Altered mismatch response of inferior parietal lobule in amnestic mild cognitive impairment: A magnetoencephalographic study

Chen, Pin-Yu; Hsu, Hui Yun; Yi, Chao; Nouchi, Rui; Wang, Pei Ning; Cheng, Chia‐Hsiung

doi:10.1111/cns.13691

Cited by 6 publications

(6 citation statements)

References 70 publications

(178 reference statements)

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“…In the brain node attention module, we set up multiple base layers to capture the brain regions related to MCI. The experiments in this article found that 34 brain regions in all brain regions are closely related to MCI, including the middle temporal gyrus controls semantic cognition (Davey et al, 2016 ); the Superior frontal gyrus medial orbitally affects schizophrenia and delusions (Gao et al, 2015 ); Inferior parietal affects sensory memory function Chen et al ( 2021 ); Supramarginal gyrus affects auditory memory function (DES, 2014 ); and Precuneus affects cognitive function (Nagano-Saito et al, 2021 ). These brain nodes are correlated with MCI and are consistent with the experimental results of previous studies (Greicius, 2008 ; Albert et al, 2011 ).…”

Section: Discussionmentioning

confidence: 93%

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

Feng

Huang

Le³

et al. 2022

Front. Aging Neurosci.

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Mild cognitive impairment (MCI) is a nervous system disease, and its clinical status can be used as an early warning of Alzheimer's disease (AD). Subtle and slow changes in brain structure between patients with MCI and normal controls (NCs) deprive them of effective diagnostic methods. Therefore, the identification of MCI is a challenging task. The current functional brain network (FBN) analysis to predict human brain tissue structure is a new method emerging in recent years, which provides sensitive and effective medical biomarkers for the diagnosis of neurological diseases. Therefore, to address this challenge, we propose a novel Deep Spatiotemporal Attention Network (DSTAN) framework for MCI recognition based on brain functional networks. Specifically, we first extract spatiotemporal features between brain functional signals and FBNs by designing a spatiotemporal convolution strategy (ST-CONV). Then, on this basis, we introduce a learned attention mechanism to further capture brain nodes strongly correlated with MCI. Finally, we fuse spatiotemporal features for MCI recognition. The entire network is trained in an end-to-end fashion. Extensive experiments show that our proposed method significantly outperforms current baselines and state-of-the-art methods, with a classification accuracy of 84.21%.

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Section: Discussionmentioning

confidence: 93%

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

Feng

Huang

Le³

et al. 2022

Front. Aging Neurosci.

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“…The IPL, including the ANG, is regarded as a hub for information transmission and integration 99 . Numerous investigations have revealed that IPL is associated with a wide variety of cognitive impairments 100 – 102 . Meanwhile, several studies have found altered FC of the IPL in migraineurs than in healthy controls 103 – 105 .…”

Section: Discussionmentioning

confidence: 99%

Altered functional brain network patterns in patients with migraine without aura after transcutaneous auricular vagus nerve stimulation

