scholarly journals Dynamic connectivity modulates local activity in the core regions of the default-mode network

2017 ◽  
Vol 114 (36) ◽  
pp. 9713-9718 ◽  
Author(s):  
Wei Tang ◽  
Hesheng Liu ◽  
Linda Douw ◽  
Mark A. Kramer ◽  
Uri T. Eden ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Anterior Cingulate ◽  
Default Mode ◽  
Local Activity ◽  
The Core ◽  
Dynamic Connectivity

Segregation and integration are distinctive features of large-scale brain activity. Although neuroimaging studies have been unraveling their neural correlates, how integration takes place over segregated modules remains elusive. Central to this problem is the mechanism by which a brain region adjusts its activity according to the influence it receives from other regions. In this study, we explore how dynamic connectivity between two regions affects the neural activity within a participating region. Combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same group of subjects, we analyzed resting-state data from the core of the default-mode network. We observed directed influence from the posterior cingulate cortex (PCC) to the anterior cingulate cortex (ACC) in the 10-Hz range. This time-varying influence was associated with the power alteration in the ACC: strong influence corresponded with a decrease of power around 13–16 Hz and an increase of power in the lower (1–7 Hz) and higher (30–55 Hz) ends of the spectrum. We also found that the amplitude of the 30- to 55-Hz activity was coupled to the phase of the 3- to 4-Hz activity in the ACC. These results characterized the local spectral changes associated with network interactions. The specific spectral information both highlights the functional roles of PCC–ACC connectivity in the resting state and provides insights into the dynamic relationship between local activity and coupling dynamics of a network.

scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Cortical and subcortical changes in resting-state functional connectivity before and during an episode of postoperative delirium

2019 ◽  
Vol 53 (8) ◽  
pp. 794-806 ◽  
Author(s):  
Jooyoung Oh ◽  
Jung Eun Shin ◽  
Kyu Hyun Yang ◽  
Sunghyon Kyeong ◽  
Woo Suk Lee ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Default Mode Network ◽  
Resting State ◽  
Postoperative Delirium ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Default Mode ◽  
Posterior Cingulate ◽  
Subcortical Regions

Objective: Delirium is an acute brain failure related to uncertain problems in neural connectivity, including aberrant functional interactions between remote cortical regions. This study aimed to elucidate the underlying neural mechanisms of delirium by clarifying the changes in resting-state functional connectivity induced by postoperative delirium using imaging data scanned before and after surgery. Method: Fifty-eight patients with a femoral neck fracture were preoperatively scanned using resting-state functional magnetic resonance imaging. Twenty-five patients developed postoperative delirium, and 14 of those had follow-up scans during delirium. Eighteen patients without delirium completed follow-up scans 5 or 6 days after surgery. We assessed group differences in voxel-based connectivity, in which the seeds were the posterior cingulate cortex, medial prefrontal cortex and 11 subcortical regions. Connections between the subcortical regions were also examined. Results: The results showed four major findings during delirium. Both the posterior cingulate cortex and medial prefrontal cortex were strongly connected to the dorsolateral prefrontal cortex. The posterior cingulate cortex had hyperconnectivity with the inferior parietal lobule, whereas the medial prefrontal cortex had hyperconnectivity with the frontopolar cortex and hypoconnectivity with the superior frontal gyrus. Connectivity of the striatum with the anterior cingulate cortex and insula was increased. Disconnections were found between the lower subcortical regions including the neurotransmitter origins and the striatum/thalamus in the upper level. Conclusions: Our findings suggest that cortical dysfunction during delirium is characterized by a diminution of the anticorrelation between the default mode network and task-positive regions, excessive internal connections in the posterior default mode network and a complex imbalance of internal connectivity in the anterior default mode network. These dysfunctions can be attributed to the loss of reciprocity between the default mode network and central executive network associated with defective function in the salience network, which might be closely linked to aberrant subcortical neurotransmission-related connectivity and striato-cortical connectivity.

