scholarly journals Interacting brains revisited: A cross-brain network neuroscience perspective

2021 ◽  
Author(s):  
C. Gerloff ◽  
K. Konrad ◽  
D. Bzdok ◽  
C. Büsing ◽  
V. Reindl
Keyword(s):  
Social Behavior ◽  
Matrix Decomposition ◽  
Brain Regions ◽  
Brain Network ◽  
Social Characteristics ◽  
Neural Basis ◽  
Graph Representations ◽  
Neural Underpinnings ◽  
Nodal Density ◽  
Global And Local

AbstractElucidating the neural basis of social behavior is a long-standing challenge in neuroscience. Such endeavors are driven by attempts to extend the isolated perspective on the human brain by considering interacting persons’ brain activities, but a theoretical and computational framework for this purpose is still in its infancy. Here, we posit a comprehensive framework based on bipartite graphs for interbrain networks and address whether they provide meaningful insights into the neural underpinnings of social interactions. First, we show that the nodal density of such graphs exhibits nonrandom properties. While the current analyses mostly rely on global metrics, we encode the regions’ roles via matrix decomposition to obtain an interpretable network representation yielding both global and local insights. With Bayesian modeling, we reveal how synchrony patterns seeded in specific brain regions contribute to global effects. Beyond inferential inquiries, we demonstrate that graph representations can be used to predict individual social characteristics, outperforming functional connectivity estimators for this purpose. In the future, this may provide a means of characterizing individual variations in social behavior or identifying biomarkers for social interaction and disorders.

scholarly journals Neuroimaging studies exploring the neural basis of social isolation

2021 ◽  
Vol 30 ◽  
Author(s):  
Niccolò Zovetti ◽  
Maria Gloria Rossetti ◽  
Cinzia Perlini ◽  
Paolo Brambilla ◽  
Marcella Bellani
Keyword(s):  
Social Isolation ◽  
Brain Regions ◽  
Brain Network ◽  
Neural Basis ◽  
Social Brain ◽  
Temporal Lobes ◽  
The Social ◽  
Neural Underpinnings ◽  
Parietal Cortices ◽  
Posterior Superior Temporal Sulcus

Abstract According to the social brain hypothesis, the human brain includes a network designed for the processing of social information. This network includes several brain regions that elaborate social cues, interactions and contexts, i.e. prefrontal paracingulate and parietal cortices, amygdala, temporal lobes and the posterior superior temporal sulcus. While current literature suggests the importance of this network from both a psychological and evolutionary perspective, little is known about its neurobiological bases. Specifically, only a paucity of studies explored the neural underpinnings of constructs that are ascribed to the social brain network functioning, i.e. objective social isolation and perceived loneliness. As such, this review aimed to overview neuroimaging studies that investigated social isolation in healthy subjects. Social isolation correlated with both structural and functional alterations within the social brain network and in other regions that seem to support mentalising and social processes (i.e. hippocampus, insula, ventral striatum and cerebellum). However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies with longitudinal designs are needed to measure the effect of social isolation in experimental v. control groups and to explore its relationship with perceived loneliness, ultimately helping to clarify the neural correlates of the social brain.

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 Global and Local Head Direction Coding in the Human Brain

2021 ◽  
Author(s):  
J. P. Shine ◽  
T. Wolbers
Keyword(s):  
Reference Frames ◽  
Brain Regions ◽  
Retrosplenial Cortex ◽  
Specific Reference ◽  
Head Direction ◽  
Imaging Data ◽  
Neural Basis ◽  
Local Environments ◽  
Human Participants ◽  
Global And Local

AbstractOrientation-specific head direction (HD) cells increase their firing rate to indicate one’s facing direction in the environment. Rodent studies suggest HD cells in distinct areas of thalamus and retrosplenial cortex (RSC) code either for global (relative to the wider environment) or local (e.g., room-specific) reference frames. To investigate whether similar neuroanatomical dissociations exist in humans, we reanalysed functional magnetic resonance imaging data in which participants learned the orientation of unique images in separate local environments relative to distinct global landmarks (Shine, Valdés-Herrera, Hegarty, & Wolbers, 2016). The environment layout meant that we could establish two separate multivariate analysis models in which the HD on individual trials was coded relative either to global (North, South, East, West) or local (Front, Back, Right, Left) reference frames. Examining the data first in key regions of interest (ROI) for HD coding, we replicated our previous results and found that global HD was decodable in the thalamus and precuneus; the RSC, however, was sensitive only to local HD. Extending recent findings in both humans and rodents, V1 was sensitive to both HD reference frames. Additional small volume-corrected searchlight analyses supported the ROI results and indicated that the anatomical locus of the thalamic global HD coding was located in the medial thalamus, bordering the anterior thalamus, a region critical for global HD coding in rodents. Our findings elucidate further the putative neural basis of HD coding in humans, and suggest that distinct brain regions code for different frames of reference in HD.Significance statementHead direction (HD) cells provide a neural signal as to one’s orientation in the environment. HD can be coded relative to global or local (e.g., room-specific) reference frames, with studies suggesting that distinct areas of thalamus and retrosplenial cortex (RSC) code for this information. We reanalysed fMRI data where human participants associated images with global HDs before undergoing scanning. The design enabled us to examine both global and local HD coding. Supporting previous findings, global HD was decodable in thalamus, however the RSC coded only for local HD. We found evidence also for both reference frames in V1. These findings elucidate the putative neural basis of HD coding in humans, with distinct brain regions coding for different HD reference frames.

