scholarly journals Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation

2019 ◽  
Author(s):  
Valerio Zerbi ◽  
Amalia Floriou-Servou ◽  
Marija Markicevic ◽  
Yannick Vermeiren ◽  
Oliver Sturman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Locus Coeruleus ◽  
Large Scale ◽  
Network Connectivity ◽  
Brain Regions ◽  
Causal Link ◽  
Receptor Expression ◽  
Brain Functions ◽  
Neuropsychiatric Diseases ◽  
The Impact

AbstractThe locus coeruleus (LC) supplies norepinephrine (NE) to the entire forebrain, regulates many fundamental brain functions, and is implicated in several neuropsychiatric diseases. Although selective manipulation of the LC is not possible in humans, studies have suggested that strong LC activation might shift network connectivity to favor salience processing. To test this hypothesis, we use a mouse model to study the impact of LC stimulation on large-scale functional connectivity by combining chemogenetic activation of the LC with resting-state fMRI, an approach we term “chemo-connectomics”. LC activation rapidly interrupts ongoing behavior and strongly increases brain-wide connectivity, with the most profound effects in the salience and amygdala networks. We reveal a direct correlation between functional connectivity changes and transcript levels of alpha-1, alpha-2, and beta-1 adrenoceptors across the brain, and a positive correlation between NE turnover and functional connectivity within select brain regions. These results represent the first brain-wide functional connectivity mapping in response to LC activation, and demonstrate a causal link between receptor expression, brain states and functionally connected large-scale networks at rest. We propose that these changes in large-scale network connectivity are critical for optimizing neural processing in the context of increased vigilance and threat detection.

scholarly journals Using structural connectivity to augment community structure in EEG functional connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 761-787 ◽  
Author(s):  
Katharina Glomb ◽  
Emeline Mullier ◽  
Margherita Carboni ◽  
Maria Rubega ◽  
Giannarita Iannotti ◽  
...  
Keyword(s):  
Community Structure ◽  
White Matter ◽  
Functional Connectivity ◽  
Large Scale ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Source Analysis ◽  
Volume Conduction ◽  
Functional Relationships ◽  
The Impact

Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle from spurious FC introduced by volume conduction. Here, we investigate the relationship between white matter structural connectivity (SC) and large-scale network structure encoded in EEG-FC. We start by confirming that FC (power envelope correlations) is predicted by SC beyond the impact of Euclidean distance, in line with the assumption that SC mediates genuine FC. We then use information from white matter structural connectivity in order to smooth the EEG signal in the space spanned by graphs derived from SC. Thereby, FC between nearby, structurally connected brain regions increases while FC between nonconnected regions remains unchanged, resulting in an increase in genuine, SC-mediated FC. We analyze the induced changes in FC, assessing the resemblance between EEG-FC and volume-conduction- free fMRI-FC, and find that smoothing increases resemblance in terms of overall correlation and community structure. This result suggests that our method boosts genuine FC, an outcome that is of interest for many EEG network neuroscience questions.

scholarly journals Ongoing dynamics in large-scale functional connectivity predict perception

2015 ◽  
Vol 112 (27) ◽  
pp. 8463-8468 ◽  
Author(s):  
Sepideh Sadaghiani ◽  
Jean-Baptiste Poline ◽  
Andreas Kleinschmidt ◽  
Mark D’Esposito
Keyword(s):  
Functional Connectivity ◽  
Network Structure ◽  
Large Scale ◽  
Brain Activity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Modular Network ◽  
Auditory Detection ◽  
Correlation Strength ◽  
The Difference

Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.

scholarly journals Resting-state functional connectivity modulates the BOLD activation induced by nucleus accumbens stimulation in the swine brain