Distributed changes in default-mode resting-state connectivity in multiple sclerosis

2011 ◽  
Vol 17 (4) ◽  
pp. 411-422 ◽  
Author(s):  
Simona Bonavita ◽  
Antonio Gallo ◽  
Rosaria Sacco ◽  
Marida Della Corte ◽  
Alvino Bisecco ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Resting State ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Cognitive Status ◽  
Anterior Cingulate ◽  
Default Mode ◽  
Relapsing Remitting ◽  
Multiple Sclerosis Patients ◽  
Global And Local

Background: The default-mode network (DMN) has been increasingly recognized as relevant to cognitive status. Objectives: To explore DMN changes in patients with relapsing–remitting (RR) multiple sclerosis (MS) and to relate these to the cognitive status. Methods: Eighteen cognitively impaired (CI) and eighteen cognitively preserved (CP) RRMS patients and eighteen healthy controls (HCs), matched for age, sex and education, underwent neuropsychological evaluation and anatomical and resting-state functional MRI (rs-fMRI). DMN functional connectivity was evaluated from rs-fMRI data via independent component analysis. T2 lesion load (LL) was computed by a semi-automatic method and global and local atrophy was estimated by SIENAX and SPM8 voxel-based morphometry analyses from 3D-T1 images. Results: When the whole group of RRMS patients was compared with HCs, DMN connectivity was significantly weaker in the anterior cingulate cortex, whereas it was significantly weaker in the core but stronger at the periphery of the posterior cingulate cortex. These findings were more evident in CP than CI patients. Observed DMN changes did not correlate with global atrophy or T2-LL, but were locally associated with regional grey matter loss. Conclusion: Relapsing–remitting multiple sclerosis patients show a consistent dysfunction of DMN at the level of the anterior node. DMN distribution changes in the posterior node may reflect a possible compensatory effect on cognitive performance.

scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Author(s):  
Mohammad S.E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

AbstractBackgroundSchizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well characterized.MethodResting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.ResultsWe found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.ConclusionsTo our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

scholarly journals Resting-State Isolated Effective Connectivity of the Cingulate Cortex as a Neurophysiological Biomarker in Patients with Severe Treatment-Resistant Schizophrenia

2020 ◽  
Vol 10 (3) ◽  
pp. 89
Author(s):  
Masataka Wada ◽  
Shinichiro Nakajima ◽  
Ryosuke Tarumi ◽  
Fumi Masuda ◽  
Takahiro Miyazaki ◽  
...  
Keyword(s):  
Resting State ◽  
Effective Connectivity ◽  
Treatment Resistance ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Anterior Cingulate ◽  
Treatment Resistant ◽  
Neural Basis ◽  
Subject Factor ◽  
Post Hoc

Background: The neural basis of treatment-resistant schizophrenia (TRS) remains unclear. Previous neuroimaging studies suggest that aberrant connectivity between the anterior cingulate cortex (ACC) and default mode network (DMN) may play a key role in the pathophysiology of TRS. Thus, we aimed to examine the connectivity between the ACC and posterior cingulate cortex (PCC), a hub of the DMN, computing isolated effective coherence (iCoh), which represents causal effective connectivity. Methods: Resting-state electroencephalogram with 19 channels was acquired from seventeen patients with TRS and thirty patients with non-TRS (nTRS). The iCoh values between the PCC and ACC were calculated using sLORETA software. We conducted four-way analyses of variance (ANOVAs) for iCoh values with group as a between-subject factor and frequency, directionality, and laterality as within-subject factors and post-hoc independent t-tests. Results: The ANOVA and post-hoc t-tests for the iCoh ratio of directionality from PCC to ACC showed significant findings in delta (t45 = 7.659, p = 0.008) and theta (t45 = 8.066, p = 0.007) bands in the left side (TRS < nTRS). Conclusion: Left delta and theta PCC and ACC iCoh ratio may represent a neurophysiological basis of TRS. Given the preliminary nature of this study, these results warrant further study to confirm the importance of iCoh as a clinical indicator for treatment-resistance.

scholarly journals Functional parcellation of the default mode network: a large-scale meta-analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shaoming Wang ◽  
Lindsey J. Tepfer ◽  
Adrienne A. Taren ◽  
David V. Smith
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Default Mode Network ◽  
Large Scale ◽  
Functional Organization ◽  
Meta Analysis ◽  
Posterior Cingulate Cortex ◽  
Health Conditions ◽  
Treatment Protocols ◽  
Default Mode

Abstract The default mode network (DMN) consists of several regions that selectively interact to support distinct domains of cognition. Of the various sites that partake in DMN function, the posterior cingulate cortex (PCC), temporal parietal junction (TPJ), and medial prefrontal cortex (MPFC) are frequently identified as key contributors. Yet, it remains unclear whether these subcomponents of the DMN make unique contributions to specific cognitive processes and health conditions. To address this issue, we applied a meta-analytic parcellation approach used in prior work. This approach used the Neurosynth database and classification methods to quantify the association between PCC, TPJ, and MPFC activation and specific topics related to cognition and health (e.g., decision making and smoking). Our analyses replicated prior observations that the PCC, TPJ, and MPFC collectively support multiple cognitive functions such as decision making, memory, and awareness. To gain insight into the functional organization of each region, we parceled each region based on its coactivation pattern with the rest of the brain. This analysis indicated that each region could be further subdivided into functionally distinct subcomponents. Taken together, we further delineate DMN function by demonstrating the relative strengths of association among subcomponents across a range of cognitive processes and health conditions. A continued attentiveness to the specialization within the DMN allows future work to consider the nuances in sub-regional contributions necessary for healthy cognition, as well as create the potential for more targeted treatment protocols in various health conditions.

