scholarly journals Development of human electrophysiological brain networks

2018 ◽  
Vol 120 (6) ◽  
pp. 3122-3130 ◽  
Author(s):  
Paul M. Briley ◽  
Elizabeth B. Liddle ◽  
Madeleine J. Groom ◽  
Helen J. F. Smith ◽  
Peter G. Morris ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Skills ◽  
Network Connectivity ◽  
Brain Regions ◽  
Higher Order ◽  
Cognitive Networks ◽  
Beta Band ◽  
Mri Findings ◽  
Sensorimotor Systems ◽  
Beta Frequency

Functional activity in the human brain is intrinsically organized into independently active, connected brain regions. These networks include sensorimotor systems, as well as higher-order cognitive networks such as the default mode network (DMN), which dominates activity when the brain is at rest, and the frontoparietal (FPN) and salience (SN) networks, which are often engaged during demanding tasks. Evidence from functional magnetic resonance imaging (fMRI) suggests that although sensory systems are mature by the end of childhood, the integrity of the FPN and SN develops throughout adolescence. There has been little work to corroborate these findings with electrophysiology. Using magnetoencephalography (MEG) recordings of 48 participants (aged 9–25 yr) at rest, we find that beta-band functional connectivity within the FPN, SN, and DMN continues to increase through adolescence, whereas connectivity in the visual system is mature by late childhood. In contrast to fMRI results, but replicating the MEG findings of Schäfer et al. (Schäfer CB, Morgan BR, Ye AX, Taylor MJ, Doesburg SM. Hum Brain Mapp 35: 5249–5261, 2014), we also see that connectivity between networks increases rather than decreases with age. This suggests that the development of coordinated beta-band oscillations within and between higher-order cognitive networks through adolescence might contribute to the developing abilities of adolescents to focus their attention and coordinate diverse aspects of mental activity. NEW & NOTEWORTHY Using magnetoencephalography to assess beta frequency oscillations, we show that functional connectivity within higher-order cognitive networks increases from childhood, reaching adult values by age 20 yr. In contrast, connectivity within a primary sensory (visual) network reaches adult values by age 14 yr. In contrast to functional MRI findings, connectivity between cognitive networks matures at a rate similar to within-network connectivity, suggesting that coordination of beta oscillations both within and between networks is associated with maturation of cognitive skills.

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 Heterogeneity of EEG resting-state brain networks in absolute pitch

2020 ◽  
Author(s):  
Marielle Greber ◽  
Carina Klein ◽  
Simon Leipold ◽  
Silvano Sele ◽  
Lutz Jäncke
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Resting State ◽  
Large Scale ◽  
Absolute Pitch ◽  
Brain Regions ◽  
Brain Network ◽  
Higher Order ◽  
Neural Basis ◽  
Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

scholarly journals The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

2020 ◽  
Author(s):  
Michael Eyre ◽  
Sean P Fitzgibbon ◽  
Judit Ciarrusta ◽  
Lucilio Cordero-Grande ◽  
Anthony N Price ◽  
...  
Keyword(s):  
Preterm Birth ◽  
Functional Connectivity ◽  
Large Scale ◽  
Developmental Coordination Disorder ◽  
Positive Association ◽  
Brain Regions ◽  
Higher Order ◽  
Dependent Manner ◽  
Normal Term ◽  
Human Connectome Project

AbstractThe Developing Human Connectome Project (dHCP) is an Open Science project which provides the first large sample of neonatal functional MRI (fMRI) data with high temporal and spatial resolution. This data enables mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organisation in humans. Here, we characterise in unprecedented detail the maturation and integrity of resting-state networks (RSNs) at normal term age in 337 infants (including 65 born preterm).First, we applied group independent component analysis (ICA) to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder which occur frequently in preterm children.Overall, we find a robust, modular, symmetrical functional brain organisation at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher-order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

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 Altered functional connectivity of cortical networks in semantic variant Primary Progressive Aphasia

2020 ◽  
Author(s):  
Haroon Popal ◽  
Megan Quimby ◽  
Daisy Hochberg ◽  
Bradford C. Dickerson ◽  
Jessica A. Collins
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Large Scale ◽  
Network Connectivity ◽  
Primary Progressive Aphasia ◽  
Cognitive Networks ◽  
Default Mode ◽  
Progressive Aphasia ◽  
Primary Progressive ◽  
Semantic Variant

