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 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 Childhood Cognition and Age-Related Change in Standing Balance Performance From Mid to Later Life: Findings From a British Birth Cohort

2018 ◽  
Vol 75 (1) ◽  
pp. 155-161 ◽  
Author(s):  
Joanna M Blodgett ◽  
Diana Kuh ◽  
Rebecca Hardy ◽  
Daniel H J Davis ◽  
Rachel Cooper
Keyword(s):  
Cognitive Processing ◽  
Verbal Memory ◽  
Repeated Measures ◽  
Later Life ◽  
Standing Balance ◽  
Balance Performance ◽  
Standard Deviation Increase ◽  
Eyes Closed ◽  
Age Related ◽  
The Impact

Abstract Background Cognitive processing plays a crucial role in the integration of sensory input and motor output that facilitates balance. However, whether balance ability in adulthood is influenced by cognitive pathways established in childhood is unclear, especially as no study has examined if these relationships change with age. We aimed to investigate associations between childhood cognition and age-related change in standing balance between mid and later life. Methods Data on 2,380 participants from the MRC National Survey of Health and Development were included in analyses. Repeated measures multilevel models estimated the association between childhood cognition, assessed at age 15, and log-transformed balance time, assessed at ages 53, 60–64, and 69 using the one-legged stand with eyes closed. Adjustments were made for sex, death, attrition, anthropometric measures, health conditions, health behaviors, education, other indicators of socioeconomic position (SEP), and adult verbal memory. Results In a sex-adjusted model, 1 standard deviation increase in childhood cognition was associated with a 13% (95% confidence interval: 10, 16; p < .001) increase in balance time at age 53, and this association got smaller with age (cognition × age interaction: p < .001). Adjustments for education, adult verbal memory, and SEP largely explained these associations. Conclusions Higher childhood cognition was associated with better balance performance in midlife, with diminishing associations with increasing age. The impact of adjustment for education, cognition and other indicators of SEP suggested a common pathway through which cognition is associated with balance across life. Further research is needed to understand underlying mechanisms, which may have important implications for falls risk and maintenance of physical capability.

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 Hemispheric Asymmetry of Functional Brain Networks under Different Emotions Using EEG Data

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 939
Author(s):  
Rui Cao ◽  
Huiyu Shi ◽  
Xin Wang ◽  
Shoujun Huo ◽  
Yan Hao ◽  
...  
Keyword(s):  
Hemispheric Asymmetry ◽  
Right Hemisphere ◽  
Brain Networks ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Phase Lag ◽  
Characteristic Path Length ◽  
High Arousal ◽  
Eeg Data ◽  
The Right

Despite many studies reporting hemispheric asymmetry in the representation and processing of emotions, the essence of the asymmetry remains controversial. Brain network analysis based on electroencephalography (EEG) is a useful biological method to study brain function. Here, EEG data were recorded while participants watched different emotional videos. According to the videos’ emotional categories, the data were divided into four categories: high arousal high valence (HAHV), low arousal high valence (LAHV), low arousal low valence (LALV) and high arousal low valence (HALV). The phase lag index as a connectivity index was calculated in theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz) and gamma (31–45 Hz) bands. Hemispheric networks were constructed for each trial, and graph theory was applied to quantify the hemispheric networks’ topological properties. Statistical analyses showed significant topological differences in the gamma band. The left hemispheric network showed significantly higher clustering coefficient (Cp), global efficiency (Eg) and local efficiency (Eloc) and lower characteristic path length (Lp) under HAHV emotion. The right hemispheric network showed significantly higher Cp and Eloc and lower Lp under HALV emotion. The results showed that the left hemisphere was dominant for HAHV emotion, while the right hemisphere was dominant for HALV emotion. The research revealed the relationship between emotion and hemispheric asymmetry from the perspective of brain networks.