scholarly journals Anosognosia predicts default mode network hypometabolism and clinical progression to dementia

Neurology ◽  
2018 ◽  
Vol 90 (11) ◽  
pp. e932-e939 ◽  
Author(s):  
Joseph Therriault ◽  
Kok Pin Ng ◽  
Tharick A. Pascoal ◽  
Sulantha Mathotaarachchi ◽  
Min Su Kang ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Default Mode Network ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Amnestic Mild Cognitive Impairment ◽  
Default Mode ◽  
Posterior Cingulate ◽  
Impaired Awareness

ObjectiveTo identify the pathophysiologic mechanisms and clinical significance of anosognosia for cognitive decline in mild cognitive impairment.MethodsWe stratified 468 patients with amnestic mild cognitive impairment into intact and impaired awareness groups, determined by the discrepancy between the patient and the informant score on the Everyday Cognition questionnaire. Voxel-based linear regression models evaluated the associations between self-awareness status and baseline β-amyloid load, measured by [18F]florbetapir, and the relationships between awareness status and regional brain glucose metabolism measured by [18F]fluorodeoxyglucose at baseline and at 24-month follow-up. Multivariate logistic regression tested the association of awareness status with conversion from amnestic mild cognitive impairment to dementia.ResultsWe found that participants with impaired awareness had lower [18F]fluorodeoxyglucose uptake and increased [18F]florbetapir uptake in the posterior cingulate cortex at baseline. In addition, impaired awareness in mild cognitive impairment predicted [18F]fluorodeoxyglucose hypometabolism in the posterior cingulate cortex, left basal forebrain, bilateral medial temporal lobes, and right lateral temporal lobe over 24 months. Furthermore, participants with impaired awareness had a nearly 3-fold increase in likelihood of conversion to dementia within a 2-year time frame.ConclusionsOur results suggest that anosognosia is linked to Alzheimer disease pathophysiology in vulnerable structures, and predicts subsequent hypometabolism in the default mode network, accompanied by an increased risk of progression to dementia. This highlights the importance of assessing awareness of cognitive decline in the clinical evaluation and management of individuals with amnestic mild cognitive impairment.

Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network?

2008 ◽  
Vol 38 (8) ◽  
pp. 1185-1193 ◽  
Author(s):  
E. Pomarol-Clotet ◽  
R. Salvador ◽  
S. Sarró ◽  
J. Gomar ◽  
F. Vila ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Default Mode Network ◽  
Sense Of Self ◽  
Memory Task ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Default Mode ◽  
Schizophrenic Patients ◽  
Back Task

BackgroundFunctional imaging studies using working memory tasks have documented both prefrontal cortex (PFC) hypo- and hyperactivation in schizophrenia. However, these studies have often failed to consider the potential role of task-related deactivation.MethodThirty-two patients with chronic schizophrenia and 32 age- and sex-matched normal controls underwent functional magnetic resonance imaging (fMRI) scanning while performing baseline, 1-back and 2-back versions of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups.ResultsThe controls showed activation in the expected frontal regions. There were also clusters of deactivation, particularly in the anterior cingulate/ventromedial PFC and the posterior cingulate cortex/precuneus. Compared to the controls, the schizophrenic patients showed reduced activation in the right dorsolateral prefrontal cortex (DLPFC) and other frontal areas. There was also an area in the anterior cingulate/ventromedial PFC where the patients showed apparently greater activation than the controls. This represented a failure of deactivation in the schizophrenic patients. Failure to activate was a function of the patients' impaired performance on the n-back task, whereas the failure to deactivate was less performance dependent.ConclusionsPatients with schizophrenia show both failure to activate and failure to deactivate during performance of a working memory task. The area of failure of deactivation is in the anterior prefrontal/anterior cingulate cortex and corresponds to one of the two midline components of the ‘default mode network’ implicated in functions related to maintaining one's sense of self.

Sign in / Sign up

Export Citation Format

Share Document