scholarly journals Disruptions in effective connectivity within and between default mode network and anterior forebrain mesocircuit in prolonged disorders of consciousness

2021 ◽  
Author(s):  
Sean Coulborn ◽  
Chris Taylor ◽  
Lorina Naci ◽  
Adrian M Owen ◽  
Davinia Fernandez-Espejo
Keyword(s):  
Default Mode Network ◽  
Empirical Bayes ◽  
Effective Connectivity ◽  
Disorders Of Consciousness ◽  
Fmri Data ◽  
Functional Impairments ◽  
Default Mode ◽  
Causal Modelling ◽  
Inferior Parietal Cortex ◽  
Anterior Forebrain

Recent research indicates prolonged disorders of consciousness (PDOC) result from structural and functional impairments to key cortical and subcortical networks including the default mode network (DMN) and the anterior forebrain mesocircuit (AFM). However, the specific mechanisms which underpin such impairments remain unknown. It is known that disruptions in the striatal-pallidal pathway can result in the over inhibition of the thalamus and lack of excitation to the cortex that characterises PDOC. Here, we used spectral dynamic causal modelling and parametric empirical Bayes on rs-fMRI data to assess whether DMN changes in PDOC are caused by disruptions in the AFM. PDOC patients displayed overall reduced coupling within the AFM, and specifically, decreased self-inhibition of the striatum paired with reduced coupling from striatum to thalamus. This led to loss of inhibition from AFM to DMN, mostly driven by posterior areas including the precuneus and inferior parietal cortex. In turn, the DMN showed disruptions in self-inhibition of the precuneus and medial prefrontal cortex. Our results provide support for the anterior mesocircuit model at the subcortical level but highlight an inhibitory role for the AFM over the DMN, which is disrupted in PDOC.

scholarly journals Disruptions in Effective Connectivity within and between Default Mode Network and Anterior Forebrain Mesocircuit in Prolonged Disorders of Consciousness

2021 ◽  
Vol 11 (6) ◽  
pp. 749
Author(s):  
Sean Coulborn ◽  
Chris Taylor ◽  
Lorina Naci ◽  
Adrian M. Owen ◽  
Davinia Fernández-Espejo
Keyword(s):  
Default Mode Network ◽  
Empirical Bayes ◽  
Effective Connectivity ◽  
Disorders Of Consciousness ◽  
Fmri Data ◽  
Functional Impairments ◽  
Default Mode ◽  
Causal Modelling ◽  
Inferior Parietal Cortex ◽  
Anterior Forebrain

Recent research indicates prolonged disorders of consciousness (PDOC) result from structural and functional impairments to key cortical and subcortical networks, including the default mode network (DMN) and the anterior forebrain mesocircuit (AFM). However, the specific mechanisms which underpin such impairments remain unknown. It is known that disruptions in the striatal-pallidal pathway can result in the over inhibition of the thalamus and lack of excitation to the cortex that characterizes PDOC. Here, we used spectral dynamic causal modelling and parametric empirical Bayes on rs-fMRI data to assess whether DMN changes in PDOC are caused by disruptions in the AFM. PDOC patients displayed overall reduced coupling within the AFM, and specifically, decreased self-inhibition of the striatum, paired with reduced coupling from striatum to thalamus. This led to loss of inhibition from AFM to DMN, mostly driven by posterior areas including the precuneus and inferior parietal cortex. In turn, the DMN showed disruptions in self-inhibition of the precuneus and medial prefrontal cortex. Our results provide support for the anterior mesocircuit model at the subcortical level but highlight an inhibitory role for the AFM over the DMN, which is disrupted in PDOC.

scholarly journals Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

2016 ◽  
Vol 10 ◽  
Author(s):  
Maksim G. Sharaev ◽  
Viktoria V. Zavyalova ◽  
Vadim L. Ushakov ◽  
Sergey I. Kartashov ◽  
Boris M. Velichkovsky
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Fmri Data ◽  
Network Dynamic ◽  
Dynamic Causal Modeling ◽  
Default Mode

scholarly journals Relationship between the anterior forebrain mesocircuit and the default mode network in the structural bases of disorders of consciousness

2016 ◽  
Vol 10 ◽  
pp. 27-35 ◽  
Author(s):  
Nicholas D. Lant ◽  
Laura E. Gonzalez-Lara ◽  
Adrian M. Owen ◽  
Davinia Fernández-Espejo
Keyword(s):  
Default Mode Network ◽  
Disorders Of Consciousness ◽  
Default Mode ◽  
Anterior Forebrain

scholarly journals Neurophysiology (fMRI)

2015 ◽  
Vol 42 (S1) ◽  
pp. S38-S38
Author(s):  
ST Lang ◽  
B Goodyear ◽  
J Kelly ◽  
P Federico
Keyword(s):  
Cognitive Functioning ◽  
Default Mode Network ◽  
Resting State ◽  
Attentional Control ◽  
Brain Tumours ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Resting State Networks ◽  
Default Mode ◽  
Eloquent Cortex

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

scholarly journals Task-Dependent Modulation of Effective Connectivity within the Default Mode Network

2012 ◽  
Vol 3 ◽  
Author(s):  
Baojuan Li ◽  
Xiang Wang ◽  
Shuqiao Yao ◽  
Dewen Hu ◽  
Karl Friston
Keyword(s):  
Default Mode Network ◽  
Effective Connectivity ◽  
Default Mode

scholarly journals Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study

2021 ◽  
Author(s):  
Abdulhakim Al-Ezzi ◽  
Nidal Kamel ◽  
Ibrahima Faye ◽  
Esther Gunaseli
Keyword(s):  
Anxiety Disorder ◽  
Social Anxiety ◽  
Social Anxiety Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Mean Values ◽  
Default Mode ◽  
Severe Group ◽  
The Mean

Several neuroimaging findings by using different modalities (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, these modalities do not quantify the fast dynamic connectivity of causal information networks due to their poor temporal resolution. In this study, SAD-related changes in brain connections within the default mode network (DMN) was investigated using Electroencephalogram (EEG). Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The EEG data were collected from 88 subjects (control, mild, moderate, severe) and used to estimate the effective connectivity between DMN regions at different frequency bands. Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta and alpha bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, the HC exhibited higher resting-state connectivity at the mesial prefrontal cortex (mPFC), providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group and negatively correlated with those of the HC group. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

IC-P-031: EFFECTIVE CONNECTIVITY WITHIN THE DEFAULT MODE NETWORK IN MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE

2006 ◽  
Vol 14 (7S_Part_1) ◽  
pp. P35-P36
Author(s):  
Cole John Cook ◽  
Gyujoon Hwang ◽  
Veena A. Nair ◽  
Andrew L. Alexander ◽  
Piero G. Antuono ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Default Mode Network ◽  
Effective Connectivity ◽  
Default Mode

scholarly journals Alpha dependent effective connectivity in the default mode network of resting state MEG

IBRO Reports ◽  
2019 ◽  
Vol 6 ◽  
pp. S171
Author(s):  
Junho Son ◽  
Chongwon Pae ◽  
Jiyoung Kang ◽  
Jinseok Eo ◽  
Hae-Jeong Park
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Default Mode
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