Graph slepians to probe into large-scale network organization of resting-state functional connectivity

The default mode network (DMN) is the main large-scale network of the resting brain and the PCC/precuneus is a major hub of this network. Glutamate and GABA (γ-amino butyric acid) are the main excitatory and inhibitory neurotransmitters in the CNS, respectively. We studied glutamate and GABA concentrations in the PCC/precuneus via magnetic resonance spectroscopy (MRS) at 7T in relation to age and correlated them with functional connectivity between this region and other DMN nodes in ten healthy right-handed volunteers ranging in age between 23–68 years. Mean functional connectivity of the PCC/precuneus to the other DMN nodes and the glutamate/GABA ratio significantly correlated with age (r = 0.802, p = 0.005 and r = 0.793, p = 0.006, respectively) but not with each other. Glutamate and GABA alone did not significantly correlate with age nor with functional connectivity within the DMN. The glutamate/GABA ratio and functional connectivity of the PCC/precuneus are, therefore, independent age-related biomarkers of the DMN and may be combined in a multimodal pipeline to study DMN alterations in various disease states.

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Large-scale network organization of EEG functional connectivity in newborn infants

Human Brain Mapping ◽

10.1002/hbm.23645 ◽

2017 ◽

Vol 38 (8) ◽

pp. 4019-4033 ◽

Cited By ~ 22

Author(s):

Brigitta Tóth ◽

Gábor Urbán ◽

Gábor P. Háden ◽

Molnár Márk ◽

Miklós Török ◽

...

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Newborn Infants ◽

Network Organization ◽

Large Scale Network ◽

Scale Network ◽

Eeg Functional Connectivity

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Networks of worry—towards a connectivity-based signature of late-life worry using higher criticism

Translational Psychiatry ◽

10.1038/s41398-021-01648-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Andrew R. Gerlach ◽

Helmet T. Karim ◽

Joseph Kazan ◽

Howard J. Aizenstein ◽

Robert T. Krafty ◽

...

Keyword(s):

Older Adults ◽

Functional Connectivity ◽

Resting State ◽

Large Scale ◽

Resting State Fmri ◽

Anterior Cingulate ◽

Resting State Functional Connectivity ◽

Targeted Interventions ◽

Higher Criticism ◽

Large Scale Network

AbstractSevere worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults.

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Attention network modulation via tRNS correlates with attention gain

eLife ◽

10.7554/elife.63782 ◽

2021 ◽

Vol 10 ◽

Author(s):

Federica Contò ◽

Grace Edwards ◽

Sarah Tyler ◽

Danielle Parrott ◽

Emily Grossman ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Large Scale ◽

Random Noise ◽

Cognitive Capacity ◽

Resting State Functional Connectivity ◽

Attention Network ◽

Transcranial Random Noise Stimulation ◽

The Impact ◽

Behavioral Improvement

Transcranial random noise stimulation (tRNS) can enhance vision in the healthy and diseased brain. Yet, the impact of multi-day tRNS on large-scale cortical networks is still unknown. We investigated the impact of tRNS coupled with behavioral training on resting-state functional connectivity and attention. We trained human subjects for 4 consecutive days on two attention tasks, while receiving tRNS over the intraparietal sulci, the middle temporal areas, or Sham stimulation. We measured resting-state functional connectivity of nodes of the dorsal and ventral attention network (DVAN) before and after training. We found a strong behavioral improvement and increased connectivity within the DVAN after parietal stimulation only. Crucially, behavioral improvement positively correlated with connectivity measures. We conclude changes in connectivity are a marker for the enduring effect of tRNS upon behavior. Our results suggest that tRNS has strong potential to augment cognitive capacity in healthy individuals and promote recovery in the neurological population.

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Childhood Trauma and Functional Connectivity between Amygdala and Medial Prefrontal Cortex: A Dynamic Functional Connectivity and Large-Scale Network Perspective

Frontiers in Systems Neuroscience ◽

10.3389/fnsys.2017.00029 ◽

2017 ◽

Vol 11 ◽

Cited By ~ 14

Author(s):

Josh M. Cisler

Keyword(s):

Prefrontal Cortex ◽

Functional Connectivity ◽

Childhood Trauma ◽

Medial Prefrontal Cortex ◽

Large Scale ◽

Dynamic Functional Connectivity ◽

Large Scale Network ◽

Scale Network

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Sex-specific differences in resting-state functional connectivity of large-scale networks in postconcussion syndrome

Scientific Reports ◽

10.1038/s41598-020-77137-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Reema Shafi ◽

Adrian P. Crawley ◽

Maria Carmela Tartaglia ◽

Charles H. Tator ◽

Robin E. Green ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Large Scale ◽

Brain Regions ◽

Healthy Controls ◽

Postconcussion Syndrome ◽

Resting State Functional Connectivity ◽

Post Injury ◽

Network Nodes ◽

Specific Impact

AbstractConcussions are associated with a range of cognitive, neuropsychological and behavioral sequelae that, at times, persist beyond typical recovery times and are referred to as postconcussion syndrome (PCS). There is growing support that concussion can disrupt network-based connectivity post-injury. To date, a significant knowledge gap remains regarding the sex-specific impact of concussion on resting state functional connectivity (rs-FC). The aims of this study were to (1) investigate the injury-based rs-FC differences across three large-scale neural networks and (2) explore the sex-specific impact of injury on network-based connectivity. MRI data was collected from a sample of 80 concussed participants who fulfilled the criteria for postconcussion syndrome and 31 control participants who did not have any history of concussion. Connectivity maps between network nodes and brain regions were used to assess connectivity using the Functional Connectivity (CONN) toolbox. Network based statistics showed that concussed participants were significantly different from healthy controls across both salience and fronto-parietal network nodes. More specifically, distinct subnetwork components were identified in the concussed sample, with hyperconnected frontal nodes and hypoconnected posterior nodes across both the salience and fronto-parietal networks, when compared to the healthy controls. Node-to-region analyses showed sex-specific differences across association cortices, however, driven by distinct networks. Sex-specific network-based alterations in rs-FC post concussion need to be examined to better understand the underlying mechanisms and associations to clinical outcomes.

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