scholarly journals Oxytocin modulates social brain network correlations in resting and task state

2022 ◽  
Author(s):  
Qingyuan Wu ◽  
Qi Huang ◽  
Chao Liu ◽  
Haiyan Wu
Keyword(s):  
Resting State ◽  
Predictive Power ◽  
Brain Networks ◽  
Brain Network ◽  
System Level ◽  
Social Brain ◽  
The Social ◽  
The Difference ◽  
The Relationship ◽  
And Task

Oxytocin (OT) is a neuropeptide that modulates social behaviors and the social brain. The effects of OT on the social brain can be tracked by assessing the neural activity in the resting and task states, providing a system-level framework for characterizing state-based functional relationships of its distinct effect. Here, we contribute to this framework by examining how OT modulates social brain network correlations during the resting and task states using fMRI. Firstly, we investigated network activation, followed by analyzing the relationship between networks and individual differences measured by the Positive and Negative Affect Schedule and the Big-Five scales. Subsequently, we evaluated functional connectivity in both states. Finally, the relationship between networks across the states was represented by the predictive power of networks in the resting state for task-evoked activity. The difference in predicted accuracy between subjects displayed individual variations in this relationship. Our results showed decreased dorsal default mode network (DDMN) for OT group in the resting state. Additionally, only in the OT group, the activity of the DDMN in the resting state had the largest predictive power for task-evoked activation of the precuneus network (PN). The results also demonstrated OT reduced individual variation of PN, specifically, the difference of accuracy between predicting a subject's own and others' PN task activation. These findings suggest a distributed but modulatory effect of OT on the association between resting brain networks and task-dependent brain networks, showing increased DDMN to PN connectivity after OT administration, which may support OT-induced distributed processing during task performance.

Schizophrenia is a disease of general connectivity more than a specifically “social brain” network

2004 ◽  
Vol 27 (6) ◽  
pp. 856-856 ◽  
Author(s):  
Conrado Bosman ◽  
Enzo Brunetti ◽  
Francisco Aboitiz
Keyword(s):  
Social Behavior ◽  
Neural Circuits ◽  
Brain Networks ◽  
Brain Network ◽  
Sufficient Condition ◽  
Social Brain ◽  
The Social

Dysfunctions of the neural circuits that implement social behavior are necessary but not a sufficient condition to develop schizophrenia. We propose that schizophrenia represents a disease of general connectivity that impairs not only the “social brain” networks, but also different neural circuits related with higher cognitive and perceptual functions. We discuss possible mechanisms and evolutionary considerations.

scholarly journals Effects of a Motor Imagery Task on Functional Brain Network Community Structure in Older Adults: Data from the Brain Networks and Mobility Function (B-NET) Study

2021 ◽  
Vol 11 (1) ◽  
pp. 118
Author(s):  
Blake R. Neyland ◽  
Christina E. Hugenschmidt ◽  
Robert G. Lyday ◽  
Jonathan H. Burdette ◽  
Laura D. Baker ◽  
...  
Keyword(s):  
Older Adults ◽  
Graph Theory ◽  
Community Structure ◽  
Resting State ◽  
Brain Networks ◽  
Brain Network ◽  
Functional Brain ◽  
Network Community ◽  
Functional Brain Networks ◽  
The Brain

Elucidating the neural correlates of mobility is critical given the increasing population of older adults and age-associated mobility disability. In the current study, we applied graph theory to cross-sectional data to characterize functional brain networks generated from functional magnetic resonance imaging data both at rest and during a motor imagery (MI) task. Our MI task is derived from the Mobility Assessment Tool–short form (MAT-sf), which predicts performance on a 400 m walk, and the Short Physical Performance Battery (SPPB). Participants (n = 157) were from the Brain Networks and Mobility (B-NET) Study (mean age = 76.1 ± 4.3; % female = 55.4; % African American = 8.3; mean years of education = 15.7 ± 2.5). We used community structure analyses to partition functional brain networks into communities, or subnetworks, of highly interconnected regions. Global brain network community structure decreased during the MI task when compared to the resting state. We also examined the community structure of the default mode network (DMN), sensorimotor network (SMN), and the dorsal attention network (DAN) across the study population. The DMN and SMN exhibited a task-driven decline in consistency across the group when comparing the MI task to the resting state. The DAN, however, displayed an increase in consistency during the MI task. To our knowledge, this is the first study to use graph theory and network community structure to characterize the effects of a MI task, such as the MAT-sf, on overall brain network organization in older adults.

