Predicting depression based on dynamic regional connectivity: A windowed Granger causality analysis of MEG recordings

Lü, Qing; Bi, Ke; Chu, Liu; Luo, Guoping; Tang, Hao; Yao, Zhijian

doi:10.1016/j.brainres.2013.08.033

Cited by 52 publications

(19 citation statements)

References 40 publications

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“…Furthermore, cortical activity of the visual perception network is thought to suppress subcortical emotional activity by cortical feedback [73]. In support of our EEG results, a magnetoencephalography study using connectivity analysis showed that major depressive disorder was characterized by enhanced activity of the amygdala and reduced inhibitory connectivity from the inferior frontal cortex to the amygdala during exposure to sad facial stimuli [74]. Taken together, these results and ours suggest that a reduction in visual perception network activity might lead to depression and increased anxiety associated with reduced cortical inhibitory feedback to subcortical emotional regions.…”

Section: Discussionsupporting

confidence: 69%

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

et al. 2019

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Background: Dementia with Lewy bodies (DLB) is characterized by progressive cognitive decline, fluctuating cognition, visual hallucinations, rapid eye movement sleep behavior disorder, and parkinsonism. DLB is the second most common type of degenerative dementia of all dementia cases. However, DLB, particularly in the early stage, is underdiagnosed and sometimes misdiagnosed with other types of dementia. Thus, it is of great interest investigating neurophysiological markers of DLB. Method: We introduced exact low-resolution brain electromagnetic tomography (eLORETA)-independent component analysis (ICA) to assess activities of 5 electroencephalography (EEG) resting-state networks (RSNs) in 41 drug-free DLB patients. Results: Compared to 80 healthy controls, DLB patients had significantly decreased activities in occipital visual and sensorimotor networks, where DLB patients and healthy controls showed no age dependences in all EEG-RSN activities. Also, we found correlations between all EEG-RSN activities and DLB symptoms. Specifically, decreased occipital α activity showed correlations with worse brain functions related to attention/concentration, visuospatial discrimination, and global cognition. Enhanced visual perception network activity correlated with milder levels of depression and anxiety. Enhanced self-referential network activity correlated with milder levels of depression. Enhanced memory perception network activity correlated with better semantic memory, visuospatial discrimination function, and global cognitive function as well as with severer visual hallucination. In addition, decreased sensorimotor network activity correlated with a better semantic memory. Conclusion: These results indicate that eLORETA-ICA can detect EEG-RSN activity alterations in DLB related to symptoms. Therefore, eLORETA-ICA with EEG data can be a useful noninvasive tool for sensitive detection of EEG-RSN activity changes characteristic of DLB and for understanding the neurophysiological mechanisms underlying this disease.

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Section: Discussionsupporting

confidence: 69%

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

et al. 2019

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“…The disruption may contribute to the dysfunction of visual recognition and selective attention in MDD 3 5 35 . Previous GC analysis demonstrated abnormal effective connectivity in fronto-occipital network 48 . Our results further found the abnormally elevated causal influence from ORBinf to the visual sensory areas, and this aberrant influence increased progressively over the illness severity in MDD.…”

Section: Discussionmentioning

confidence: 89%

Causal connectivity alterations of cortical-subcortical circuit anchored on reduced hemodynamic response brain regions in first-episode drug-naïve major depressive disorder

Gao

Sun

et al. 2016

Sci Rep

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Some efforts were done to investigate the disruption of brain causal connectivity networks involved in major depressive disorder (MDD) using Granger causality (GC) analysis. However, the homogenous hemodynamic response function (HRF) assumption over the brain may disturb the inference of temporal precedence. Here we applied a blind deconvolution approach to examine the altered HRF shape in first-episode, drug-naïve MDD patients. The regions with abnormal HRF shape in patients were chosen as seeds to detect the GC alterations in MDD. The results demonstrated significantly decreased magnitude of spontaneous hemodynamic response of the orbital frontal cortex (OFC) and the caudate nucleus (CAU) in MDD comparing to healthy controls, suggesting MDD patients likely had alterations in neurovascular coupling and cerebrovascular physiology in these two regions. GC mapping showed increased/decreased GC in OFC-/CAU centered networks in MDD. The outgoing GC values from OFC to anterior cingulate cortex and occipital regions were positively correlated with Hamilton Depression Scale (HAMD) scores, while the incoming GC from insula, middle and superior temporal gyrus to CAU were negatively correlated with HAMD scores of MDD. The abnormalities of directional connections in the cortico-subcortico-cerebellar network may lead to unbalanced integrating the emotional-related information for MDD, and further exacerbating depressive symptoms.

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“…In addition, MEG connectivity between the amygdala, ACC, inferior frontal gyrus, and visual cortex in response to sad facial stimuli has been investigated using multiple sparse prior source estimation and Granger causality analysis. Relative to controls, MDD was characterized by an enhanced connectivity of the amygdala after exposure to sad facial stimuli in the early stage and reduced inhibitory connectivity from the inferior frontal cortex to the amygdala in the late stage (Lu et al 2013). Taking these findings into consideration, abnormal connectivity of the amygdala and the thalamus with the DMN appears to be a key feature of MDD and may reflect the increased emotional processing seen in MDD, including rumination and brooding.…”

Section: Major Depressive Disordermentioning

confidence: 96%

The Role of Functional Networks in Neuropsychiatric Disorders

Canuet¹,

Aoki

Ishii

et al. 2016

Multimodal Oscillation-Based Connectivity Theory

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Predicting depression based on dynamic regional connectivity: A windowed Granger causality analysis of MEG recordings

Cited by 52 publications

References 40 publications

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

Causal connectivity alterations of cortical-subcortical circuit anchored on reduced hemodynamic response brain regions in first-episode drug-naïve major depressive disorder

The Role of Functional Networks in Neuropsychiatric Disorders

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