AbstractAs their illness progresses, patients with the semantic variant of Primary Progressive Aphasia (svPPA) frequently exhibit peculiar behaviors indicative of altered visual attention or an increased interest in artistic endeavors. In the present study, we examined changes within and between large-scale functional brain networks that may explain this altered visual behavior. We first examined the connectivity of the visual association network, the dorsal attention network, and the default mode network in healthy young adults (n=89) to understand the typical architecture of these networks in the healthy brain. We then compared the large-scale functional connectivity of these networks in a group of svPPA patients (n=12) to a group of age-matched cognitively normal controls (n=30). Our results showed that the between-network connectivity of the dorsal attention and visual association networks was elevated in svPPA patients relative to controls. We further showed that this heightened between-network connectivity was associated with a decrease in the within-network connectivity of the default mode network, possibly due to progressive degeneration of the anterior temporal lobes in svPPA. These results suggest that focal neurodegeneration can lead to the reorganization of large-scale cognitive networks beyond the primarily affected network(s), possibly contributing to cognitive or behavioral changes that are commonly present as part of the clinical phenotype of svPPA.

scholarly journals Altered beta-band oscillations and connectivity underlie detail-oriented visual processing in autism

2020 ◽  
Author(s):  
Luca Ronconi ◽  
Andrea Vitale ◽  
Alessandra Federici ◽  
Elisa Pini ◽  
Massimo Molteni ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Visual Processing ◽  
Autism Spectrum ◽  
Visual Scene ◽  
Compensatory Mechanism ◽  
Beta Band ◽  
Beta Power ◽  
Cascade Effects ◽  
Beta Frequency ◽  
Visual Crowding

AbstractSensory and perceptual anomalies have been increasingly recognized as core phenotypic markers for autism spectrum disorders (ASD). A neurophysiological characterization of these anomalies is of utmost importance to understand more complex behavioural manifestations within the spectrum. The present study employed electroencephalography (EEG) to test whether detail-oriented visual perception, a recognized hallmark of ASD, is associated with altered neural oscillations and functional connectivity in beta (and alpha) frequency bands, considering their role in feedback and top-down reentrant signalling in the typical population. A sample of children with diagnosis of ASD (N=18) and typically developing peers (TD; N=20) performed a visual crowding task, where they had to discriminate a peripheral target letter surrounded by flankers at different distances, together with a control condition with no flankers. In TD participants the amplitude of the target-locked N1 component and its cortical sources was significantly modulated as a function of visual crowding, whereas such modulation was absent in the ASD group, suggesting that their visual scene analysis takes place without a flexible neural computation. The comparison between groups showed a decreased activity in the ASD group in occipital, infero-temporal and inferior/middle frontal regions in conditions requiring detail-oriented perception as opposed to conditions requiring the discrimination of target in isolation. Moreover, in TD participants detail-oriented perception was associated with an event-related beta power reduction (15-30 Hz), which was not evident in the ASD group. A data-driven functional connectivity analysis highlighted in the ASD sample an increased connectivity in the beta frequency range between occipital and infero-temporal regions. Notably, individual hyperconnectivity indexes correlated to less severe ASD symptomatology and to a diminished detail-oriented perception, suggesting a potential compensatory mechanism. Overall, these results show that altered communication in the beta frequency band may explain atypical perception in ASD, reflecting aberrant feedback connectivity within the visual system with potential cascade effects in visual scene parsing and higher-order functions.

scholarly journals Measuring robust functional connectivity from resting-state MEG using amplitude and entropy correlation across frequency-bands and temporal scales

2020 ◽  
Author(s):  
Megan Godfrey ◽  
Krish D. Singh
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Fine Scale ◽  
Beta Band ◽  
Temporal Scales ◽  
Frequency Bands ◽  
Functional Connections ◽  
Connectivity Patterns ◽  
Oscillatory Coupling ◽  
Beta Frequency

AbstractRecent studies have shown how MEG can reveal spatial patterns of functional connectivity using frequency-specific oscillatory coupling measures and that these may be modified in disease. However, there is a need to understand both how repeatable these patterns are across participants and how these measures relate to the moment-to-moment variability (or ‘irregularity’) of neural activity seen in healthy brain function. In this study, we used Multi-scale Rank-Vector Entropy (MRVE) to calculate the dynamic timecourses of signal variability over a range of temporal scales. The correlation of MRVE timecourses was then used to detect functional connections in resting state MEG recordings that were robust over 183 participants and varied with temporal scale. We then compared these MRVE connectivity patterns to those derived using more standard amplitude-amplitude coupling measures, using methods designed to quantify the consistency of these patterns across participants.Using oscillatory amplitude envelope correlation (AEC), the most consistent connectivity patterns, across the cohort, were seen in the alpha and beta frequency bands. At fine temporal scales (corresponding to ‘scale frequencies’, fS = 30-150Hz), MRVE correlation detected mostly occipital and parietal connections and these showed high similarity with the networks identified by AEC in the alpha and beta frequency bands. The most consistent connectivity profiles between participants were given by MRVE correlation at fS = 75Hz and AEC in the beta band.It was also found that average mid-to fine scale variability within each region (fS ∼ 10-150Hz) negatively correlated with the region’s overall connectivity strength with other brain areas, as measured by fine scale MRVE correlation (fS ∼ 30-150Hz) and by alpha and beta band AEC. These findings suggest that local activity at frequencies fS ≳ 10Hz becomes more regular when a region exhibits high levels of resting state connectivity.

