How the brain negotiates divergent executive processing demands: Evidence of network reorganization in fleeting brain states

Liu, Mengting; Backer, Robert; Amey, Rachel; Forbes, Chad E.

doi:10.1016/j.neuroimage.2021.118653

Cited by 5 publications

(4 citation statements)

References 90 publications

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“…EEG epoching is a procedure in which specific time-windows are extracted from the continuous EEG signal. EEG artifacts were removed via FASTER (Fully Automated Statistical Thresholding for EEG artifact Rejection; Amey et al, 2022; Forbes et al, 2018; Liu, Backer, Amey, & Forbes, 2021; Liu, Backer, Amey, Splan, et al, 2021; Nolan et al, 2010), an automated approach to cleaning EEG data that is based on multiple iterations of independent component and statistical thresholding analyses. Processing the data through iterations of thresholding analyses helps remove artifacts from the EEG data.…”

Section: Methodsmentioning

confidence: 99%

When Majority Men Respect Minority Women, Groups Communicate Better: A Neurological Exploration

Amey

Emich

Forbes

2023

Small Group Research

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Groups must leverage their members’ diverse knowledge to make optimal decisions. However, the gender composition of a group may affect this ability, particularly because solo status female members (one female grouped with males) are generally allocated lower status than their male counterparts, so their knowledge is more likely to be ignored. Whereas most previous work suggests ways solo status women can increase their status; instead, we propose that groups communicate better when men give their female teammate appropriate respect. We examine this in mixed-gender groups working on a hidden profile task while wearing wireless EEGs to measure live neural activity. We find that groups who solve the problem correctly are more likely to contain majority male members with more approach-oriented mindsets, operationalized as neural alpha asymmetry, as they respect their female teammate more. Thus, we provide evidence that neural activity is partially responsible for whether mixed-gender groups make optimal decisions.

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Section: Methodsmentioning

confidence: 99%

When Majority Men Respect Minority Women, Groups Communicate Better: A Neurological Exploration

Amey

Emich

Forbes

2023

Small Group Research

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“…Once the dynamic functional connectivity is established, brain dynamics can be categorized into several brain states that reoccur over time. Clustering algorithms, such as k-means clustering introduced by Allen et al (2012 , 2014) used to be the most widely used method to obtain brain states ( Damaraju et al, 2014 ; Hutchison et al, 2014 ; Rashid et al, 2014 ; Barttfeld et al, 2015 ; Gonzalez-Castillo et al, 2015 ; Hudetz et al, 2015 ; Marusak et al, 2016 ; Shakil et al, 2016 ; Su et al, 2016 ; Liu et al, 2021a ). A limitation with clustering algorithms, however, is that they summarize brain patterns only based on the spatial distribution of brain connectivity.…”

Section: Brain Network Dynamicsmentioning

confidence: 99%

“…After characterizing the brain states, networks are estimated by pooling all data corresponding to a specific brain state. Finally, as another alternative, instead of using all connectivity, some sub-networks of interest may be pre-defined, then a single matrix representing the graph-theoretical properties of the specific sub-network can be estimated ( Liu et al, 2021a ). In this way, brain states can be defined based on the activity of a small number of sub-networks.…”

Section: Brain Network Dynamicsmentioning

confidence: 99%

Behavioral Studies Using Large-Scale Brain Networks – Methods and Validations

Liu

Amey

Backer

et al. 2022

Front. Hum. Neurosci.

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Mapping human behaviors to brain activity has become a key focus in modern cognitive neuroscience. As methods such as functional MRI (fMRI) advance cognitive scientists show an increasing interest in investigating neural activity in terms of functional connectivity and brain networks, rather than activation in a single brain region. Due to the noisy nature of neural activity, determining how behaviors are associated with specific neural signals is not well-established. Previous research has suggested graph theory techniques as a solution. Graph theory provides an opportunity to interpret human behaviors in terms of the topological organization of brain network architecture. Graph theory-based approaches, however, only scratch the surface of what neural connections relate to human behavior. Recently, the development of data-driven methods, e.g., machine learning and deep learning approaches, provide a new perspective to study the relationship between brain networks and human behaviors across the whole brain, expanding upon past literatures. In this review, we sought to revisit these data-driven approaches to facilitate our understanding of neural mechanisms and build models of human behaviors. We start with the popular graph theory approach and then discuss other data-driven approaches such as connectome-based predictive modeling, multivariate pattern analysis, network dynamic modeling, and deep learning techniques that quantify meaningful networks and connectivity related to cognition and behaviors. Importantly, for each topic, we discuss the pros and cons of the methods in addition to providing examples using our own data for each technique to describe how these methods can be applied to real-world neuroimaging data.

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“…Previous research has shown that SBS contexts typically engender a variety of behavioral and physiological SBS responses including sustained vACC activation, unique neural network configurations, and enhanced connectivity between regions integral for emotion (dACC, vACC, and mPFC) and saliency networks (IPL, insula, and STS). This evidence collectively suggests increased emotional processing and heightened awareness of negatively arousing or stressful information (Forbes et al, 2018;Liu et al, 2020Liu et al, , 2021Amey et al, 2022). We sought to understand if threatened women can transmit their stress to otherwise non-threatened partners, does it hurt or benefit the woman directly under threat, and to what extent can this come at a cost to their otherwise non-threatened partners?…”

Section: Introductionmentioning

confidence: 99%

Functional graph contrastive learning of hyperscanning EEG reveals emotional contagion evoked by stereotype-based stressors

Huang,

Amey,

Liu

et al. 2023

Front. Hum. Neurosci.

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IntroductionThis study delves into the intricacies of emotional contagion and its impact on performance within dyadic interactions. Specifically, it focuses on the context of stereotype-based stress (SBS) during collaborative problem-solving tasks among female pairs. Through an exploration of emotional contagion, this study seeks to unveil its underlying mechanisms and effects.MethodsLeveraging EEG-based hyperscanning technology, we introduced an innovative approach known as the functional graph contrastive learning (fGCL), which extracts subject-invariant representations of neural activity patterns from feedback trials. These representations are further subjected to analysis using the dynamic graph classification (DGC) model, aimed at dissecting the process of emotional contagion along three independent temporal stages.ResultsThe results underscore the substantial role of emotional contagion in shaping the trajectories of participants' performance during collaborative tasks in the presence of SBS conditions.DiscussionOverall, our research contributes invaluable insights into the neural underpinnings of emotional contagion, thereby enriching our comprehension of the complexities underlying social interactions and emotional dynamics.

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How the brain negotiates divergent executive processing demands: Evidence of network reorganization in fleeting brain states

Cited by 5 publications

References 90 publications

When Majority Men Respect Minority Women, Groups Communicate Better: A Neurological Exploration

When Majority Men Respect Minority Women, Groups Communicate Better: A Neurological Exploration

Behavioral Studies Using Large-Scale Brain Networks – Methods and Validations

Functional graph contrastive learning of hyperscanning EEG reveals emotional contagion evoked by stereotype-based stressors

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