Rao

Liu

Zhu

et al. 2023

Sci Rep

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Transcutaneous auricular vagus nerve stimulation (taVNS) shows excellent effects on relieving clinical symptoms in migraine patients. Nevertheless, the neurological mechanisms of taVNS for migraineurs remain unclear. In recent years, voxel-wise degree centrality (DC) and functional connectivity (FC) methods were extensively utilized for exploring alterations in patterns of FC in the resting-state brain. In the present study, thirty-five migraine patients without aura and thirty-eight healthy controls (HCs) were recruited for magnetic resonance imaging scans. Firstly, this study used voxel-wise DC analysis to explore brain regions where abnormalities were present in migraine patients. Secondly, for elucidating neurological mechanisms underlying taVNS in migraine, seed-based resting-state functional connectivity analysis was employed to the taVNS treatment group. Finally, correlation analysis was performed to explore the relationship between alterations in neurological mechanisms and clinical symptoms. Our findings indicated that migraineurs have lower DC values in the inferior temporal gyrus (ITG) and paracentral lobule than in healthy controls (HCs). In addition, migraineurs have higher DC values in the cerebellar lobule VIII and the fusiform gyrus than HCs. Moreover, after taVNS treatment (post-taVNS), patients displayed increased FC between the ITG with the inferior parietal lobule (IPL), orbitofrontal gyrus, angular gyrus, and posterior cingulate gyrus than before taVNS treatment (pre-taVNS). Besides, the post-taVNS patients showed decreased FC between the cerebellar lobule VIII with the supplementary motor area and postcentral gyrus compared with the pre-taVNS patients. The changed FC of ITG-IPL was significantly related to changes in headache intensity. Our study suggested that migraine patients without aura have altered brain connectivity patterns in several hub regions involving multisensory integration, pain perception, and cognitive function. More importantly, taVNS modulated the default mode network and the vestibular cortical network related to the dysfunctions in migraineurs. This paper provides a new perspective on the potential neurological mechanisms and therapeutic targets of taVNS for treating migraine.

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“…The IPL supports an extensive range of cognitive functions, including visuospatial attention, memory, motor planning, and mathematical cognition (Uddin et al, 2010 ). The left IPL, vital for the storage of visual short‐term memory (Chen et al, 2021 ; Henson et al, 2000 ; Todd & Marois, 2004 ), is considered a promising biomarker to distinguish aMCI from HC (Hänggi et al, 2011 ). Particularly, the peak MNI coordinate of IPL in our study was located in the angular gyrus.…”

Section: Discussionmentioning

confidence: 99%

Alterations of voxel‐wise spontaneous activity and corresponding brain functional networks in multiple system atrophy patients with mild cognitive impairment

Liu

et al. 2022

Human Brain Mapping

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Emerging evidence has indicated that cognitive impairment is an underrecognized feature of multiple system atrophy (MSA). Mild cognitive impairment (MCI) is related to a high risk of dementia. However, the mechanism underlying MCI in MSA remains controversial. In this study, we conducted the amplitude of low‐frequency fluctuation (ALFF) and seed‐based functional connectivity (FC) analyses to detect the characteristics of local neural activity and corresponding network alterations in MSA patients with MCI (MSA‐MCI). We enrolled 80 probable MSA patients classified as cognitively normal (MSA‐NC, n = 36) and MSA‐MCI ( n = 44) and 40 healthy controls. Compared with MSA‐NC, MSA‐MCI exhibited decreased ALFF in the right dorsal lateral prefrontal cortex (RDLPFC) and increased ALFF in the right cerebellar lobule IX and lobule IV–V. In the secondary FC analyses, decreased FC in the left inferior parietal lobe (IPL) was observed when we set the RDLPFC as the seed region. Decreased FC in the bilateral cuneus, left precuneus, and left IPL and increased FC in the right middle temporal gyrus were shown when we set the right cerebellar lobule IX as the seed region. Furthermore, FC of DLPFC‐IPL and cerebello‐cerebral circuit, as well as ALFF alterations, were significantly correlated with Montreal Cognitive Assessment scores in MSA patients. We also employed whole‐brain voxel‐based morphometry analysis, but no gray matter atrophy was detected between the patient subgroups. Our findings indicate that altered spontaneous activity in the DLPFC and the cerebellum and disrupted DLPFC‐IPL, cerebello‐cerebral networks are possible biomarkers of early cognitive decline in MSA patients.

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Altered mismatch response of inferior parietal lobule in amnestic mild cognitive impairment: A magnetoencephalographic study

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 6 publications

References 70 publications

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

Altered functional brain network patterns in patients with migraine without aura after transcutaneous auricular vagus nerve stimulation

Alterations of voxel‐wise spontaneous activity and corresponding brain functional networks in multiple system atrophy patients with mild cognitive impairment

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