scholarly journals Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation

2019 ◽  
Vol 117 (2) ◽  
pp. 1201-1206 ◽  
Author(s):  
Sophia Stoecklein ◽  
Anne Hilgendorff ◽  
Meiling Li ◽  
Kai Förster ◽  
Andreas W. Flemmer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Interindividual Variability ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Cognitive Networks ◽  
Temporoparietal Junction ◽  
Nervous Function ◽  
Preterm Born ◽  
Tissue Characteristics ◽  
Cortical Maturation

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

Altered thalamic connectivity during spontaneous attacks of migraine without aura: A resting-state fMRI study

Cephalalgia ◽  
2017 ◽  
Vol 38 (7) ◽  
pp. 1237-1244 ◽  
Author(s):  
Faisal Mohammad Amin ◽  
Anders Hougaard ◽  
Stefano Magon ◽  
Till Sprenger ◽  
Frauke Wolfram ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Migraine Without Aura ◽  
Primary Motor Cortex ◽  
Premotor Cortex ◽  
Network Connectivity ◽  
Insular Cortex ◽  
Resting State Fmri ◽  
Brain Regions ◽  
The Right

Background Functional connectivity of brain networks may be altered in migraine without aura patients. Functional magnetic resonance imaging (fMRI) studies have demonstrated changed activity in the thalamus, pons and cerebellum in migraineurs. Here, we investigated the thalamic, pontine and cerebellar network connectivity during spontaneous migraine attacks. Methods Seventeen patients with episodic migraine without aura underwent resting-state fMRI scan during and outside of a spontaneous migraine attack. Primary endpoint was a difference in functional connectivity between the attack and the headache-free days. Functional connectivity was assessed in four different networks using seed-based analysis. The chosen seeds were in the thalamus (MNI coordinates x,y,z: right, 22,–24,0 and left, –22,–28,6), pons (right, 8,–24,–32 and left, –8,–24,–32), cerebellum crus I (right, 46,–58,–30 and left, –46,–58,–30) and cerebellum lobule VI (right, 34,–42,–36 and left, –32,–42,–36). Results We found increased functional connectivity between the right thalamus and several contralateral brain regions (superior parietal lobule, insular cortex, primary motor cortex, supplementary motor area and orbitofrontal cortex). There was decreased functional connectivity between the right thalamus and three ipsilateral brain areas (primary somatosensory cortex and premotor cortex). We found no change in functional connectivity in the pontine or the cerebellar networks. Conclusions The study indicates that network connectivity between thalamus and pain modulating as well as pain encoding cortical areas are affected during spontaneous migraine attacks.

scholarly journals Prefrontal Cortex Modulation during Anticipation of Working Memory Demands as Revealed by Magnetoencephalography

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Mario Altamura ◽  
Terry E. Goldberg ◽  
Brita Elvevåg ◽  
Tom Holroyd ◽  
Frederick W. Carver ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Brain Regions ◽  
Higher Order ◽  
Task Demands ◽  
Beta Band ◽  
Stimulus Response ◽  
Synthetic Aperture Magnetometry ◽  
Beta Power ◽  
Dorsolateral Prefrontal

During the anticipation of task demands frontal control is involved in the assembly of stimulus-response mappings based on current goals. It is not clear whether prefrontal modulations occur in higher-order cortical regions, likely reflecting cognitive anticipation processes. The goal of this paper was to investigate prefrontal modulation during anticipation of upcoming working memory demands as revealed by magnetoencephalography (MEG). Twenty healthy volunteers underwent MEG while they performed a variation of the Sternberg Working Memory (WM) task. Beta band (14–30 Hz) SAM (Synthetic Aperture Magnetometry) analysis was performed. During the preparatory periods there was an increase in beta power (event-related synchronization) in dorsolateral prefrontal cortex (DLPFC) bilaterally, left inferior prefrontal gyrus, left parietal, and temporal areas. Our results provide support for the hypothesis that, during preparatory states, the prefrontal cortex is important for biasing higher order brain regions that are going to be engaged in the upcoming task.

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