AJNR. American journal of neuroradiology · 2026
Study of Cerebellar Network Dynamics in Patients with Poststroke Aphasia Based on Resting-State Functional MRI.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chen Liting, Li Lifeng, Dai Yanhong, Mai Wenfeng, Luo Zhenye, Shu Yongqiang, Chen Xiaoyun, Fang Qun, Chen Lv, Chen Zhuoming, Zhang Shuixing
Аннотация
BACKGROUND AND PURPOSE: The cerebellum is increasingly recognized as a key contributor to language and cognitive processing, but its dynamic network alterations in poststroke aphasia remain poorly understood. This study investigated dynamic cerebellar networks in patients with poststroke aphasia using resting-state functional MRI. We examined intracerebellar and cerebellar-cortical dynamic functional connectivity and quantified their temporal properties and graph-theoretical topology.
MATERIALS AND METHODS: Seventy-seven right-handed patients with poststroke aphasia and 79 healthy controls underwent 3T resting-state functional MRI. Dynamic cerebellar functional networks were constructed using the Seitzman-27 cerebellar atlas. A sliding window approach (30 TR window, 1 TR step) was applied, followed by K-means clustering to identify distinct connectivity states. Graph-theoretical analyses were performed to quantify state-specific network topology. The variability of dynamic functional connectivity between the cerebellar and cortical regions was calculated. Partial correlation analyses were performed to examine the relationships among dynamic network measures, lesion volume, and language and cognitive function.
RESULTS: Two cerebellar dynamic functional connectivity states were identified in poststroke aphasia: a predominant segregated state (78.93%) with widespread reductions in connectivity and decreased clustering coefficient (d = -1.29), characteristic path length (d = -0.62), and local efficiency (d = -1.11) but higher global efficiency (d = 1.06) and a less frequent integrated state (21.07%) with enhanced connectivity and a higher clustering coefficient (d = 0.57) and characteristic path length (d = 0.70) and diminished global efficiency (d = -1.25) and small-worldness (d = -0.92) and small-world index (d = -0.89). Poststroke aphasia showed reduced variability of dynamic functional connectivity between the cerebellar and cortical regions involved in language and cognition (Gaussian random field correction, voxel-level P < .001, cluster-level P < .05). Lesion volume negatively correlated with Aphasia Quotient, repetition, memory, executive function, and attention (P < .005). State-specific network metrics and variability measures were associated with language and cognitive performance independent of lesion volume.
CONCLUSIONS: Patients with poststroke aphasia exhibited a segregated cerebellar state with reduced intracerebellar connectivity and efficiency and an integrated state with enhanced connectivity and small-world properties, together with reduced variability in cerebellar-cortical connections to language- and cognition-related regions. These state-specific network alterations were linked to distinct behavioral domains independent of lesion volume, highlighting a dissociation between structural constraints and dynamic, lesion-independent plasticity.
MATERIALS AND METHODS: Seventy-seven right-handed patients with poststroke aphasia and 79 healthy controls underwent 3T resting-state functional MRI. Dynamic cerebellar functional networks were constructed using the Seitzman-27 cerebellar atlas. A sliding window approach (30 TR window, 1 TR step) was applied, followed by K-means clustering to identify distinct connectivity states. Graph-theoretical analyses were performed to quantify state-specific network topology. The variability of dynamic functional connectivity between the cerebellar and cortical regions was calculated. Partial correlation analyses were performed to examine the relationships among dynamic network measures, lesion volume, and language and cognitive function.
RESULTS: Two cerebellar dynamic functional connectivity states were identified in poststroke aphasia: a predominant segregated state (78.93%) with widespread reductions in connectivity and decreased clustering coefficient (d = -1.29), characteristic path length (d = -0.62), and local efficiency (d = -1.11) but higher global efficiency (d = 1.06) and a less frequent integrated state (21.07%) with enhanced connectivity and a higher clustering coefficient (d = 0.57) and characteristic path length (d = 0.70) and diminished global efficiency (d = -1.25) and small-worldness (d = -0.92) and small-world index (d = -0.89). Poststroke aphasia showed reduced variability of dynamic functional connectivity between the cerebellar and cortical regions involved in language and cognition (Gaussian random field correction, voxel-level P < .001, cluster-level P < .05). Lesion volume negatively correlated with Aphasia Quotient, repetition, memory, executive function, and attention (P < .005). State-specific network metrics and variability measures were associated with language and cognitive performance independent of lesion volume.
CONCLUSIONS: Patients with poststroke aphasia exhibited a segregated cerebellar state with reduced intracerebellar connectivity and efficiency and an integrated state with enhanced connectivity and small-world properties, together with reduced variability in cerebellar-cortical connections to language- and cognition-related regions. These state-specific network alterations were linked to distinct behavioral domains independent of lesion volume, highlighting a dissociation between structural constraints and dynamic, lesion-independent plasticity.