scholarly journals Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

2016 ◽  
Vol 371 (1693) ◽  
pp. 20150366 ◽  
Author(s):  
Uri Hasson ◽  
Chris D. Frith
Keyword(s):  
Social Interactions ◽  
Brain Activity ◽  
Division Of Labour ◽  
Shared Understanding ◽  
Complex Stimulus ◽  
Brain Areas ◽  
Mutual Adaptation ◽  
Neural Processes ◽  
Generalized Framework ◽  
Stimulus Shape

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis

scholarly journals Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative

2017 ◽  
Author(s):  
Emily S. Finn ◽  
Philip R. Corlett ◽  
Gang Chen ◽  
Peter A. Bandettini ◽  
R. Todd Constable
Keyword(s):  
Correlation Analysis ◽  
Brain Activity ◽  
Behavioral Responses ◽  
Complex Stimulus ◽  
Brain Areas ◽  
Syntactic Features ◽  
Specific Dimension ◽  
Trait Level ◽  
Social Narrative

ABSTRACTIndividuals often interpret the same event in different ways. How do personality traits modulate brain activity evoked by a complex stimulus? Here we report results from a naturalistic paradigm designed to draw out both neural and behavioral variation along a specific dimension of interest, namely paranoia. Participants listen to a narrative during functional MRI describing an ambiguous social scenario, written such that some individuals would find it highly suspicious, while others less so. Using inter-subject correlation analysis, we identify several brain areas that are differentially synchronized during listening between participants with high- and low trait-level paranoia, including theory-of-mind regions. Follow-up analyses indicate that these regions are more active to mentalizing events in high-paranoia individuals. Analyzing participants’ speech as they freely recall the narrative reveals semantic and syntactic features that also scale with paranoia. Results indicate that a personality trait can act as an intrinsic ‘prime’, yielding different neural and behavioral responses to the same stimulus across individuals.

Cannabidiol Has a Unique Effect on Global Brain Activity: A Pharmacological, Functional MRI Study in Awake Mice 

2021 ◽  
Author(s):  
Aymen Sadaka ◽  
Ana Ozuna ◽  
Richard Ortiz ◽  
Praveen Kulkarni ◽  
Clare Johnson ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Stress Disorders ◽  
Functional Coupling ◽  
Specific Information ◽  
Imaging Data ◽  
Post Traumatic Stress ◽  
Brain Areas ◽  
Dose Dependent ◽  
The Brain

Abstract Background: The phytocannabinoid cannabidiol (CBD) is a potential treatment for post-traumatic stress disorders. How does CBD interact with the brain to alter behavior? We hypothesized that CBD would produce a dose-dependent reduction in brain activity and functional coupling in neural circuitry associated with fear and defense. Methods: During the scanning session awake mice were given vehicle or CBD (3, 10, or 30 mg/kg I.P.) and imaged for 10 min post treatment. Mice were also treated with the 10 mg/kg dose of CBD and imaged one hr later for resting state BOLD functional connectivity (rsFC). Imaging data were registered to a 3D MRI mouse atlas providing site-specific information on 138 different brain areas. Blood samples were collected for CBD measurements.Results: CBD produced a dose-dependent polarization of activation along the rostral-caudal axis of the brain. The olfactory bulb and prefrontal cortex showed an increase in positive BOLD whereas the brainstem and cerebellum showed a decrease in BOLD signal. This negative BOLD affected many areas connected to the ascending reticular activating system (ARAS). The ARAS was decoupled to much of the brain but was hyperconnected to the olfactory system and prefrontal cortex. The pattern of ARAS connectivity closely overlapped with brain areas showing high levels N-acyl-phosphatidylethanolamines-specific phospholipase D (NAPE-PLD) messenger RNA.Conclusion: The CBD-induced decrease in ARAS activity is consistent with an emerging literature suggesting that CBD reduces autonomic arousal under conditions of emotional and physical stress. The putative target and mechanism of action is NAPE-PLD the enzyme responsible for the biosynthesis of lipid signaling molecules like anandamide.

scholarly journals Task-Dependent Warping of Semantic Representations During Search for Visual Action Categories

2021 ◽  
Author(s):  
Mo Shahdloo ◽  
Emin Çelik ◽  
Burcu A Urgen ◽  
Jack L. Gallant ◽  
Tolga Çukur
Keyword(s):  
Visual Search ◽  
Social Interactions ◽  
Brain Activity ◽  
Semantic Representation ◽  
Natural Scenes ◽  
Action Perception ◽  
Semantic Representations ◽  
Object Categories ◽  
Search For Objects ◽  
The Brain

Object and action perception in cluttered dynamic natural scenes relies on efficient allocation of limited brain resources to prioritize the attended targets over distractors. It has been suggested that during visual search for objects, distributed semantic representation of hundreds of object categories is warped to expand the representation of targets. Yet, little is known about whether and where in the brain visual search for action categories modulates semantic representations. To address this fundamental question, we studied human brain activity recorded via functional magnetic resonance imaging while subjects viewed natural movies and searched for either communication or locomotion actions. We find that attention directed to action categories elicits tuning shifts that warp semantic representations broadly across neocortex, and that these shifts interact with intrinsic selectivity of cortical voxels for target actions. These results suggest that attention serves to facilitate task performance during social interactions by dynamically shifting semantic selectivity towards target actions, and that tuning shifts are a general feature of conceptual representations in the brain.