2019 ◽  
Author(s):  
Shinho Cho ◽  
Jan T. Hachmann ◽  
Irena Balzekas ◽  
Myung-Ho In ◽  
Lindsey G. Andres-Beck ◽  
...  
Keyword(s):  
Nucleus Accumbens ◽  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Regions ◽  
Blood Oxygenation ◽  
Functional Networks ◽  
Swine Model ◽  
Resting State Functional Connectivity ◽  
The Impact

ABSTRACTWhile it is known that the clinical efficacy of deep brain stimulation (DBS) alleviates motor-related symptoms, cognitive and behavioral effects of DBS and its action mechanism on brain circuits are not clearly understood. By combining functional magnetic resonance imaging (fMRI) and DBS, we investigated the pattern of blood-oxygenation-level-dependent (BOLD) signal changes induced by stimulating the nucleus accumbens and how inter-regional resting-state functional connectivity is related with the stimulation DBS effect in a healthy swine model. We found that the pattern of stimulation-induced BOLD activation was diffused across multiple functional networks including the prefrontal, limbic, and thalamic regions, altering inter-regional functional connectivity after stimulation. Furthermore, our results showed that the strength of the DBS effect is closely related to the strength of inter-regional resting-state functional connectivity including stimulation locus and remote brain regions. Our results reveal the impact of nucleus accumbens stimulation on major functional networks, highlighting functional connectivity may mediate the modulation effect of DBS via large-scale brain networks.

scholarly journals Functional Connectivity Among Default Mode, Fronto-Parietal, and Salience Networks Moderates the Lagged Association between Sadness and Rumination in Daily Life

2018 ◽  
Author(s):  
David M. Lydon-Staley ◽  
Christine Kuehner ◽  
Vera Zamoscik ◽  
Silke Huffziger ◽  
Peter Kirsch ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Large Scale ◽  
Daily Life ◽  
Network Connectivity ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Adaptive Responses ◽  
Default Mode ◽  
Perseverative Thinking

Rumination, the perseverative thinking about one’s problems and emotions, is a maladaptive response to sadness and a risk factor for the development and course of depression. A critical challenge hampering attempts to promote more adaptive responses to sadness is that the between-person characteristics associated with the tendency to ruminate following depressed mood remain uncharacterized. We examine the importance of between-person differences in blood-oxygen-level dependent (BOLD) functional networks underlying cognitive control for the moment-to-moment association between sadness and rumination in daily life. We pair functional magnetic resonance imaging with ambulatory assessments measuring momentary sadness and rumination deployed 10 times per day over 4 consecutive days from 58 participants (40 female, mean age = 36.69 years; 29 remitted from a lifetime episode of Major Depression). Using a multilevel model, we show that rumination increases following increases in sadness for participants with higher than average between-network connectivity of the default mode network and the fronto-parietal network. We also show that rumination increases following increases in sadness for participants with lower than average between-network connectivity of the fronto- parietal network and the salience network. In addition, we find that the flexibility of the salience network’s pattern of connections with brain regions across time is protective against increases in rumination following sadness. Our findings highlight the importance of the neural correlates of cognitive control for understanding maladaptive responses to sadness and also support the value of large-scale functional connectivity networks for understanding cognitive-affective behaviors as they naturally occur during the course of daily life.

scholarly journals Identification of amyloid beta oligomers in locus coeruleus (LC) neurons of Alzheimer’s patients and their impact on LC oxidative stress, inhibitory neurotransmitter receptors and neuronal excitability

2020 ◽  
Author(s):  
Louise Kelly ◽  
Mohsen Seifi ◽  
Ruolin Ma ◽  
Scott Mitchell ◽  
Uwe Rudolph ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Locus Coeruleus ◽  
Expression Profile ◽  
Neuronal Excitability ◽  
Psychiatric Symptoms ◽  
Amyloid Β ◽  
Wild Type Mouse ◽  
Brain Regions ◽  
Brain Functions ◽  
The Impact

