Group‐guided individual functional parcellation of the hippocampus and application to normal aging

Zhang, Jiang; Xu, Dundi; Cui, Hongjie; Zhao, Tianyu; Chu, Congying; Wang, Jiaojian

doi:10.1002/hbm.25662

Cited by 30 publications

(28 citation statements)

References 66 publications

(105 reference statements)

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“…This is suggestive of a link between T2D and SZ. Given their shared role in emotion processing function (Wilcox et al, 2016;Pierce and Peron, 2020;Zhang et al, 2021b), it is possible that the cerebellum, which has been believed to be strongly connected with the limbic system (Schmahmann, 2000;Silvia et al, 2017;Zhang et al, 2021a), will proceed to develop GMV abnormalities after the limbic system. Poor emotion regulation has been observed in T2D patients (Rezaei et al, 2019;Pourmohammad Fahreh and Shirazi, 2020), and limbiccerebellum GMV alterations might be the structural basis for this finding.…”

Section: Discussionmentioning

confidence: 99%

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients

Zhang

Liu

Guo

et al. 2022

Front. Hum. Neurosci.

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Background and PurposeAccording to reports, type 2 diabetes (T2D) is a progressive disease. However, no known research has examined the progressive brain structural changes associated with T2D. The purpose of this study was to determine whether T2D patients exhibit progressive brain structural alterations and, if so, how the alterations progress.Materials and MethodsStructural magnetic resonance imaging scans were collected for 81 T2D patients and 48 sex-and age-matched healthy controls (HCs). Voxel-based morphometry (VBM) and causal structural covariance network (CaSCN) analyses were applied to investigate gray matter volume (GMV) alterations and the likely chronological processes underlying them in T2D. Two sample t-tests were performed to compare group differences, and the differences were corrected using Gaussian random field (GRF) correction (voxel-level p < 0.001, cluster-level p < 0.01).ResultsOur findings demonstrated that GMV alterations progressed in T2D patients as disease duration increased. In the early stages of the disease, the right temporal pole of T2D patients had GMV atrophy. As the diseases duration prolonged, the limbic system, cerebellum, subcortical structures, parietal cortex, frontal cortex, and occipital cortex progressively exhibited GMV alterations. The patients also exhibited a GMV alterations sequence exerting from the right temporal pole to the limbic-cerebellum-striatal-cortical network areas.ConclusionOur results indicate that the progressive GMV alterations of T2D patients manifested a limbic-cerebellum-striatal-cortical sequence. These findings may contribute to a better understanding of the progression and an improvement of current diagnosis and intervention strategies for T2D.

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Section: Discussionmentioning

confidence: 99%

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients

Zhang

Liu

Guo

et al. 2022

Front. Hum. Neurosci.

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“…Group prior guided individualized atlas construction. It has been proved that a high probability group atlas is the commonality among population 50,53 . Based on this, we directly registered the high probability (P>0.70) group thalamus atlas to native diffusion space and took it as the high-probability group prior.…”

Section: Individualized Thalamus Atlas Constructionmentioning

confidence: 99%

“…Meanwhile, the capacity to identify the unique architecture of an individual’s thalamus is essential for personalized medicine. The individual-specific brain atlas could provide higher parcellation accuracy 49,50 and better predict performance in cognition 51 , behavior 52 , and brain aging 53 . Besides, an individualized brain atlas has been frequently applied in disease diagnosis 54 , neurosurgery localization 55–57 , and prognosis prediction 58 .…”

Section: Introductionmentioning

confidence: 99%

“…And they lack canonical cluster labeling criteria and population commonality. Multi-subject-based methods first build a group-level brain atlas to substitute 62,66 or guide 24,50,53,67 the further construction of an individualized atlas. The group substitution strategy completely ignores individual specificity.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, the capacity to identify the unique architecture of an individual's thalamus is essential for personalized medicine. The individual-specific brain atlas could provide higher parcellation accuracy 49,50 and better predict performance in cognition 51 , behavior 52 , and brain aging 53 .…”

Section: Introductionmentioning

confidence: 99%

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Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

Gao

Wang

et al. 2022

Preprint

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As a gateway for projections entering and exiting the cerebral cortex, the human thalamus processes information from sensory to cognition relevant to various neuropsychiatric disorders. It is composed of dozens of nuclei, which have been difficult to identify with clinical MR sequences. However, delineating thalamic nuclei accurately at an individual level is essential for precise neuromodulation treatment. Here, we not only identified the fine-grained thalamic nuclei using local diffusion properties in vivo but also employed a deep learning strategy to achieve highly reproducible individual-level parcellation. Using High-quality diffusion MRI (dMRI), we first constructed a fine-grained group thalamus atlas based on thalamic local diffusion features. Then, the high-probability core area of the group thalamus atlas was wrapped into the native space as prior guidance for individualized thalamus construction. Finally, we trained the semi-supervised multiple classification models to accurately construct the individualized thalamus atlas with single-subject local diffusion characteristics. Compared to group atlas registration and single-subject clustering strategies, our individualized thalamus atlas combines population commonality and individual specificity and is superior in depicting the individual thalamic nuclei boundaries. Besides, our atlas provides a more conspicuous capacity to capture the individual specificity of thalamic nuclei. Through the evaluation by 3.0T\7.0T and test-retest dMRI datasets, the proposed high-probability group prior guided individualized thalamus construction pipeline is robust and repeatable in different magnetic field strengths and scanning batches. In addition, the individual parcellation of the thalamic nuclei has a good correspondence with the histological atlas and captured both higher group consistency and inter-subjects variations, which could be a valuable solution for precision clinical treatment.

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Group‐guided individual functional parcellation of the hippocampus and application to normal aging

Zhang

Cui

et al. 2021

Human Brain Mapping

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Aging is closely associated with cognitive decline affecting attention, memory and executive functions. The hippocampus is the core brain area for human memory, learning, and cognition processing. To delineate the individual functional patterns of hippocampus is pivotal to reveal the neural basis of aging. In this study, we developed a group-guided individual parcellation approach based on semisupervised affinity propagation clustering using the resting-state functional magnetic resonance imaging to identify individual functional subregions of hippocampus and to identify the functional patterns of each subregion during aging. A three-way group parcellation was yielded and was taken as prior information to guide individual parcellation of hippocampus into head, body, and tail in each subject. The superiority of individual parcellation of hippocampus is validated by higher intraregional functional similarities by compared to group-level parcellation results. The individual variations of hippocampus were associated with coactivation patterns of three typical functions of hippocampus. Moreover, the individual functional connectivities of hippocampus subregions with predefined target regions could better predict age than group-level functional connectivities. Our study provides a novel framework for individual brain functional parcellations, which may facilitate the future individual researches for brain cognitions and brain disorders and directing accurate neuromodulation.

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Group‐guided individual functional parcellation of the hippocampus and application to normal aging

Cited by 30 publications

References 66 publications

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients

Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

Group‐guided individual functional parcellation of the hippocampus and application to normal aging

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