Neural Mechanisms of Visual Attention: Object-Based Selection of a Region in Space

2000 ◽  
Vol 12 (supplement 2) ◽  
pp. 106-117 ◽  
Author(s):  
Catherine M. Arrington ◽  
Thomas H. Carr ◽  
Andrew R. Mayer ◽  
Stephen M. Rao
Keyword(s):  
Visual Attention ◽  
Spatial Attention ◽  
Brain Activity ◽  
Temporal Cortex ◽  
Brain Structures ◽  
Brain Regions ◽  
Brain Areas ◽  
Unbounded Region ◽  
Object Based ◽  
Selection Of

Objects play an important role in guiding spatial attention through a cluttered visual environment. We used event-related functional magnetic resonance imaging (ER-fMRI) to measure brain activity during cued discrimination tasks requiring subjects to orient attention either to a region bounded by an object (object-based spatial attention) or to an unbounded region of space (location-based spatial attention) in anticipation of an upcoming target. Comparison between the two tasks revealed greater activation when attention selected a region bounded by an object. This activation was strongly lateralized to the left hemisphere and formed a widely distributed network including (a) attentional structures in parietal and temporal cortex and thalamus, (b) ventral-stream object processing structures in occipital, inferior-temporal, and parahippocampal cortex, and (c) control structures in medial-and dorsolateral-prefrontal cortex. These results suggest that object-based spatial selection is achieved by imposing additional constraints over and above those processes already operating to achieve selection of an unbounded region. In addition, ER-fMRI methodology allowed a comparison of validly versus invalidly cued trials, thereby delineating brain structures involved in the reorientation of attention after its initial deployment proved incorrect. All areas of activation that differentiated between these two trial types resulted from greater activity during the invalid trials. This outcome suggests that all brain areas involved in attentional orienting and task performance in response to valid cues are also involved on invalid trials. During invalid trials, additional brain regions are recruited when a perceiver recovers from invalid cueing and reorients attention to a target appearing at an uncued location. Activated brain areas specific to attentional reorientation were strongly right-lateralized and included posterior temporal and inferior parietal regions previously implicated in visual attention processes, as well as prefrontal regions that likely subserve control processes, particularly related to inhibition of inappropriate responding.

scholarly journals Transient brain networks underlying interpersonal strategies during synchronized action

2020 ◽  
Author(s):  
Ole Adrian Heggli ◽  
Ivana Konvalinka ◽  
Joana Cabral ◽  
Elvira Brattico ◽  
Morten L Kringelbach ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Human Interaction ◽  
Action Perception ◽  
Network Information ◽  
Mutual Adaptation ◽  
Underlying Mechanisms ◽  
The Brain

Abstract Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading–leading, and leading–following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading–leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action–perception-related brain network in the alpha range, as compared to the leading–leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading–leading might be facilitated by a higher degree of action–perception network coupling in the brain.

scholarly journals Investigation of changes in the activity and function of dry eye-associated brain regions using the amplitude of low frequency fluctuations(ALFF)method

2022 ◽  
Author(s):  
Tie Sun ◽  
Hui-Ye Shu ◽  
Jie-Li Wu ◽  
Ting Su ◽  
Yu-Ji Liu ◽  
...  
Keyword(s):  
Dry Eye ◽  
Brain Activity ◽  
Pearson Correlation ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Brain Regions ◽  
Middle Frontal Gyrus ◽  
Brain Areas ◽  
Spontaneous Brain Activity ◽  
Frequency Fluctuations

Objective: The local characteristics of spontaneous brain activity in patients with dry eye (DE) and its relationship with clinical characteristics were evaluated using the amplitude of low-frequency fluctuations (ALFF) method. Methods: A total of 27 patients with DE (10 males and 17 females) and 28 healthy controls (HCs) (10 males and 18 females) were recruited, matched according to sex, age, weight, and height, classified into the DE and HC groups, and examined using functional magnetic resonance imaging scans. Spontaneous brain activity changes were recorded using ALFF technology. Data were recorded and plotted on the receiver operating characteristic curve, reflecting changes in activity in different brain areas. Finally, Pearson correlation analysis was used to calculate the potential relationship between spontaneous brain activity abnormalities in multiple brain regions and clinical features in patients with DE. GraphPad Prism 8 (GraphPad Software, Inc.) was used to analyze the linear correlation between the Hospital Anxiety and Depression Scale and ALFF value. Results: Compared with HCs, the ALFF values of patients with DE were decreased in the right middle frontal gyrus/right inferior orbitofrontal cortex, left triangle inferior frontal gyrus, left middle frontal gyrus, and right superior frontal gyrus. In contrast, the ALFF value of patients with DE was increased in the left calcarine. Conclusion: There are significant fluctuations in the ALFF value of specific brain regions in patients with DE versus HCs. This corroborates previous evidence showing that the symptoms of ocular surface damage in patients with DE are related to dysfunction in specific brain areas.

