scholarly journals Age-differences in information flow in executive and sensorimotor brain networks during childhood and adolescence

2020 ◽  
Author(s):  
Martina J. Lund ◽  
Dag Alnæs ◽  
Jaroslav Rokicki ◽  
Simon Schwab ◽  
Ole A. Andreassen ◽  
...  
Keyword(s):  
Information Flow ◽  
Graphical Models ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Network ◽  
Childhood And Adolescence ◽  
Imaging Data ◽  
Fine Grained ◽  
Age Related

AbstractObjectiveMental disorders often emerge during adolescence, and age-related differences in connection strengths of brain networks (static connectivity) have been identified. However, little is known about the directionality of information flow (directed connectivity) in this period of brain development.MethodsWe employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 979 participants aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on directionality.ResultsWe show robust bi-directionality in information flow between visual-medial and visual-lateral nodes of the network, in line with prior studies in adult samples. Furthermore, we found that age in this developmental sample was associated with directionality of information flow in sensorimotor and executive control networks, yet we did not find associations with cognitive abilities or psychopathology.DiscussionOur results revealed that directionality in information flow of large-scale brain networks is sensitive to age during adolescence, warranting further studies that may explore trajectories of development in more fine-grained network parcellations and in different populations.

scholarly journals Stabilization of Brain Network Dynamics during Childhood and Adolescence is Associated with Gene Expressions

2021 ◽  
Author(s):  
Tianyuan Lei ◽  
Xuhong Liao ◽  
Xiaodan Chen ◽  
Tengda Zhao ◽  
Yuehua Xu ◽  
...  
Keyword(s):  
Large Scale ◽  
Expression Profiles ◽  
Brain Networks ◽  
Network Dynamics ◽  
Brain Network ◽  
Global Network ◽  
Association Cortex ◽  
Childhood And Adolescence ◽  
Gene Expressions ◽  
Age Related

AbstractFunctional brain networks require dynamic reconfiguration to support flexible cognitive function. However, the developmental principles shaping brain network dynamics remain poorly understood. Here, we report the longitudinal development of large-scale brain network dynamics during childhood and adolescence, and its connection with gene expression profiles. Using a multilayer network model, we show the temporally varying modular architecture of child brain networks, with higher network switching primarily in the association cortex and lower switching in the primary regions. This topographical profile exhibits progressive maturation, which manifests as reduced modular dynamics, particularly in the transmodal (e.g., default-mode and frontoparietal) and sensorimotor regions. These developmental refinements mediate age-related enhancements of global network segregation and are linked with the expression profiles of genes associated with the enrichment of ion transport and nucleobase-containing compound transport. These results highlight a progressive stabilization of brain dynamics, which expand our understanding of the neural mechanisms that underlie cognitive development.

scholarly journals Mapping human brain networks with cortico-cortical evoked potentials

2014 ◽  
Vol 369 (1653) ◽  
pp. 20130528 ◽  
Author(s):  
Corey J. Keller ◽  
Christopher J. Honey ◽  
Pierre Mégevand ◽  
Laszlo Entz ◽  
Istvan Ulbert ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Cognitive Processing ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Brain Network ◽  
Fundamental Aspect ◽  
Neural Basis ◽  
Network Function

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex.

scholarly journals Trajectory of rich club properties in structural brain networks

2021 ◽  
Author(s):  
Levin Riedel ◽  
Martijn P van den Heuvel ◽  
Sebastian Markett
Keyword(s):  
Brain Networks ◽  
Structural Connectivity ◽  
Subsequent Development ◽  
Brain Network ◽  
Aging Brain ◽  
Childhood And Adolescence ◽  
Rich Club ◽  
Age Related ◽  
Connectivity Strength ◽  
Structural Brain

Many organizational principles of structural brain networks are established before birth and undergo considerable developmental changes afterwards. These include the topologically central hub regions and a densely connected rich club. While several studies have mapped developmental trajectories of brain connectivity and brain network organization across childhood and adolescence, comparatively little is known about subsequent development over the course of the lifespan. Here, we present a cross-sectional analysis of structural brain network development in N = 8,066 participants aged 5 to 80 years. Across all brain regions, structural connectivity strength followed an ′inverted-U′-shaped trajectory with vertex in the early 30s. Connectivity strength of hub regions showed a similar trajectory and the identity of hub regions remained stable across all age groups. While connectivity strength declined with advancing age, the organization of hub regions into a rich club did not only remain intact but became more pronounced, presumingly through a selected sparing of relevant connections from age-related connectivity loss. The stability of rich club organization in the face of overall age-related decline is consistent with a ′first come, last served′ model of neurodevelopment, where the first principles to develop are the last to decline with age. Rich club organization has been shown to be highly beneficial for communicability and higher cognition. A resilient rich club might thus be protective of a functional loss in late adulthood and represent a neural reserve to sustain cognitive functioning in the aging brain.

