scholarly journals Transcranial stimulation of alpha oscillations up-regulates the default mode network

2021 ◽  
Vol 119 (1) ◽  
pp. e2110868119
Author(s):  
Kevin J. Clancy ◽  
Jeremy A. Andrzejewski ◽  
Yuqi You ◽  
Jens T. Rosenberg ◽  
Mingzhou Ding ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Functional Organization ◽  
Oscillatory Activity ◽  
High Definition ◽  
Alpha Oscillations ◽  
Default Mode ◽  
Effective Interventions ◽  
Transcranial Alternating Current Stimulation ◽  
Source Level ◽  
Eeg Alpha

The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain’s functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.

scholarly journals Transcranial stimulation of alpha oscillations upregulates the default mode network

2021 ◽  
Author(s):  
Kevin J. Clancy ◽  
Jeremy A. Andrzejewski ◽  
Jens T. Rosenberg ◽  
Mingzhou Ding ◽  
Wen Li
Keyword(s):  
Default Mode Network ◽  
Functional Organization ◽  
Oscillatory Activity ◽  
High Definition ◽  
Alpha Oscillations ◽  
Default Mode ◽  
Effective Interventions ◽  
Transcranial Alternating Current Stimulation ◽  
Source Level ◽  
Eeg Alpha

The default mode network (DMN) is the most prominent intrinsic connectivity network, serving as a key architecture of the brain's functional organization. Conversely, dysregulation of the DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly, alpha (8-12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition (HD) alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous EEG-fMRI, we demonstrated that α-tACS (vs. sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can upregulate the DMN further highlights an effective non-invasive intervention to normalize DMN functioning in various disorders.

The default mode network and EEG alpha oscillations: An independent component analysis

2011 ◽  
Vol 1402 ◽  
pp. 67-79 ◽  
Author(s):  
Gennady G. Knyazev ◽  
Jaroslav Y. Slobodskoj-Plusnin ◽  
Andrey V. Bocharov ◽  
Liudmila V. Pylkova
Keyword(s):  
Independent Component Analysis ◽  
Default Mode Network ◽  
Component Analysis ◽  
Independent Component ◽  
Alpha Oscillations ◽  
Default Mode ◽  
Eeg Alpha

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 Alteration of Cortical Functional Networks in Default-Mode Network-Related Regions in Mood Disorders with Resting-State Electroencephalography

2020 ◽  
Author(s):  
Sungkean Kim ◽  
Ji Hyun Baek ◽  
Se-hoon Shim ◽  
Young Joon Kwon ◽  
Hwa Young Lee ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Functional Networks ◽  
Global Level ◽  
Beta Band ◽  
Default Mode ◽  
Source Level ◽  
The Right ◽  
High Beta ◽  
Nodal Level

Abstract Studies comparing bipolar disorder (BD) and major depressive disorder (MDD) are scarce, and the neuropathology of these disorders is poorly understood. This study investigated source-level cortical functional networks using resting-state electroencephalography (EEG) in patients with BD and MDD. EEG was recorded in 35 patients with BD, 39 patients with MDD, and 42 healthy controls (HCs). Graph theory-based source-level weighted functional networks were assessed via strength, clustering coefficient (CC), and path length (PL) in six frequency bands. At the global level, patients with BD and MDD showed higher strength and CC, and lower PL in the high beta band, compared to HCs. At the nodal level, compared to HCs, patients with BD showed higher high beta band nodal CCs in the right precuneus, left isthmus cingulate, bilateral paracentral, and left superior frontal, belonging to the default-mode network (DMN); however, patients with MDD showed higher nodal CC only in the right precuneus compared to HCs. Although both MDD and BD patients had similar global level network changes, they had different nodal level network changes in DMN-related regions. Our findings might suggest more altered network in the DMN-related regions in patients with BD than in those with MDD.

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.

BOLD correlates of EEG alpha phase-locking and the fMRI default mode network

NeuroImage ◽  
2009 ◽  
Vol 45 (3) ◽  
pp. 903-916 ◽  
Author(s):  
K. Jann ◽  
T. Dierks ◽  
C. Boesch ◽  
M. Kottlow ◽  
W. Strik ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Phase Locking ◽  
Alpha Phase ◽  
Default Mode ◽  
Eeg Alpha

scholarly journals Resting-state Modulation of Alpha Rhythms by Interference with Angular Gyrus Activity

2014 ◽  
Vol 26 (1) ◽  
pp. 107-119 ◽  
Author(s):  
Paolo Capotosto ◽  
Claudio Babiloni ◽  
Gian Luca Romani ◽  
Maurizio Corbetta
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Low Frequency ◽  
Angular Gyrus ◽  
Alpha Power ◽  
Default Mode ◽  
Dorsal Attention Network ◽  
Left And Right ◽  
Eeg Alpha ◽  
Adult Volunteers

The default mode network is active during restful wakefulness and suppressed during goal-driven behavior. We hypothesize that inhibitory interference with spontaneous ongoing, that is, not task-driven, activity in the angular gyrus (AG), one of the core regions of the default mode network, will enhance the dominant idling EEG alpha rhythms observed in the resting state. Fifteen right-handed healthy adult volunteers underwent to this study. Compared with sham stimulation, magnetic stimulation (1 Hz for 1 min) over both left and right AG, but not over FEF or intraparietal sulcus, core regions of the dorsal attention network, enhanced the dominant alpha power density (8–10 Hz) in occipitoparietal cortex. Furthermore, right AG-rTMS enhanced intrahemispheric alpha coherence (8–10 Hz). These results suggest that AG plays a causal role in the modulation of dominant low-frequency alpha rhythms in the resting-state condition.

scholarly journals Alpha oscillatory activity causally linked to working memory retention: insights from online phase-locking closed-loop transcranial alternating current stimulation (tACS)

2021 ◽  
Author(s):  
Xueli Chen ◽  
Ru Ma ◽  
Wei Zhang ◽  
Qianying Wu ◽  
Ajiguli Yimiti ◽  
...  
Keyword(s):  
Working Memory ◽  
Closed Loop ◽  
Phase Locking ◽  
Alternating Current ◽  
Causal Link ◽  
Oscillatory Activity ◽  
Memory Retention ◽  
Alpha Oscillations ◽  
Transcranial Alternating Current Stimulation ◽  
Retention Intervals

Although previous studies have reported correlations between alpha oscillations and the "retention" sub-process of working memory (WM), no direct causal evidence has been established in human neuroscience. Here, we developed an online phase-locking closed-loop transcranial alternating current stimulation (tACS) system capable of precisely controlling the phase difference between tACS and concurrent endogenous oscillations. This system permits both up- and down-regulation of brain oscillations at the target stimulation frequency, and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to 39 participants during the retention intervals of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. Moreover, the in-phase tACS-induced changes in WM performance were positively correlated with alpha oscillatory activity. These findings strongly support a causal link between alpha oscillations and WM retention, and illustrate the broad application prospects of phase-locking tACS.

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