The longitudinal neural dynamics changes of whole brain connectome during natural recovery from poststroke aphasia

Fan, Liming; Li, Chenxi; Huang, Zi‐Gang; Zhao, Jie; Wu, Xin; Liu, Tian; Li, Youjun; Wang, Jue

doi:10.1016/j.nicl.2022.103190

Cited by 3 publications

(2 citation statements)

References 117 publications

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“…To conduct energy landscape analysis, we applied the pairwise maximum entropy model (MEM) to the time series of the 9 brain networks in the same manner as in previous studies ( Watanabe et al, 2014a ; Watanabe and Rees, 2017 ; Ezaki et al, 2018 ; Fan et al, 2022 ). The pairwise MEM and the model fitting procedures are briefly described as follows.…”

Section: Methodsmentioning

confidence: 99%

“…Energy landscape analysis has been utilized to analyze abnormalities in brain dynamic dysfunction, including autism spectrum disorder ( Watanabe and Rees, 2017 ), poststroke aphasia ( Fan et al, 2022 ) and AD ( Klepl et al, 2022 ; Li et al, 2023 ). For the AD patient, it was found that the dynamics of AD patients’ EEG were shown to be more constrained - with more local minima, less variation in basin size, and smaller basins ( Klepl et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Energy landscape analysis of brain network dynamics in Alzheimer’s disease

Xing,

Guo,

Long

2024

Front. Aging Neurosci.

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BackgroundAlzheimer’s disease (AD) is a common neurodegenerative dementia, characterized by abnormal dynamic functional connectivity (DFC). Traditional DFC analysis, assuming linear brain dynamics, may neglect the complexity of the brain’s nonlinear interactions. Energy landscape analysis offers a holistic, nonlinear perspective to investigate brain network attractor dynamics, which was applied to resting-state fMRI data for AD in this study.MethodsThis study utilized resting-state fMRI data from 60 individuals, comparing 30 Alzheimer’s patients with 30 controls, from the Alzheimer’s Disease Neuroimaging Initiative. Energy landscape analysis was applied to the data to characterize the aberrant brain network dynamics of AD patients.ResultsThe AD group stayed in the co-activation state for less time than the healthy control (HC) group, and a positive correlation was identified between the transition frequency of the co-activation state and behavior performance. Furthermore, the AD group showed a higher occurrence frequency and transition frequency of the cognitive control state and sensory integration state than the HC group. The transition between the two states was positively correlated with behavior performance.ConclusionThe results suggest that the co-activation state could be important to cognitive processing and that the AD group possibly raised cognitive ability by increasing the occurrence and transition between the impaired cognitive control and sensory integration states.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy landscape analysis of brain network dynamics in Alzheimer’s disease

Xing,

Guo,

Long

2024

Front. Aging Neurosci.

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Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder

Ishida,

Yamada,

Yasuda

et al. 2024

NeuroImage: Clinical

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Right Hemisphere and Speech Recovery in Post-Stroke Aphasia

Shipkova,

Bulygina

2023

Клиническая И Специальная Психология

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<p style="text-align: justify;">The analytical review presents the clinical, neurobiological, and neuropsychological aspects of post-stroke aphasia as well as the role of the right hemisphere in speech recovery. The paper shows the influence of size, topography, lesion depth, cerebral hemodynamic plasticity, initial morphometric characteristics of the brain, and handedness on the functional recovery of aphasia. The review considers the typology and mechanisms of the appearance of "stealing symptoms" of homologous and non-homologous regions of the intact hemisphere. The "low-level" and "high-level" models of language competence of the right hemisphere are analyzed. The study describes the topography of the brain activation regions in the intact hemisphere during various speech task-solving. The paper shows the heterochrony between impressive and expressive speech recovery in aphasics and its bilateral inter-lateral distribution. The authors conclude that to clarify the mechanisms of aphasia recovery, it is necessary for a comprehensive account of clinical, neurobiological and neuropsychological patterns of speech disorder reparation in different post-stoke epochs. The paper notices that a deeper understanding of the impact of structural and functional repairment of speech processes on the aphasia outcome, it needs to assess the relationship between the degree of speech disorders reduction and the lateral vector of speech architectonics in the post-stroke period.</p>

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The longitudinal neural dynamics changes of whole brain connectome during natural recovery from poststroke aphasia

Cited by 3 publications

References 117 publications

Energy landscape analysis of brain network dynamics in Alzheimer’s disease

Energy landscape analysis of brain network dynamics in Alzheimer’s disease

Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder

Right Hemisphere and Speech Recovery in Post-Stroke Aphasia

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