scholarly journals Social synchronisation of brain activity by eye-contact

2021 ◽  
Author(s):  
Caroline Luft ◽  
Ioanna Zioga ◽  
Anastasios Giannopoulos ◽  
Gabriele Di Bona ◽  
Andrea Civilini ◽  
...  
Keyword(s):  
Frequency Band ◽  
Brain Activity ◽  
Brain Networks ◽  
Eye Contact ◽  
Mental States ◽  
Brain Network ◽  
Alpha Frequency ◽  
Gamma Frequency ◽  
Brain Connections ◽  
Extract Information

Abstract Humans make eye-contact to extract information about other people’s mental states, recruiting dedicated brain networks that process information about the self and others. Recent studies show that eye-contact increases the synchronization between two brains. We investigated how eye-contact affects the frequency and direction of the synchronization within and between brains and the characteristics of the dual brain network (i.e. hyperbrain). Eye-contact was associated with higher coherence in the gamma frequency band (30-45Hz) for between and within brain connections. Network analysis revealed that some brain areas served as hubs which linked within- and between- brain networks (midparietal, midfrontal and right parietal areas). Friends showed more efficient eye-contact hyperbrain networks than strangers. During eye-contact, some dyads spontaneously adopted leader/follower roles, resulting in an increase in synchronization from leader to follower (interbrain) in the alpha frequency band. Eye-contact affected directed and undirected synchronization between brains more than within brains, offering support to the interactive brain hypothesis.

scholarly journals Spatial and temporal autocorrelation weave human brain networks

2021 ◽  
Author(s):  
Maxwell Shinn ◽  
Amber Hu ◽  
Laurel Turner ◽  
Stephanie Noble ◽  
Sophie Achard ◽  
...  
Keyword(s):  
Network Topology ◽  
Healthy Aging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Brain Network ◽  
Temporal Autocorrelation ◽  
Activity Networks ◽  
Graph Properties ◽  
Test Retest Reliability

Correlations are a basic object of analysis across neuroscience, but multivariate patterns of correlations can be difficult to interpret. For example, correlations are fundamental to understanding timeseries derived from resting-state functional magnetic resonance imaging (rs-fMRI), a proxy of brain activity. Networks constructed from regional correlations in rs-fMRI timeseries are often interpreted as brain connectivity, yet the links between brain networks and neurobiology have until now been largely speculative. Here, we show that the topology of rs-fMRI brain networks is caused by the spatial and temporal autocorrelation of the timeseries used to construct them. Spatial and temporal autocorrelation show high test-retest reliability, and are correlated with popular measures of network topology. A generative model of spatially and temporally autocorrelated timeseries exhibits similar network topology to brain networks, and when fit to individual subjects, it captures near the reliability limit of subject and regional variation. We demonstrate why spatial and temporal autocorrelation induce network structure, and highlight their ability to link graph properties to neurobiology during healthy aging. These results offer a reductionistic account of brain network complexity, explaining characteristic patterns in brain networks using timeseries statistics.

scholarly journals Altered Functional Connectivity in Children with ADHD Revealed by Scalp EEG: An ERP Study

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chunli Chen ◽  
Huan Yang ◽  
Yasong Du ◽  
Guangzhi Zhai ◽  
Hesheng Xiong ◽  
...  
Keyword(s):  
Cognitive Processing ◽  
Early Stage ◽  
Brain Activity ◽  
Brain Networks ◽  
Brain Network ◽  
Event Related Potential ◽  
Children With Adhd ◽  
Scalp Eeg ◽  
Adhd Children ◽  
The One

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental brain disorders in childhood. Despite extensive researches, the neurobiological mechanism underlying ADHD is still left unveiled. Since the deficit functions, such as attention, have been demonstrated in ADHD, in our present study, based on the oddball P3 task, the corresponding electroencephalogram (EEG) of both healthy controls (HCs) and ADHD children was first collected. And we then not only focused on the event-related potential (ERP) evoked during tasks but also investigated related brain networks. Although an insignificant difference in behavior was found between the HCs and ADHD children, significant electrophysiological differences were found in both ERPs and brain networks. In detail, the dysfunctional attention occurred during the early stage of the designed task; as compared to HCs, the reduced P2 and N2 amplitudes in ADHD children were found, and the atypical information interaction might further underpin such a deficit. On the one hand, when investigating the cortical activity, HCs recruited much stronger brain activity mainly in the temporal and frontal regions, compared to ADHD children; on the other hand, the brain network showed atypical enhanced long-range connectivity between the frontal and occipital lobes but attenuated connectivity among frontal, parietal, and temporal lobes in ADHD children. We hope that the findings in this study may be instructive for the understanding of cognitive processing in children with ADHD.

scholarly journals The Power of Smiling: The Adult Brain Networks Underlying Learned Infant Emotionality

