Two hypotheses of autism spectrum disorder (ASD) propose that this condition is characterized by deficits in Theory of Mind and by hypoconnectivity between remote cortical regions with hyperconnectivity locally. The default mode network (DMN) is a set of remote, functionally connected cortical nodes less active during executive tasks than at rest and is implicated in Theory of Mind, episodic memory, and other self-reflective processes. We show that children with ASD have reduced connectivity between DMN nodes and increased local connectivity within DMN nodes and the visual and motor resting-state networks. We show that, like the trajectory of synaptogenesis, internodal DMN functional connectivity increased as a quadratic function of age in typically developing children, peaking between, 11 and 13 years. In children with ASD, these long-distance connections fail to develop during adolescence. These findings support the "developmental disconnection model" of ASD, provide a possible mechanistic explanation for the Theory-of-Mind hypothesis of ASD, and show that the window for effectively treating ASD could be wider than previously thought.
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http://dx.doi.org/10.1002/hbm.22252 | DOI Listing |
Brain Topogr
January 2025
Department of Neurology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.
Aberrant large-scale resting-state functional connectivity (rsFC) has been frequently documented in ischemic stroke. However, it remains unclear about the altered patterns of within- and across-network connectivity. The purpose of this meta-analysis was to identify the altered rsFC in patients with ischemic stroke relative to healthy controls, as well as to reveal longitudinal changes of network dysfunctions across acute, subacute, and chronic phases.
View Article and Find Full Text PDFJ Psychiatry Neurosci
January 2025
From the Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China (Gong, Wang, Nie, Ma, Zhou, Deng, Xie, Lyu, Chen, Kang, Liu); the Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China (Liu)
Background: Cortical morphometry is an intermediate phenotype that is closely related to the genetics and onset of major depressive disorder (MDD), and cortical morphometric networks are considered more relevant to disease mechanisms than brain regions. We sought to investigate changes in cortical morphometric networks in MDD and their relationship with genetic risk in healthy controls.
Methods: We recruited healthy controls and patients with MDD of Han Chinese descent.
J Psychiatry Neurosci
January 2025
From the Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China (X. Liu, Chen, K. Liu, Yan, Wu); the Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, Zhejiang Province, China (X. Liu, Chen, K. Liu, Yan); the Jinhua Municipal Central Hospital, Jinhua, Zhejiang 321000, China (Chen); the Hebei General Hospital, Shijiazhuang, Hebei 050050, China (Cheng); the Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang 310012, China (Wei, Hou, Li, Guo); the Zhoushan Second People's Hospital, Zhoushan, Zhejiang 316000, China (Guo)
Background: Both depressive symptoms and neurotransmitter changes affect the characteristics of functional brain networks in clinical patients. We sought to explore how brain functional grading is organized among patients with mild cognitive impairment and depressive symptoms (D-MCI) and whether changes in brain organization are related to neurotransmitter distribution.
Methods: Using 3 T magnetic resonance imaging (MRI) we acquired functional MRI (fMRI) data from patients with D-MCI, patients with mild cognitive impairment without depression (nD-MCI), and healthy controls.
Alzheimers Dement
December 2024
Korea University, Sejong, Sejong, Korea, Republic of (South).
Background: Amyloid-β accumulation is a pivotal factor in Alzheimer's disease (AD) progression. As treatment for AD has not been successful yet, the most effective approach lies in early diagnosis and the subsequent delay of disease progression. Hence, this study introduces a deep learning model to predict amyloid-β accumulation in the brain.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Neurologia, Azienda Ospedaliero Universitaria di Modena, Modena, Italy.
Background: Recent evidence suggests that unawareness in Alzheimer's disease (AD) continuum can be explained by a failure of the connections between brain regions involved in accessing and monitoring self and other information. It has been demonstrated that AD patients with anosognosia have reduced network connectivity in the default mode network (DMN); in addition, stronger connectivity of bilateral anterior cingulate cortex (ACC) was showed to be associated with anosognosia in prodromal AD suggesting a possible role of this region in mechanisms of "adaptation" to anosognosia early in the disease. Therefore, we hypothesized that anosognosia in AD could be associated with an imbalance between the activity of the DMN and the salience network (SN) detectable using resting state functional magnetic resonance imaging (fMRI).
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