scholarly journals Electrophysiological foundations of the human default-mode network revealed by brain-wide intracranial-EEG recordings during resting-state and cognition

2020 ◽  
Author(s):  
Anup Das ◽  
Carlo de los Angeles ◽  
Vinod Menon
Keyword(s):  
Slow Wave ◽  
Default Mode Network ◽  
Verbal Memory ◽  
Resting State ◽  
Large Scale ◽  
Phase Synchronization ◽  
Functional Organization ◽  
Memory Encoding ◽  
Intracranial Eeg ◽  
Default Mode

AbstractInvestigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the brain-wide electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used brain-wide intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during the resting-state and cognition. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz) while DMN interactions with other brain networks was higher in all higher frequencies. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during verbal memory encoding and recall. Compared to resting-state, intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify dynamic spectro-temporal network features that allow the DMN to maintain a balance between stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the neurophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

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 Functional Parcellation of the Default Mode Network: A Large-Scale Meta-Analysis

2017 ◽  
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

AbstractThe 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 Default Mode Network in Temporal Lobe epilepsy: interactions with memory performance

2017 ◽  
Author(s):  
Tamires Araujo Zanão ◽  
Tátila Martins Lopes ◽  
Brunno Machado de Campos ◽  
Mateus Henrique Nogueira ◽  
Clarissa Lin Yasuda ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Temporal Lobe Epilepsy ◽  
Left Hemisphere ◽  
Temporal Lobe ◽  
Default Mode Network ◽  
Verbal Memory ◽  
Resting State ◽  
Visual Memory ◽  
Hippocampal Sclerosis ◽  
Default Mode

ABSTRACTObjectiveto investigate abnormal functional connectivity in the resting-state default mode network (DMN) and its relation to memory impairments in patients with temporal lobe epilepsy with and without hippocampal sclerosis (HS)Methodwe enrolled 122 MTLE patients divided into right-HS (n=42), left-HS (n=49), MRI-negative MTLE (n=31) and controls (n=69). All underwent resting-state seed-based connectivity fMRI, with a seed placed at the posterior cingulate cortex, an essential node for the DMN. In addition, patients and 41 controls were tested for verbal and visual memory, estimated intelligence coefficient and delayed recall.ResultsBoth right-HS and MRI-negative group presented the poorest visual memory scores, and right-HS and left-HS had a worse performance in verbal memory compared to controls and MRI-negative groups. As expected, hippocampus was less connected than controls in all groups of patients. Although EEGs indicated that 64.5% of MRI-negative patients were lateralized to the left, this group showed activations similar to the right-HS.ConclusionOur data suggest that there is a disruption of the normal pattern of DMN in MTLE. Patients with left and right-HS presented similar, increased and decreased connectivity in the ipsilateral hemisphere; however, left-HS had abnormal decreased connectivity in the contralateral hemisphere. Per neuropsychological examination, the presence of HS in the left hemisphere had more impact on verbal memory, which was not found when the seizure focus is in the left hemisphere in the absence of HS. The absence of hippocampal atrophy seems to yield a less prominent disruption in both functional connectivity and neuropsychological performance.

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

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4098
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 ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Network ◽  
Default Mode ◽  
The Mean

Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. 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 DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1–3 Hz), theta (4–8 Hz), alpha (8–12 Hz), low beta (13–21 Hz), and high beta (22–30 Hz). 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 (p = 0.009) and alpha (p = 0.001) 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, HC exhibited higher resting-state connectivity at the 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, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = −0.689, p = 0.001. 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.

scholarly journals Increased resting state connectivity in the anterior default mode network of idiopathic epileptic dogs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Katrin M. Beckmann ◽  
Adriano Wang-Leandro ◽  
Henning Richter ◽  
Rima N. Bektas ◽  
Frank Steffen ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Group Level ◽  
Resting State Networks ◽  
Default Mode ◽  
Starting Point ◽  
Healthy Control ◽  
Large Scale Networks

AbstractEpilepsy is one of the most common chronic, neurological diseases in humans and dogs and considered to be a network disease. In human epilepsy altered functional connectivity in different large-scale networks have been identified with functional resting state magnetic resonance imaging. Since large-scale resting state networks have been consistently identified in anesthetised dogs’ application of this technique became promising in canine epilepsy research. The aim of the present study was to investigate differences in large-scale resting state networks in epileptic dogs compared to healthy controls. Our hypothesis was, that large-scale networks differ between epileptic dogs and healthy control dogs. A group of 17 dogs (Border Collies and Greater Swiss Mountain Dogs) with idiopathic epilepsy was compared to 20 healthy control dogs under a standardized sevoflurane anaesthesia protocol. Group level independent component analysis with dimensionality of 20 components, dual regression and two-sample t test were performed and revealed significantly increased functional connectivity in the anterior default mode network of idiopathic epileptic dogs compared to healthy control dogs (p = 0.00060). This group level differences between epileptic dogs and healthy control dogs identified using a rather simple data driven approach could serve as a starting point for more advanced resting state network analysis in epileptic dogs.

Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity

2013 ◽  
Vol 44 (10) ◽  
pp. 2041-2051 ◽  
Author(s):  
F. Sambataro ◽  
N. D. Wolf ◽  
M. Pennuto ◽  
N. Vasic ◽  
R. C. Wolf
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Critical Role ◽  
Low Frequency ◽  
Network Connectivity ◽  
Brain Regions ◽  
Default Mode ◽  
Network Function ◽  
Functional Relevance

BackgroundMajor depressive disorder (MDD) is characterized by alterations in brain function that are identifiable also during the brain's ‘resting state’. One functional network that is disrupted in this disorder is the default mode network (DMN), a set of large-scale connected brain regions that oscillate with low-frequency fluctuations and are more active during rest relative to a goal-directed task. Recent studies support the idea that the DMN is not a unitary system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in depression, however, is unclear.MethodHere, we investigated the functional connectivity of distinct DMN subsystems and their interplay in depression using resting-state functional magnetic resonance imaging.ResultsWe show that patients with MDD exhibit increased within-network connectivity in posterior, ventral and core DMN subsystems along with reduced interplay from the anterior to the ventral DMN subsystems.ConclusionsThese data suggest that MDD is characterized by alterations of subsystems within the DMN as well as of their interactions. Our findings highlight a critical role of DMN circuitry in the pathophysiology of MDD, thus suggesting these subsystems as potential therapeutic targets.

Sign in / Sign up

Export Citation Format

Share Document