2019 ◽  
Vol 30 (4) ◽  
pp. 2019-2029 ◽  
Author(s):  
Eloise A Stark ◽  
Joana Cabral ◽  
Madelon M E Riem ◽  
Marinus H Van IJzendoorn ◽  
Alan Stein ◽  
...  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Brain Network ◽  
Adult Brain ◽  
Significant Activity ◽  
Nulliparous Women ◽  
Emotion And Memory ◽  
Underlying Mechanisms

Abstract The perception of infant emotionality, one aspect of temperament, starts to form in infancy, yet the underlying mechanisms of how infant emotionality affects adult neural dynamics remain unclear. We used a social reward task with probabilistic visual and auditory feedback (infant laughter or crying) to train 47 nulliparous women to perceive the emotional style of six different infants. Using functional neuroimaging, we subsequently measured brain activity while participants were tested on the learned emotionality of the six infants. We characterized the elicited patterns of dynamic functional brain connectivity using Leading Eigenvector Dynamics Analysis and found significant activity in a brain network linking the orbitofrontal cortex with the amygdala and hippocampus, where the probability of occurrence significantly correlated with the valence of the learned infant emotional disposition. In other words, seeing infants with neutral face expressions after having interacted and learned their various degrees of positive and negative emotional dispositions proportionally increased the activity in a brain network previously shown to be involved in pleasure, emotion, and memory. These findings provide novel neuroimaging insights into how the perception of happy versus sad infant emotionality shapes adult brain networks.

scholarly journals Early alterations of social brain networks in young children with autism

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Holger Franz Sperdin ◽  
Ana Coito ◽  
Nada Kojovic ◽  
Tonia Anahi Rihs ◽  
Reem Kais Jan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Social Brain ◽  
Compensatory Mechanisms ◽  
Source Imaging ◽  
Gaze Patterns ◽  
Cortical Regions

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD.

scholarly journals Brain networks and cognitive impairment in Parkinson′s disease

2020 ◽  
Author(s):  
Rosaria Rucco ◽  
Anna Lardone ◽  
marianna Liparoti ◽  
Emahnuel Troisi Lopez ◽  
Rosa De Micco ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Networks ◽  
Motor Impairment ◽  
Brain Network ◽  
Topological Features ◽  
Delta Band ◽  
Wide Range

Aim The aim of the present study is to investigate the relations between both functional connectivity and brain networks with cognitive decline, in patients with Parkinson′s disease (PD). Introduction PD phenotype is not limited to motor impairment but, rather, a wide range of non-motor disturbances can occur, cognitive impairment being one of the commonest. However, how the large-scale organization of brain activity differs in cognitively impaired patients, as opposed to cognitively preserved ones, remains poorly understood. Methods Starting from source-reconstructed resting-state magnetoencephalography data, we applied the PLM to estimate functional connectivity, globally and between brain areas, in PD patients with and without cognitive impairment (respectively PD-CI and PD-NC), as compared to healthy subjects (HS). Furthermore, using graph analysis, we characterized the alterations in brain network topology and related these, as well as the functional connectivity, to cognitive performance. Results We found reduced global and nodal PLM in several temporal (fusiform gyrus, Heschl′s gyrus and inferior temporal gyrus), parietal (postcentral gyrus), and occipital (lingual gyrus) areas within the left hemisphere, in the gamma band, in PD-CI patients, as compared to PD-NC and HS. With regard to the global topological features, PD-CI patients, as compared to HS and PD-NC patients, showed differences in multi frequencies bands (delta, alpha, gamma) in the Leaf fraction, Tree hierarchy (both higher in PD-CI) and Diameter (lower in PD-CI). Finally, we found statistically significant correlations between the MoCA test and both the Diameter in delta band and the Tree Hierarchy in the alpha band. Conclusion Our work points to specific large-scale rearrangements that occur selectively in cognitively compromised PD patients and correlated to cognitive impairment.

scholarly journals Impact of Antiepileptic Drugs on Cognition and Neuromagnetic Activity in Childhood Epilepsy With Centrotemporal Spikes: A Magnetoencephalography Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Kai Niu ◽  
Yihan Li ◽  
Tingting Zhang ◽  
Jintao Sun ◽  
Yulei Sun ◽  
...  
Keyword(s):  
Antiepileptic Drugs ◽  
Frequency Band ◽  
Neural Activity ◽  
Brain Activity ◽  
Posterior Cingulate Cortex ◽  
Source Location ◽  
Brain Network ◽  
Childhood Epilepsy ◽  
Longitudinal Imaging ◽  
Perceptual Reasoning