scholarly journals Automated Extraction of Human Functional Brain Network Properties Associated with Working Memory Load through a Machine Learning-Based Feature Selection Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Satoru Hiwa ◽  
Shogo Obuchi ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Support Vector ◽  
Neural Basis ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Network Properties

Working memory (WM) load-dependent changes of functional connectivity networks have previously been investigated by graph theoretical analysis. However, the extraordinary number of nodes represented within the complex network of the human brain has hindered the identification of functional regions and their network properties. In this paper, we propose a novel method for automatically extracting characteristic brain regions and their graph theoretical properties that reflect load-dependent changes in functional connectivity using a support vector machine classification and genetic algorithm optimization. The proposed method classified brain states during 2- and 3-back test conditions based upon each of the three regional graph theoretical metrics (degree, clustering coefficient, and betweenness centrality) and automatically identified those brain regions that were used for classification. The experimental results demonstrated that our method achieved a >90% of classification accuracy using each of the three graph metrics, whereas the accuracy of the conventional manual approach of assigning brain regions was only 80.4%. It has been revealed that the proposed framework can extract meaningful features of a functional brain network that is associated with WM load from a large number of nodal graph theoretical metrics without prior knowledge of the neural basis of WM.

STRUCTURAL BRAIN NETWORK ABNORMALITIES IN SUBJECTS WITH INTERNET ADDICTION

2017 ◽  
Vol 17 (07) ◽  
pp. 1740031 ◽  
Author(s):  
MIN-HEE LEE ◽  
AREUM MIN ◽  
YOON HO HWANG ◽  
DONG YOUN KIM ◽  
BONG SOO HAN ◽  
...  
Keyword(s):  
Internet Addiction ◽  
Diffusion Tensor ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Imaging Data ◽  
Structural Brain Network ◽  
Global And Local ◽  
The Impact ◽  
Structural Brain

Although problematic overuse of internet has increased, psychopathological characteristics and neurobiological mechanisms for internet addiction (IA) remain poorly understood. Therefore, it is necessary to investigate the impact of IA on the brain. The present study included 17 subjects with IA and 20 healthy subjects. We constructed the structural brain network from diffusion tensor imaging data and investigated alteration of structural connections in subjects with IA using the network analysis on the global and local levels. The subjects with IA showed increase of regional efficiency (RE) in bilateral orbitofrontal cortex (OFC) and decrease in right middle cingulate and middle temporal gyri ([Formula: see text]), whereas the global properties did not show significant changes. Young’s internet addiction test (IAT) scores and RE in left OFC showed positive correlation, and average time spent on internet per day was positively correlated with the RE in right OFC. This is the first study examining alterations of the structural brain connectivity in IA. We found that subjects with IA showed alterations of RE in some brain regions and RE was positively associated with the severity of IA and average time spent on internet per day. Therefore, RE may be a good property for IA assessment.

The Neural Basis of Religious Cognition

2020 ◽  
Vol 29 (2) ◽  
pp. 126-133 ◽  
Author(s):  
Jordan Grafman ◽  
Irene Cristofori ◽  
Wanting Zhong ◽  
Joseph Bulbulia
Keyword(s):  
Cognitive Control ◽  
Religious Beliefs ◽  
Brain Regions ◽  
Social Reasoning ◽  
Adaptive Responses ◽  
Neural Basis ◽  
Complex Interplay ◽  
Social Motivations ◽  
Neural Underpinnings ◽  
The Brain

Religion’s neural underpinnings have long been a topic of speculation and debate, but an emerging neuroscience of religion is beginning to clarify which regions of the brain integrate moral, ritual, and supernatural religious beliefs with functionally adaptive responses. Here, we review evidence indicating that religious cognition involves a complex interplay among the brain regions underpinning cognitive control, social reasoning, social motivations, and ideological beliefs.

scholarly journals Information flow between interacting human brains: Identification, validation, and relationship to social expertise

2015 ◽  
Vol 112 (16) ◽  
pp. 5207-5212 ◽  
Author(s):  
Edda Bilek ◽  
Matthias Ruf ◽  
Axel Schäfer ◽  
Ceren Akdeniz ◽  
Vince D. Calhoun ◽  
...  
Keyword(s):  
Social Behavior ◽  
Information Flow ◽  
Brain Connectivity ◽  
A Priori ◽  
Neural Basis ◽  
Temporoparietal Junction ◽  
Neural Underpinnings ◽  
Human Brains ◽  
The Brain

