 \u0000 \u0000 \u0000 This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality.\u0000 \u0000 \u0000 \u0000 Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients.\u0000 \u0000 \u0000 \u0000 Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores.\u0000 \u0000 \u0000 \u0000 Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.\u0000","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82771478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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