Objective: Childhood epilepsy with centrotemporal spikes (CECTS), the most common childhood epilepsy, still lacks longitudinal imaging studies involving antiepileptic drugs (AEDs). In order to examine the effect of AEDs on cognition and brain activity. We investigated the neuromagnetic activities and cognitive profile in children with CECTS before and after 1 year of treatment.Methods: Fifteen children with CECTS aged 6–12 years underwent high-sampling magnetoencephalography (MEG) recordings before treatment and at 1 year after treatment, and 12 completed the cognitive assessment (The Wechsler Intelligence Scale for Children). Next, magnetic source location and functional connectivity (FC) were investigated in order to characterize interictal neuromagnetic activity in the seven frequency sub-bands, including: delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), gamma (30–80 Hz), ripple (80–250 Hz), and fast ripple (250–500 Hz).Results: After 1 year of treatment, children with CECTS had increased scores on full-scale intelligence quotient, verbal comprehension index (VCI) and perceptual reasoning index (PRI). Alterations of neural activity occurred in specific frequency bands. Source location, in the 30–80 Hz frequency band, was significantly increased in the posterior cingulate cortex (PCC) after treatment. Moreover, FC analysis demonstrated that after treatment, the connectivity between the PCC and the medial frontal cortex (MFC) was enhanced in the 8–12 Hz frequency band. Additionally, the whole-brain network distribution was more dispersed in the 80–250 Hz frequency band.Conclusion: Intrinsic neural activity has frequency-dependent characteristic. AEDs have impact on regional activity and FC of the default mode network (DMN). Normalization of aberrant DMN in children with CECTS after treatment is likely the reason for improvement of cognitive function.

scholarly journals Detecting large-scale networks in the human brain using high-density electroencephalography

2016 ◽  
Author(s):  
Quanying Liu ◽  
Seyedehrezvan Farahibozorg ◽  
Camillo Porcaro ◽  
Nicole Wenderoth ◽  
Dante Mantini
Keyword(s):  
Human Brain ◽  
Frequency Band ◽  
Source Localization ◽  
Large Scale ◽  
Brain Research ◽  
Brain Networks ◽  
Brain Network ◽  
High Density ◽  
Robust Detection ◽  
Realistic Information

AbstractHigh-density electroencephalography (hdEEG) is an emerging brain imaging technique that can permit investigating fast dynamics of cortical electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from showing brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and eLORETA source localization, together with ICA for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the cortex as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research.

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 Characterizing the Network Architecture of Emotion Regulation Neurodevelopment

2019 ◽  
Author(s):  
João F. Guassi Moreira ◽  
Katie A. McLaughlin ◽  
Jennifer A. Silvers
Keyword(s):  
Emotion Regulation ◽  
Skill Acquisition ◽  
Network Architecture ◽  
Evolutionary Biology ◽  
Brain Activity ◽  
Brain Networks ◽  
Adult Life ◽  
Brain Network ◽  
Network Activity ◽  
Whole Brain

AbstractThe ability to regulate emotions is key to goal attainment and wellbeing. Although much has been discovered about how the human brain develops to support the acquisition of emotion regulation, very little of this work has leveraged information encoded in whole-brain networks. Here we employed a network neuroscience framework in conjunction with machine learning to: (i) parse the neural underpinnings of emotion regulation skill acquisition while accounting for age, and (ii) build a working taxonomy of brain network activity supporting emotion regulation in a sample of youth (N = 70, 34 female). We were able to predict emotion regulation ability, but not age, using network activity metrics from whole-brain networks during an emotion regulation task. Further, by leveraging analytic techniques traditionally used in evolutionary biology (e.g., cophenetic correlations), we were able to demonstrate that brain networks evince reliable taxonomic organization to meet emotion regulation demands in youth. This work shows that meaningful information about emotion regulation development is encoded in whole-brain network activity, suggesting that brain activity during emotion regulation encodes unique information about regulatory skill acquisition in youth but not domain-general maturation.Significance StatementThe acquisition of emotion regulation is critical for healthy functioning in later adult life. To date, little is known about how brain networks support the developmental acquisition of emotion regulation skills. This is noteworthy because brain networks have been increasingly shown to provide highly useful information about neural activity. Here we show that brain activity during an emotion regulation task encodes information about regulatory abilities over and above age. These results suggest emotion regulation skills are dependent on neural specialization of domain-specific systems, whereas age is encoded via domain-general systems.

scholarly journals Early alterations of social brain networks in young children with autism

2017 ◽  
Author(s):  
Holger Franz Sperdin ◽  
Ana Coito ◽  
Nada Kojovic ◽  
Tonia Rihs ◽  
Reem Kais Jan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Social Brain ◽  
Compensatory Mechanisms ◽  
Gaze Patterns ◽  
Clinical Impairment ◽  
Cortical Regions

ABSTRACTSocial impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. Here, we recorded the gaze patterns and brain activity of toddlers and preschoolers with ASD and their typically developing (TD) peers while they explored dynamic social scenes. Source-space directed functional connectivity analyses revealed the presence of network alterations in the theta frequency band, manifesting as increased driving (hyper-activity) and stronger connections (hyper-connectivity) from key nodes of the social brain associated with autism. Further analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with lower clinical impairment and less atypical gaze patterns. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD.

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