scholarly journals Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Simchick ◽  
Kelly M. Scheulin ◽  
Wenwu Sun ◽  
Sydney E. Sneed ◽  
Madison M. Fagan ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Brain Network ◽  
Network Activity ◽  
Anatomical Structures ◽  
Healthy Control ◽  
And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

scholarly journals A study on small-world characteristics of Chinaäó»s high-speed railway networks

2016 ◽  
Author(s):  
Xin Yuan ◽  
Guo Liu ◽  
Kun Hui Ye
Keyword(s):  
High Speed ◽  
Small World ◽  
Clustering Coefficient ◽  
High Speed Rail ◽  
Attribute Data ◽  
The Social ◽  
The Difference ◽  
Global And Local ◽  
The Relationship ◽  
Space Method

The small-world model provides a useful perspective and method to study the topological structure and intrinsic characteristics of high-speed rail networks (HRNs). In this paper, the P-space method is used to examine global and local HRNs in China, meanwhile the adjacency matrix is developed, then the social network analysis and visualization tool UCINET is used to calculate the spatial and attribute data of HRNs at national and local levels in China. The small-world characteristics of whole HRNs are discussed, three networks which have different properties are determined, and a comparative analysis of the small-world effect is detected. Then, the relationship between the construction of high-speed rail and regional development of China is analysed. The results show that: 1) China's HRNs have small average path length ( L ) and large clustering coefficient (C ), representing a typical small-world network; 2) Local HRNs have a certain correlation with economic development. The reasons for the difference of HRNs with respect to characteristics among regions are eventually discussed.

scholarly journals Brain network dynamics correlate with personality traits

2019 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Arnaud Weill ◽  
Julien Modolo ◽  
Mahmoud Hassan
Keyword(s):  
Functional Connectivity ◽  
Personality Traits ◽  
Resting State ◽  
Brain Networks ◽  
Neural Substrates ◽  
Brain Network ◽  
Functional Brain ◽  
Human Connectome Project ◽  
Functional Brain Networks ◽  
The Brain

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

scholarly journals Kesantunan dalam Ritual Pernikahan Masyarakat Hindu-Bali; Kajian Etnopsikolingustik Religius

2020 ◽  
Vol 4 (1) ◽  
pp. 51
Author(s):  
Kadek Devi Kalfika Anggria Wardani
Keyword(s):  
Social Distance ◽  
The People ◽  
Observation Methods ◽  
The Social ◽  
Politeness Strategies ◽  
Hindu Community ◽  
The Difference ◽  
Traditional Marriage ◽  
The Relationship ◽  
Speech Situation

The study which is descriptive qualitative in nature, aims to investigate preference of politeness strategies by Balinese Hindu-community in traditional marriage ritual. Data was collected using interview and observation methods. Based on the results of data analysis, this research shows that the form of politeness that arises can be seen in terms of place, time, to the leaders of the people, during preparation, implementation, disclosure of the relationship with the Almighty, and after the completion of the ritual. The different forms of politeness that emerge can be seen from the use of Balinese in various levels which are adjusted to the social distance and speech situation. Besides being seen from the use of language, linguistic politeness is also evident from the attitude, intonation, and tone of the speaker. The difference in the form of politeness is intentionally raised to cause certain psychological impacts on the interlocutor.

scholarly journals 人工智能批判的話語悖論

2019 ◽  
Vol 17 (2) ◽  
pp. 133-137
Author(s):  
Fen LIN
Keyword(s):  
New Technologies ◽  
New Technology ◽  
Critical Issue ◽  
Human Beings ◽  
Policy Makers ◽  
Social Nature ◽  
The Social ◽  
The Difference ◽  
Medical Accident ◽  
The Relationship

