Disrupted Resting-State Functional Connectivity in Hippocampal Subregions After Sleep Deprivation

Zhao, Rui; Zhang, Xinxin; Zhu, Yuanqiang; Fei, Ningbo; Sun, Jinbo; Liu, Peng; Yang, Xuejuan; Qin, Wei

doi:10.1016/j.neuroscience.2018.11.049

Cited by 25 publications

(26 citation statements)

References 67 publications

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“…More importantly, our results revealed that these GMV covariance‐based subregions additionally distributed along the transverse axis, which corresponded with the spatial configuration of the cytoarchitecturally defined subfields (Amunts et al, ). This result is similar to those reported in the fMRI literature (Beissner et al, ; Moher Alsady et al, ; Zhao et al, ), where a transverse distribution of the subregions in the head of the hippocampus is found when the number of clusters was set to a relatively high number. Furthermore, most of these subregions were located in the CA1, dentate gyrus, and subiculum, because these three subfields extend along the anterior–posterior axis mostly (Yushkevich, Pluta, et al, ).…”

Section: Discussionsupporting

confidence: 91%

“…There are some similarities as well as differences between the parcellations of the present study and of others using fMRI data (Beissner et al, ; Robinson et al, ; Robinson, Salibi, & Deshpande, ; Zhao et al, ). The longitudinally discrete configuration of the hippocampal subregions in the present study was remarkable, given the widely known model of the long‐axis functional specialization of hippocampus (Poppenk et al, ; Strange et al, ).…”

Section: Discussionsupporting

confidence: 62%

“…The left and right hippocampal ROIs were defined on the basis of the Harvard-Oxford atlas, using a probability threshold of 50% (Beissner et al, 2018;Blessing et al, 2016;Marder et al, 2014;Zhao et al, 2019) at the MNI152 space, yielding a conservative anatomical representation with 1,267 and 1,271 voxels for the left and right hippocampus respectively (MNI152 1.5 mm space). GMV covariance quantifies the extent to which GMV covary between different regions across participants, and in the present study, GMV covariance was conducted via two approaches: voxel-based GMVCorr (Kelly et al, 2012;Liu et al, 2015) and MICA (Moher Alsady et al, 2016).…”

Section: Gmv Covariance-based Parcellationmentioning

confidence: 99%

“…A data‐driven functional connectivity approach (masked independent component analysis, [MICA]) (Moher Alsady, Blessing, & Beissner, ), was also used to reproducibly define hippocampal subregions with resting‐state fMRI, and map their intrinsic functional connectivity patterns, demonstrating configurations that support longitudinal segmentation of hippocampal functions (Blessing, Beissner, Schumann, Brünner, & Bär, ). More recently, Beissner, Preibisch, Schweizer‐Arau, Popovici, and Meissner () and Zhao et al () divided the bilateral hippocampus into 10 and 17 subregions with MICA, respectively. Despite these attempts to delineate functionally hippocampal subdivisions, subregions based on the characterization of the structural connectivity/covariance are less well defined.…”

Section: Introductionmentioning

confidence: 99%

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Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults

Kot

Liu

et al. 2019

Human Brain Mapping

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The hippocampus is a key brain region that participates in a range of cognitive and affective functions, and is involved in the etiopathogenesis of numerous neuropsychiatric disorders. The structural complexity and functional diversity of the hippocampus suggest the existence of structural and functional subdivisions within this structure. For the first time, we parcellated the human hippocampus with two independent data sets, each of which consisted of 198 T1‐weighted structural magnetic resonance imaging (sMRI) images of healthy young subjects. The method was based on gray matter volume (GMV) covariance, which was quantified by a bivariate voxel‐to‐voxel linear correlation approach, as well as a multivariate masked independent component analysis approach. We subsequently interrogated the relationship between the GMV covariance patterns and the functional connectivity patterns of the hippocampal subregions using sMRI and resting‐state functional MRI (fMRI) data from the same participants. Seven distinct GMV covariance‐based subregions were identified for bilateral hippocampi, with robust reproducibility across the two data sets. We further demonstrated that the structural covariance patterns of the hippocampal subregions had a correspondence with the intrinsic functional connectivity patterns of these subregions. Together, our results provide a topographical configuration of the hippocampus with converging structural and functional support. The resulting subregions may improve our understanding of the hippocampal connectivity and functions at a subregional level, which provides useful parcellations and masks for future neuroscience and clinical research on the structural and/or functional connectivity of the hippocampus.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 62%

Section: Gmv Covariance-based Parcellationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults

Kot

Liu

et al. 2019

Human Brain Mapping

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“…Although the exact function of sleep remains to be elucidated, it is well known that sleep facilitates memory retention [10][11][12][13] , whereas sleep deprivation degrades memory performance and brain function [14][15][16][17][18][19][20][21][22][23] . Animal studies have consistently demonstrated the impairing effects of sleep loss on several neural circuits involved in learning and memory, in particular the hippocampal complex [16][17][18] .…”

mentioning

confidence: 99%

Two nights of recovery sleep restores hippocampal connectivity but not episodic memory after total sleep deprivation

Chai

Fang

Yang

et al. 2020

Sci Rep

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Sleep deprivation significantly impairs a range of cognitive and brain function, particularly episodic memory and the underlying hippocampal function. However, it remains controversial whether one or two nights of recovery sleep following sleep deprivation fully restores brain and cognitive function. In this study, we used functional magnetic resonance imaging (fMRI) and examined the effects of two consecutive nights (20-hour time-in-bed) of recovery sleep on resting-state hippocampal connectivity and episodic memory deficits following one night of total sleep deprivation (TSD) in 39 healthy adults in a controlled in-laboratory protocol. TSD significantly reduced memory performance in a scene recognition task, impaired hippocampal connectivity to multiple prefrontal and default mode network regions, and disrupted the relationships between memory performance and hippocampal connectivity. Following TSD, two nights of recovery sleep restored hippocampal connectivity to baseline levels, but did not fully restore memory performance nor its associations with hippocampal connectivity. These findings suggest that more than two nights of recovery sleep are needed to fully restore memory function and hippocampal-memory associations after one night of total sleep loss.

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Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

Sun

Zhao

et al. 2022

Human Brain Mapping

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Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting-state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep-deprived subjects showed increased regional-level temporal variability in largescale brain regions, and decreased regional-level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra-network temporal variability in the default mode network (DMN) and increased inter-network temporal variability in numerous subnetwork pairs. Furthermore, we found that the internetwork temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (β = À.42, p = 5.57 Â 10 À4 ) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep-deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.

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Disrupted Resting-State Functional Connectivity in Hippocampal Subregions After Sleep Deprivation

Cited by 25 publications

References 67 publications

Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults

Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults

Two nights of recovery sleep restores hippocampal connectivity but not episodic memory after total sleep deprivation

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

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