AbstractAmyloid β oligomers (AβO) are potent modulators of two key Alzheimer’s pathological processes, namely synaptic dysfunction and tau tangle formation in various brain regions. Remarkably, the impact of AβO in one of the earliest brain regions to exhibit Alzheimer’s pathology, the locus coeruleus (LC), remains to be determined. Of particular importance is the effect of AβO on the excitability of individual LC neurons. This parameter determines brain-wide noradrenaline (NA) release, and thus NA-mediated brain functions, including cognition, emotion and immune function, which are all severely compromised in Alzheimer’s. Using a mouse model of increased Aβ production (APP-PSEN1), together with correlative histopathological analyses in post mortem Alzheimer’s patient samples, we determined the impact of Aβ pathology on various correlates of LC neuronal integrity. AβO immunoreactivity in the LC of APP-PSEN1 mice was replicated in patient samples, presenting as individual clusters located both intraneuronally, in mitochondrial compartments, as well as extracellularly in association with inhibitory synapses. No specific signal was detected in either patient control or wild type mouse samples. Accompanying this AβO expression profile was LC neuronal hyperexcitability and indicators of oxidative stress in APP-PSEN1 mice. LC hyperexcitability arose from a diminished inhibitory effect of GABA, due to impaired expression and function of the GABA-A receptor (GABAAR) α3 subunit. Importantly, this altered LC α3-GABAAR expression profile overlapped with AβO expression in both APP-PSEN1 mice and Alzheimer’s patient samples. Finally, strychnine-sensitive glycine receptors (GlyRs) remained resilient to AβO-induced changes and their activation reversed LC hyperexcitability. Alongside this first demonstration of AβO expression in the LC of Alzheimer’s patients, the study is also first to reveal a direct association between AβO and LC neuronal excitability. GlyR-α3-GABAAR modulation of AβO-dependent LC hyperexcitability could delay the onset of cognitive and psychiatric symptoms arising from LC-NA deficits, thereby significantly diminishing the disease burden for Alzheimer’s patients.

scholarly journals Attention network modulation via tRNS correlates with attention gain

eLife ◽  
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.

scholarly journals Lynn_etal_MathSkills_CPM_Preprint_V1_05July2021

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Math Skills ◽  
Whole Brain ◽  
Building Models ◽  
State Dependent ◽  
Brain Behavior

The human brain comprises multiple canonical networks, several of which are distributed across frontal, parietal, and temporooccipital regions. Studies report both positive and negative correlations between children’s math skills and the strength of functional connectivity among these regions during math-related tasks and at rest. Yet, it is unclear how the relation between children’s math skills and functional connectivity map onto patterns of distributed whole-brain connectivity, canonical network connectivity, and whether these relations are consistent across different task-states. We used connectome-based predictive modeling to test whether functional connectivity during number comparison and at rest predicts children’s math skills (N=31, Mage=9.21years) using distributed whole-brain connections versus connections among canonical networks. We found that weaker connectivity distributed across the whole brain and weaker connectivity between key math-related brain regions in specific canonical networks predicts better math skills in childhood. The specific connections predicting math skills, and whether they were distributed or mapped onto canonical networks, varied between tasks, suggesting that state-dependent rather than trait-level functional network architectures support children’s math skills. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

scholarly journals Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruedeerat Keerativittayayut ◽  
Ryuta Aoki ◽  
Mitra Taghizadeh Sarabi ◽  
Koji Jimura ◽  
Kiyoshi Nakahara
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Large Scale ◽  
Brain Regions ◽  
Brain Network ◽  
Time Varying ◽  
Memory Encoding ◽  
Graph Metrics ◽  
Connectivity Patterns ◽  
Network States

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

scholarly journals Altered topology of large-scale structural brain networks in chronic stroke

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Bastian Cheng ◽  
Eckhard Schlemm ◽  
Robert Schulz ◽  
Marlene Boenstrup ◽  
Arnaud Messé ◽  
...  
Keyword(s):  
Information Transfer ◽  
Large Scale ◽  
Neuronal Degeneration ◽  
Brain Networks ◽  
Brain Regions ◽  
Local Network ◽  
Structural Connectome ◽  
The Impact ◽  
Structural Brain ◽  
Topological Changes

