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

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.

Author(s):  
Hana Burianová

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.


2018 ◽  
Author(s):  
Štefan Holiga ◽  
Joerg F. Hipp ◽  
Christopher H. Chatham ◽  
Pilar Garces ◽  
Will Spooren ◽  
...  

AbstractDespite the high clinical burden little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here we address these questions in the most comprehensive, large-scale effort to date comprising evaluation of four large ASD cohorts. We followed a strict exploration and replication procedure to identify core rs-fMRI functional connectivity (degree centrality) alterations associated with ASD as compared to typically developing (TD) controls (ASD: N=841, TD: N=984). We then tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status and clinical symptom severity. We find reproducible patterns of ASD-associated functional hyper- and hypo-connectivity with hypo-connectivity being primarily restricted to sensory-motor regions and hyper-connectivity hubs being predominately located in prefrontal and parietal cortices. We establish shifts in between-network connectivity from outside to within the identified regions as a key driver of these abnormalities. The magnitude of these alterations is linked to core ASD symptoms related to communication and social interaction and is not affected by age, sex or medication status. The identified brain functional alterations provide a reproducible pathophysiological phenotype underlying the diagnosis of ASD reconciling previous divergent findings. The large effect sizes in standardized cohorts and the link to clinical symptoms emphasize the importance of the identified imaging alterations as potential treatment and stratification biomarkers for ASD.


2019 ◽  
Author(s):  
Valerio Zerbi ◽  
Amalia Floriou-Servou ◽  
Marija Markicevic ◽  
Yannick Vermeiren ◽  
Oliver Sturman ◽  
...  

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.


2018 ◽  
Author(s):  
David M. Lydon-Staley ◽  
Christine Kuehner ◽  
Vera Zamoscik ◽  
Silke Huffziger ◽  
Peter Kirsch ◽  
...  

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.


2020 ◽  
Author(s):  
Bingbo Bao ◽  
Lei Duan ◽  
Haifeng Wei ◽  
Pengbo Luo ◽  
Hongyi Zhu ◽  
...  

Abstract Background: Amputation in adults is a serious condition and previous studies suggested a remapping of representations in motor and sensory brain networks. However, little is known about the longitudinal reorganizing pattern in upper limb amputees’ patients.Methods: The present study included 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and large-scale brain plasticity in patients suffering from amputation. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity.Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees; and we found that not only the sensory and motor cortex, but also the cognitive-related brain regions involved in the functional plasticity after upper extremity deafferentation.Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The changes in activation and intrinsic connectivity in the brain showed correlation with the deafferentation status.


2021 ◽  
Author(s):  
Oscar Portoles ◽  
Yuzhen Qin ◽  
Jonathan Hadida ◽  
Mark Woolrich ◽  
Ming Cao ◽  
...  

AbstractBiophysical models of large-scale brain activity are a fundamental tool for understanding the mechanisms underlying the patterns observed with neuroimaging. These models combine a macroscopic description of the within- and between-ensemble dynamics of neurons within a single architecture. A challenge for these models is accounting for modulations of within-ensemble synchrony over time. Such modulations in local synchrony are fundamental for modeling behavioral tasks and resting-state activity. Another challenge comes from the difficulty in parametrizing large scale brain models which hinders researching principles related with between-ensembles differences. Here we derive a parsimonious large scale brain model that can describe fluctuations of local synchrony. Crucially, we do not reduce within-ensemble dynamics to macroscopic variables first, instead we consider within and between-ensemble interactions similarly while preserving their physiological differences. The dynamics of within-ensemble synchrony can be tuned with a parameter which manipulates local connectivity strength. We simulated resting-state static and time-resolved functional connectivity of alpha band envelopes in models with identical and dissimilar local connectivities. We show that functional connectivity emerges when there are high fluctuations of local and global synchrony simultaneously (i.e. metastable dynamics). We also show that for most ensembles, leaning towards local asynchrony or synchrony correlates with the functional connectivity with other ensembles, with the exception of some regions belonging to the default-mode network.Author summaryHere we present and evaluate a parsimonious model of large-scale brain activity. The model represents the brain as a network-of-networks structure. The sub-networks describe the neural activity within a brain region, and the global network encodes interactions between brain regions. Unlike other models, it capture progressive changes of local synchrony and local dynamics can be tuned with one parameter. Therefore the model could be used not only to model resting-state, but also behavioural tasks. Furthermore, we describe a simple framework that can deal with the arduous task of identifying global and local parameters.


Author(s):  
A. F. Belyaev ◽  
G. E. Piskunova

Introduction. One of the main tools of an osteopath are soft tissue techniques, which have a number of particular qualities such as minimization of force and duration of indirect techniques with an emphasis on muscle and ligamentous structures; combination of gestures, tendency to maximal relaxation and exclusion of direct action on pathological symptoms such as tension, overtone and pain. Minimization of the force applied during the performance of soft tissue techniques often invites a question whether there are differences between the usual touch and the therapeutic touch of an osteopath.Goal of research - to reveal the changes in the bioelectrical activity of the cerebral cortex arising in the process of osteopathic treatment in order to prove its specifi city in comparison with nonspecifi c tactile stimulation (neutral touch).Materials and methods. 75 people were examined with the use of multiparameter analysis of multichannel EEG in different times. 25 patients were clinically healthy adults, whereas 50 patients had signs of somatic dysfunctions.Results. Computer encephalography permits to perceive the difference between the neutral touch and the therapeutic action. An identifi cation reaction is a response to the neutral touch (changes in brain bioelectrical activity with an increase in statistically signifi cant connections in the temporal lobes), whereas the therapeutic action provokes the state of purposeful brain activity during still point (intensifi cation of frontooccipital interactions).Conclusions. Osteopathic action causes additional tension in the processing of incoming information, which requires participation of different brain regions, including interhemispheric mechanisms associated with analysis, maintenance of attention and regulation of targeted activities.


2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price

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.


eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruedeerat Keerativittayayut ◽  
Ryuta Aoki ◽  
Mitra Taghizadeh Sarabi ◽  
Koji Jimura ◽  
Kiyoshi Nakahara

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.


2019 ◽  
Vol 51 (3) ◽  
pp. 155-166
Author(s):  
Annamaria Painold ◽  
Pascal L. Faber ◽  
Eva Z. Reininghaus ◽  
Sabrina Mörkl ◽  
Anna K. Holl ◽  
...  

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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