LANGUAGE NOTE | Document text in Chinese; abstract in English only.In the dominant discourse of the "human–machine relationship," people and machines are the subjects, with a mutually shaping influence. However, this framework neglects the crux of the current critical analysis of AI. It reduces the problems with new technology to the relationship between people and machines, ignoring the re-shaping of the relationship between "people and people" in the era of new technology. This simplification may mislead policy and legal regulations for new technologies. Why would a robot killing cause more panic than a murder committed by a human? Why is a robot's misdiagnosis more troubling than a doctor's? Why do patients assume that machines make more accurate diagnoses than doctors? When a medical accident occurs, who is responsible for the mistakes of an intelligent medical system? In the framework of traditional professionalism, the relationship between doctors and patients, whether trusted or not, is based on the premise that doctors have specialized knowledge that patients do not possess. Therefore, the authority of a doctor is the authority of knowledge. In the age of intelligence, do machines provide information or knowledge? Can this strengthen or weaken the authority of doctors? It is likely that in the age of intelligence, the professionalism, authority and trustworthiness of doctors require a new knowledge base. Therefore, the de-skilling of doctors is not an issue of individual doctors, but demands an update of the knowledge of the entire industry. Recognizing this, policy makers must not focus solely on the use of machines, but take a wider perspective, considering how to promote the development of doctors and coordinate the relationship between doctors with different levels of knowledge development. We often ask, "In the era of intelligence, what defines a human?" This philosophical thinking should be directed toward not only the difference between machines and people as individuals, but also how the relationship between human beings, i.e., the social nature of humans, evolves in different technological environments. In short, this commentary stresses that a "good" machine or an "evil" machine—beyond the sci-fi romance of such discourse—reflects the evolution of the relationships between people. In today's smart age, the critical issue is not the relationship between people and machines. It is how people adjust their relationships with other people as machines become necessary tools in life. In the era of intelligence, therefore, our legislation, policy and ethical discussion should resume their focus on evolutionary relationships between people.DOWNLOAD HISTORY | This article has been downloaded 41 times in Digital Commons before migrating into this platform.

The HPWS and AMO: a dynamic study of system- and individual-level effects

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fiona Edgar ◽  
Jing A. Zhang ◽  
Nancy M. Blaker
Keyword(s):  
Task Performance ◽  
Service Sector ◽  
Contextual Performance ◽  
System Level ◽  
Human Resource Research ◽  
Organizational System ◽  
Content Type ◽  
Individual Level ◽  
The Relationship ◽  
And Task

PurposeDrawing on the dynamic model of ability, motivation, opportunity (AMO) for human resource research, this study aims to examine how organizational system-level (i.e. the high-performance work system (HPWS)) and individual-level AMO affect employees' performance. Specifically, this paper proposes that employee task performance is resultant from the integration of system- and individual-level AMO factors with employee contextual performance.Design/methodology/approachA survey design is employed with data collected from 250 employees working in New Zealand's service sector.FindingsThis study finds both organizational system (HPWS) and individual AMO dimensions have positive associations with employees' performance. At the system level, the supportive role played by contextual performance is highlighted with pro-social behaviors fully mediating the relationship between the HPWS and task performance. At the individual level, contextual performance is found to partially mediate the relationship between ability and task performance and fully mediate the relationship between motivation and task performance. Opportunity, on the other hand, is significantly associated with task but not contextual performance.Originality/valueIn acknowledging there are a plurality of factors that impact performance, this study enriches our understanding of AMO's influence in the context of people management.

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 Modular reconfiguration of an auditory control brain network supports adaptive listening behavior

2018 ◽  
Vol 116 (2) ◽  
pp. 660-669 ◽  
Author(s):  
Mohsen Alavash ◽  
Sarah Tune ◽  
Jonas Obleser
Keyword(s):  
Spatial Attention ◽  
Resting State ◽  
Brain Networks ◽  
Brain Network ◽  
Control Network ◽  
Speech Comprehension ◽  
Individual Level ◽  
Auditory Spatial Attention ◽  
The Individual ◽  
Listening Task

Speech comprehension in noisy, multitalker situations poses a challenge. Successful behavioral adaptation to a listening challenge often requires stronger engagement of auditory spatial attention and context-dependent semantic predictions. Human listeners differ substantially in the degree to which they adapt behaviorally and can listen successfully under such circumstances. How cortical networks embody this adaptation, particularly at the individual level, is currently unknown. We here explain this adaptation from reconfiguration of brain networks for a challenging listening task (i.e., a linguistic variant of the Posner paradigm with concurrent speech) in an age-varying sample of n = 49 healthy adults undergoing resting-state and task fMRI. We here provide evidence for the hypothesis that more successful listeners exhibit stronger task-specific reconfiguration (hence, better adaptation) of brain networks. From rest to task, brain networks become reconfigured toward more localized cortical processing characterized by higher topological segregation. This reconfiguration is dominated by the functional division of an auditory and a cingulo-opercular module and the emergence of a conjoined auditory and ventral attention module along bilateral middle and posterior temporal cortices. Supporting our hypothesis, the degree to which modularity of this frontotemporal auditory control network is increased relative to resting state predicts individuals’ listening success in states of divided and selective attention. Our findings elucidate how fine-tuned cortical communication dynamics shape selection and comprehension of speech. Our results highlight modularity of the auditory control network as a key organizational principle in cortical implementation of auditory spatial attention in challenging listening situations.

Sign in / Sign up

Export Citation Format

Share Document