scholarly journals Reconfiguration of human evolving large-scale epileptic brain networks prior to seizures: an evaluation with node centralities

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Theoretical Concept ◽  
Global Network ◽  
Time Resolved ◽  
Functional Connections ◽  
Node Centrality ◽  
Network Mechanism

AbstractPrevious research has indicated that temporal changes of centrality of specific nodes in human evolving large-scale epileptic brain networks carry information predictive of impending seizures. Centrality is a fundamental network-theoretical concept that allows one to assess the role a node plays in a network. This concept allows for various interpretations, which is reflected in a number of centrality indices. Here we aim to achieve a more general understanding of local and global network reconfigurations during the pre-seizure period as indicated by changes of different node centrality indices. To this end, we investigate—in a time-resolved manner—evolving large-scale epileptic brain networks that we derived from multi-day, multi-electrode intracranial electroencephalograpic recordings from a large but inhomogeneous group of subjects with pharmacoresistant epilepsies with different anatomical origins. We estimate multiple centrality indices to assess the various roles the nodes play while the networks transit from the seizure-free to the pre-seizure period. Our findings allow us to formulate several major scenarios for the reconfiguration of an evolving epileptic brain network prior to seizures, which indicate that there is likely not a single network mechanism underlying seizure generation. Rather, local and global aspects of the pre-seizure network reconfiguration affect virtually all network constituents, from the various brain regions to the functional connections between them.

scholarly journals Mindfulness Meditation Is Related to Long-Lasting Changes in Hippocampal Functional Topology during Resting State: A Magnetoencephalography Study

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Anna Lardone ◽  
Marianna Liparoti ◽  
Pierpaolo Sorrentino ◽  
Rosaria Rucco ◽  
Francesca Jacini ◽  
...  
Keyword(s):  
Resting State ◽  
Mindfulness Meditation ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Brain Network ◽  
Long Term Effects ◽  
Age Related ◽  
Functional Topology ◽  
The Right ◽  
The Brain

It has been suggested that the practice of meditation is associated to neuroplasticity phenomena, reducing age-related brain degeneration and improving cognitive functions. Neuroimaging studies have shown that the brain connectivity changes in meditators. In the present work, we aim to describe the possible long-term effects of meditation on the brain networks. To this aim, we used magnetoencephalography to study functional resting-state brain networks in Vipassana meditators. We observed topological modifications in the brain network in meditators compared to controls. More specifically, in the theta band, the meditators showed statistically significant (p corrected = 0.009) higher degree (a centrality index that represents the number of connections incident upon a given node) in the right hippocampus as compared to controls. Taking into account the role of the hippocampus in memory processes, and in the pathophysiology of Alzheimer’s disease, meditation might have a potential role in a panel of preventive strategies.

scholarly journals Approximate Entropy of Brain Network in the Study of Hemispheric Differences

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1220
Author(s):  
Francesca Alù ◽  
Francesca Miraglia ◽  
Alessandro Orticoni ◽  
Elda Judica ◽  
Maria Cotelli ◽  
...  
Keyword(s):  
Brain Networks ◽  
Approximate Entropy ◽  
Brain Network ◽  
Hemispheric Differences ◽  
Eyes Closed ◽  
Age Related ◽  
Eeg Recordings ◽  
The Right ◽  
The Impact ◽  
Adult Volunteers

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.

scholarly journals Early alterations of large-scale brain networks temporal dynamics in young children with autism

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Aurélie Bochet ◽  
Holger Franz Sperdin ◽  
Tonia Anahi Rihs ◽  
Nada Kojovic ◽  
Martina Franchini ◽  
...  
Keyword(s):  
Large Scale ◽  
Developmental Stages ◽  
Temporal Dynamics ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Clustering Methods ◽  
Early Developmental Stages ◽  
Spatio Temporal ◽  
Early Developmental

AbstractAutism spectrum disorders (ASD) are associated with disruption of large-scale brain network. Recently, we found that directed functional connectivity alterations of social brain networks are a core component of atypical brain development at early developmental stages in ASD. Here, we investigated the spatio-temporal dynamics of whole-brain neuronal networks at a subsecond scale in 113 toddlers and preschoolers (66 with ASD) using an EEG microstate approach. We first determined the predominant microstates using established clustering methods. We identified five predominant microstate (labeled as microstate classes A–E) with significant differences in the temporal dynamics of microstate class B between the groups in terms of increased appearance and prolonged duration. Using Markov chains, we found differences in the dynamic syntax between several maps in toddlers and preschoolers with ASD compared to their TD peers. Finally, exploratory analysis of brain–behavioral relationships within the ASD group suggested that the temporal dynamics of some maps were related to conditions comorbid to ASD during early developmental stages.