Abstract Beyond disruption of neuronal pathways, focal stroke lesions induce structural disintegration of distant, yet connected brain regions via retrograde neuronal degeneration. Stroke lesions alter functional brain connectivity and topology in large-scale brain networks. These changes are associated with the degree of clinical impairment and recovery. In contrast, changes of large scale, structural brain networks after stroke are less well reported. We therefore aimed to analyse the impact of focal lesions on the structural connectome after stroke based on data from diffusion-weighted imaging and probabilistic fibre tracking. In total, 17 patients (mean age 64.5 ± 8.4 years) with upper limb motor deficits in the chronic stage after stroke and 21 healthy participants (mean age 64.9 ± 10.3 years) were included. Clinical deficits were evaluated by grip strength and the upper extremity Fugl-Meyer assessment. We calculated global and local graph theoretical measures to characterize topological changes in the structural connectome. Results from our analysis demonstrated significant alterations of network topology in both ipsi- and contralesional, primarily unaffected, hemispheres after stroke. Global efficiency was significantly lower in stroke connectomes as an indicator of overall reduced capacity for information transfer between distant brain areas. Furthermore, topology of structural connectomes was shifted toward a higher degree of segregation as indicated by significantly higher values of global clustering and modularity. On a level of local network parameters, these effects were most pronounced in a subnetwork of cortico-subcortical brain regions involved in motor control. Structural changes were not significantly associated with clinical measures. We propose that the observed network changes in our patients are best explained by the disruption of inter- and intrahemispheric, long white matter fibre tracts connecting distant brain regions. Our results add novel insights on topological changes of structural large-scale brain networks in the ipsi- and contralesional hemisphere after stroke.

scholarly journals Reduced Brain Electric Activity and Functional Connectivity in Bipolar Euthymia: An sLORETA Source Localization Study

2019 ◽  
Vol 51 (3) ◽  
pp. 155-166
Author(s):  
Annamaria Painold ◽  
Pascal L. Faber ◽  
Eva Z. Reininghaus ◽  
Sabrina Mörkl ◽  
Anna K. Holl ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Time Course ◽  
Temporal Cortex ◽  
Electric Activity ◽  
Brain Regions ◽  
Frequency Bands ◽  
Head Surface ◽  
Density Values ◽  
Surface Eeg

Bipolar disorder (BD) is a chronic illness with a relapsing and remitting time course. Relapses are manic or depressive in nature and intermitted by euthymic states. During euthymic states, patients lack the criteria for a manic or depressive diagnosis, but still suffer from impaired cognitive functioning as indicated by difficulties in executive and language-related processing. The present study investigated whether these deficits are reflected by altered intracortical activity in or functional connectivity between brain regions involved in these processes such as the prefrontal and the temporal cortices. Vigilance-controlled resting state EEG of 13 euthymic BD patients and 13 healthy age- and sex-matched controls was analyzed. Head-surface EEG was recomputed into intracortical current density values in 8 frequency bands using standardized low-resolution electromagnetic tomography. Intracortical current densities were averaged in 19 evenly distributed regions of interest (ROIs). Lagged coherences were computed between each pair of ROIs. Source activity and coherence measures between patients and controls were compared (paired t tests). Reductions in temporal cortex activity and in large-scale functional connectivity in patients compared to controls were observed. Activity reductions affected all 8 EEG frequency bands. Functional connectivity reductions affected the delta, theta, alpha-2, beta-2, and gamma band and involved but were not limited to prefrontal and temporal ROIs. The findings show reduced activation of the temporal cortex and reduced coordination between many brain regions in BD euthymia. These activation and connectivity changes may disturb the continuous frontotemporal information flow required for executive and language-related processing, which is impaired in euthymic BD patients.

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