Selective Attention to Faces in a Rapid Visual Stream: Hemispheric Differences in Enhancement and Suppression of Category-selective Neural Activity

2018 ◽  
Vol 30 (3) ◽  
pp. 393-410 ◽  
Author(s):  
Genevieve Quek ◽  
Dan Nemrodov ◽  
Bruno Rossion ◽  
Joan Liu-Shuang
Keyword(s):  
Selective Attention ◽  
Left Hemisphere ◽  
Right Hemisphere ◽  
Hemispheric Differences ◽  
Face Categorization ◽  
The Face ◽  
Left And Right ◽  
The Right ◽  
The Impact ◽  
Selective Activity

In daily life, efficient perceptual categorization of faces occurs in dynamic and highly complex visual environments. Yet the role of selective attention in guiding face categorization has predominantly been studied under sparse and static viewing conditions, with little focus on disentangling the impact of attentional enhancement and suppression. Here we show that attentional enhancement and suppression exert a differential impact on face categorization supported by the left and right hemispheres. We recorded 128-channel EEG while participants viewed a 6-Hz stream of object images (buildings, animals, objects, etc.) with a face image embedded as every fifth image (i.e., OOOOFOOOOFOOOOF…). We isolated face-selective activity by measuring the response at the face presentation frequency (i.e., 6 Hz/5 = 1.2 Hz) under three conditions: Attend Faces, in which participants monitored the sequence for instances of female faces; Attend Objects, in which they responded to instances of guitars; and Baseline, in which they performed an orthogonal task on the central fixation cross. During the orthogonal task, face-specific activity was predominantly centered over the right occipitotemporal region. Actively attending to faces enhanced face-selective activity much more evidently in the left hemisphere than in the right, whereas attending to objects suppressed the face-selective response in both hemispheres to a comparable extent. In addition, the time courses of attentional enhancement and suppression did not overlap. These results suggest the left and right hemispheres support face-selective processing in distinct ways—where the right hemisphere is mandatorily engaged by faces and the left hemisphere is more flexibly recruited to serve current tasks demands.

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 Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity

2020 ◽  
Author(s):  
Danielle L. Kurtin ◽  
Ines R. Violante ◽  
Karl Zimmerman ◽  
Robert Leech ◽  
Adam Hampshire ◽  
...  
Keyword(s):  
White Matter ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Networks ◽  
Brain Network ◽  
Network Activity ◽  
Brain State ◽  
State Dependent ◽  
Cathodal Tdcs ◽  
The Right

AbstractBackgroundTranscranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure.ObjectivesIn this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity.MethodsWe applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n=22) and TBI participants (n=34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure.ResultsWe find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional – in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region.ConclusionsOur results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation.

scholarly journals White-matter degradation and dynamical compensation support age-related functional alterations in human brain

2022 ◽  
Author(s):  
Spase Petkoski ◽  
Petra Ritter ◽  
Viktor Jirsa
Keyword(s):  
Average Length ◽  
Temporal Structure ◽  
Structural Connectivity ◽  
Bimodal Distribution ◽  
Brain Network ◽  
Age Related ◽  
Spatio Temporal ◽  
The Individual ◽  
The Impact ◽  
The Brain

Structural connectivity of the brain at different ages is analyzed using diffusion-weighted Magnetic Resonance Imaging (MRI) data. The largest decrease of the number and average length of stream- lines is found for the long inter-hemispheric links, with the strongest impact for frontal regions. From the BOLD functional MRI (fMRI) time series we identify age-related changes of dynamic functional connectivity (dFC) and spatial covariation features of the FC links captured by meta- connectivity (MC). They indicate more constant dFC, but wider range and variance of MC. Finally we applied computational whole-brain network model based on oscillators, which mechanistically expresses the impact of the spatio-temporal structure of the brain (weights and the delays) to the dynamics. With this we tested several hypothesis, which revealed that the spatio-temporal reorga- nization of the brain with ageing, supports the observed functional fingerprints only if the model accounts for: (i) compensation of the individual brains for the overall loss of structural connectivity, and (ii) decrease of propagation velocity due to the loss of myelination. We also show that having these two conditions, it is sufficient to decompose the time-delays as bimodal distribution that only distinguishes between intra- and inter-hemispheric delays, and that the same working point also captures the static FC the best.

scholarly journals Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks

2021 ◽  
Vol 1 ◽  
Author(s):  
Klaus Lehnertz ◽  
Thorsten Rings ◽  
Timo Bröhl
Keyword(s):  
Spectral Characteristics ◽  
Brain Networks ◽  
Biological Rhythms ◽  
Brain Dynamics ◽  
Eeg Signals ◽  
Functional Brain ◽  
Non Invasive ◽  
Functional Brain Networks ◽  
Eeg Recordings ◽  
The Impact

Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.

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.

Sign in / Sign up

Export Citation Format

Share Document