Dynamic Reorganization of the Cortical Functional Brain Network in Affective Processing and Cognitive Reappraisal

2020 ◽  
Vol 30 (10) ◽  
pp. 2050051
Author(s):  
Feng Fang ◽  
Thomas Potter ◽  
Thinh Nguyen ◽  
Yingchun Zhang
Keyword(s):  
Emotion Regulation ◽  
Large Scale ◽  
Brain Networks ◽  
Cognitive Reappraisal ◽  
Brain Network ◽  
Affective Processing ◽  
Functional Brain ◽  
Affective Stimuli ◽  
Functional Brain Network ◽  
Functional Brain Networks

Emotion and affect play crucial roles in human life that can be disrupted by diseases. Functional brain networks need to dynamically reorganize within short time periods in order to efficiently process and respond to affective stimuli. Documenting these large-scale spatiotemporal dynamics on the same timescale they arise, however, presents a large technical challenge. In this study, the dynamic reorganization of the cortical functional brain network during an affective processing and emotion regulation task is documented using an advanced multi-model electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) technique. Sliding time window correlation and [Formula: see text]-means clustering are employed to explore the functional brain connectivity (FC) dynamics during the unaltered perception of neutral (moderate valence, low arousal) and negative (low valence, high arousal) stimuli and cognitive reappraisal of negative stimuli. Betweenness centralities are computed to identify central hubs within each complex network. Results from 20 healthy subjects indicate that the cortical mechanism for cognitive reappraisal follows a ‘top-down’ pattern that occurs across four brain network states that arise at different time instants (0–170[Formula: see text]ms, 170–370[Formula: see text]ms, 380–620[Formula: see text]ms, and 620–1000[Formula: see text]ms). Specifically, the dorsolateral prefrontal cortex (DLPFC) is identified as a central hub to promote the connectivity structures of various affective states and consequent regulatory efforts. This finding advances our current understanding of the cortical response networks of reappraisal-based emotion regulation by documenting the recruitment process of four functional brain sub-networks, each seemingly associated with different cognitive processes, and reveals the dynamic reorganization of functional brain networks during emotion regulation.

scholarly journals A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Bo-yong Park ◽  
Jae-Joong Lee ◽  
Hong Ji Kim ◽  
Choong-Wan Woo ◽  
Hyunjin Park
Keyword(s):  
Back Pain ◽  
Pain Intensity ◽  
Large Scale ◽  
Brain Networks ◽  
Penalized Regression ◽  
Brain Network ◽  
Pain Modulation ◽  
Longitudinal Changes ◽  
Functional Connections ◽  
Intensity Changes

Abstract Identification of predictive neuroimaging markers of pain intensity changes is a crucial issue to better understand macroscopic neural mechanisms of pain. Although a single connection between the medial prefrontal cortex and nucleus accumbens has been suggested as a powerful marker, how the complex interactions on a large-scale brain network can serve as the markers is underexplored. Here, we aimed to identify a set of functional connections predictive of longitudinal changes in pain intensity using large-scale brain networks. We re-analyzed previously published resting-state functional magnetic resonance imaging data of 49 subacute back pain (SBP) patients. We built a network-level model that predicts changes in pain intensity over one year by combining independent component analysis and a penalized regression framework. Connections involving top-down pain modulation, multisensory integration, and mesocorticolimbic circuits were identified as predictive markers for pain intensity changes. Pearson’s correlations between actual and predicted pain scores were r = 0.33–0.72, and group classification results between SBP patients with persisting pain and recovering patients, in terms of area under the curve (AUC), were 0.89/0.75/0.75 for visits four/three/two, thus outperforming the previous work (AUC 0.83/0.73/0.67). This study identified functional connections important for longitudinal changes in pain intensity in SBP patients, providing provisional markers to predict future pain using large-scale brain networks.

scholarly journals Loss of integration of brain networks after sleep deprivation relates to the worsening of cognitive functions

2020 ◽  
Author(s):  
Pesoli Matteo ◽  
Rucco Rosaria ◽  
Liparoti Marianna ◽  
Lardone Anna ◽  
D’Aurizio Giula ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Resting State ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Network ◽  
Cognitive Tasks ◽  
Functional Networks ◽  
Long Sleep ◽  
Before And After ◽  
The Brain

AbstractThe topology of brain networks changes according to environmental demands and can be described within the framework of graph theory. We hypothesized that 24-hours long sleep deprivation (SD) causes functional rearrangements of the brain topology so as to impair optimal communication, and that such rearrangements relate to the performance in specific cognitive tasks, namely the ones specifically requiring attention. Thirty-two young men underwent resting-state MEG recording and assessments of attention and switching abilities before and after SD. We found loss of integration of brain network and a worsening of attention but not of switching abilities. These results show that brain network changes due to SD affect switching abilities, worsened attention and induce large-scale rearrangements in the functional networks.

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