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender’s and receiver’s temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.

scholarly journals A connectome-based neuromarker of the non-verbal number acuity and arithmetic skills

2021 ◽  
Author(s):  
Dai Zhang ◽  
Liqin Zhou ◽  
Anmin Yang ◽  
Shanshan Li ◽  
Chunqi Chang ◽  
...  
Keyword(s):  
Individual Differences ◽  
Number System ◽  
Brain Regions ◽  
Brain Network ◽  
Large Sample Size ◽  
Neural Basis ◽  
Mathematical Abilities ◽  
Human Connectome Project ◽  
Survival And Reproduction ◽  
Numerosity Perception

The approximate number system (ANS) is vital for survival and reproduction in animals and crucial in constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, there lacks a neuromarker to characterize an individual's ANS acuity, especially one based on the whole-brain functional connectivity (FC). Here, we identified a distributed brain network (i.e., numerosity network) using a connectome-based predictive modeling (CPM) analysis on the resting-state functional magnetic resonance imaging (rs-fMRI) data based on a large sample size. The summed strength of all FCs within the numerosity network could reliably predict individual differences of the ANS acuity in behavior. Furthermore, in an independent dataset from the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network could also predict individual differences in arithmetic skills. Our findings illustrate that the numerosity network we identified could be an applicable neuromarker of the non-verbal number acuity and might serve as the neural basis underlying the known link between the non-verbal number acuity and mathematical abilities.

scholarly journals Neural Basis of Olfactory and Trigeminal Integration

2020 ◽  
Author(s):  
Prasanna R. Karunanayaka ◽  
Jiaming Lu ◽  
Qing X. Yang ◽  
K. Sathian
Keyword(s):  
Temporal Cortex ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Brain Network ◽  
Neural Basis ◽  
Localization Accuracy ◽  
Inferior Parietal Cortex ◽  
Superior Temporal Cortex ◽  
Connectivity Patterns ◽  
Primary Olfactory Cortex

ABSTRACTHumans naturally integrate signals from the olfactory and intranasal trigeminal systems. A tight interplay has been demonstrated between these two systems, and yet the underlying neural circuitry that mediate olfactory-trigeminal integration remains unclear. Using functional magnetic resonance imaging (fMRI), this study investigated the neural mechanisms underlying olfactory-trigeminal integration. Fifteen subjects with normal olfactory function performed a localization task with weak or strong air-puff stimuli, phenylethyl alcohol (PEA; rose odor), or a combination. Although the ability to localize PEA to either nostril was at chance, its presence significantly improved the localization accuracy of weak, but not strong, air-puffs, relative to the localization of air-puffs without concomitant PEA, when both stimuli were delivered concurrently to the same nostril. This enhancement in localization accuracy was directly correlated with the magnitude of multisensory activity in the primary olfactory cortex (POC). Changes in orbitofrontal cortex (OFC) multisensory activity alone could not predict task performance, but changes in OFC and POC connectivity could. Similar activity and connectivity patterns were observed in the superior temporal cortex (STC), inferior parietal cortex (IPC) and the cerebellum. Taken together, these results suggest that olfactory-trigeminal integration is occurring across multiple brain regions. These findings can be interpreted as an indication that the POC is part of a distributed brain network that mediate the integration between olfactory and trigeminal systems.

Neural Underpinnings of Numerical and Spatial Cognition: An fMRI Meta-Analysis of Brain Regions Associated with Symbolic Number, Arithmetic, and Mental Rotation

2019 ◽  
Author(s):  
Zachary Hawes ◽  
H Moriah Sokolowski ◽  
Chuka Bosah Ononye ◽  
Daniel Ansari
Keyword(s):  
Mental Rotation ◽  
Parietal Lobe ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Angular Gyrus ◽  
Number Representation ◽  
Neural Underpinnings ◽  
The Right ◽  
Symbolic Number

Where and under what conditions do spatial and numerical skills converge and diverge in the brain? To address this question, we conducted a meta-analysis of brain regions associated with basic symbolic number processing, arithmetic, and mental rotation. We used Activation Likelihood Estimation (ALE) to construct quantitative meta-analytic maps synthesizing results from 86 neuroimaging papers (~ 30 studies/cognitive process). All three cognitive processes were found to activate bilateral parietal regions in and around the intraparietal sulcus (IPS); a finding consistent with shared processing accounts. Numerical and arithmetic processing were associated with overlap in the left angular gyrus, whereas mental rotation and arithmetic both showed activity in the middle frontal gyri. These patterns suggest regions of cortex potentially more specialized for symbolic number representation and domain-general mental manipulation, respectively. Additionally, arithmetic was associated with unique activity throughout the fronto-parietal network and mental rotation was associated with unique activity in the right superior parietal lobe. Overall, these results provide new insights into the intersection of numerical and spatial thought in the human brain.

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