scholarly journals The Neural Basis of Shared Preference Learning

2019 ◽  
Author(s):  
Harry Farmer ◽  
Uri Hertz ◽  
Antonia Hamilton
Keyword(s):  
Social Interactions ◽  
Computational Modelling ◽  
Brain Regions ◽  
The Self ◽  
Neural Activation ◽  
Neural Basis ◽  
Daily Lives ◽  
Neural Processes ◽  
Specific Manner ◽  
The Brain

AbstractDuring our daily lives, we often learn about the similarity of the traits and preferences of others to our own and use that information during our social interactions. However, it is unclear how the brain represents similarity between the self and others. One possible mechanism is to track similarity to oneself regardless of the identity of the other (Similarity account); an alternative is to track each confederate in terms of consistency of the similarity to the self, with respect to the choices they have made before (consistency account). Our study combined fMRI and computational modelling of reinforcement learning (RL) to investigate the neural processes that underlie learning about preference similarity. Participants chose which of two pieces of artwork they preferred and saw the choices of one confederate who usually shared their preference and another who usually did not. We modelled neural activation with RL models based on the similarity and consistency accounts. Data showed more brain regions whose activity pattern fits with the consistency account, specifically, areas linked to reward and social cognition. Our findings suggest that impressions of other people can be calculated in a person-specific manner which assumes that each individual behaves consistently with their past choices.

scholarly journals A DEEP LEARNING APPROACH TO ESTIMATING INITIAL CONDITIONS OF BRAIN NETWORK MODELS IN REFERENCE TO MEASURED FMRI DATA

2021 ◽  
Author(s):  
Amrit Kashyap ◽  
Sergey Plis ◽  
Michael Schirner ◽  
Petra Ritter ◽  
Shella Keilholz
Keyword(s):  
Deep Learning ◽  
Initial Conditions ◽  
Brain Activity ◽  
Network Models ◽  
Brain Network ◽  
Measured Data ◽  
Fmri Data ◽  
Short Term ◽  
Whole Brain ◽  
Neural Processes

Brain Network Models (BNMs) are a family of dynamical systems that simulate whole brain activity using neural mass models to represent local activity in different brain regions that influence each other via a global structural network. Research has been interested in using these network models to explain measured whole brain activity measured via resting state functional magnetic resonance imaging (rs-fMRI). Properties computed over longer periods of simulated and measured data such as average functional connectivity (FC), have shown to be comparable with similar properties estimated from measured rs-fMRI data. While this shows that these network models have similar properties over the dynamical landscape, it is unclear how well simulated trajectories compare with empirical trajectories on a timepoint-by-timepoint basis. Previous studies have shown that BNMs are able to produce relevant features at shorter timescales, but analysis of short-term trajectories or transient dynamics as defined by synchronized predictions from BNM made at the same timescale as the collected data has not yet been conducted. Relevant neural processes exist in the time frame of measurements and are often used in task fMRI studies to understand neural responses to behavioral cues. Therefore, it is important to investigate how much of these dynamics are captured by our current brain simulations. To test the nature of BNMs short term trajectories against observed data, we utilize a deep learning technique known as Neural ODE that based on an observed sequence of fMRI measurements, estimates the initial conditions such that the BNMs simulation is synchronized to produce the closest trajectory relative to the observed data. We test to see if the parameterization of a specific well studied BNM, the Firing Rate Model, calculated by maximizing its accuracy in reproducing observed short term trajectories matches with the parameterized model that produces the best average long-term metrics. Our results show that such an agreement between parameterization using long and short simulation analysis exists if also considering other factors such as the sensitivity in accuracy with relative to changes in structural connectivity. Therefore, we conclude that there is evidence that by solving for initial conditions, BNMs can be simulated in a meaningful way when comparing against measured data trajectories, although future studies are necessary to establish how BNM activity relate to behavioral variables or to faster neural processes during this time period.

scholarly journals The impact of modern jazz dance on the electrical brain activity

2018 ◽  
Author(s):  
Johanna Wind ◽  
Wolfgang Schöllhorn
Keyword(s):  
Brain Activity ◽  
Brain Activation ◽  
Brain Areas ◽  
Eyes Closed ◽  
Gamma Frequency ◽  
Electrical Brain Activity ◽  
Modern Jazz ◽  
Before And After ◽  
Eyes Open ◽  
The Impact

AbstractDance as one of the earliest cultural assets of mankind is practised in different cultures, mostly for wellbeing or for treating psycho-physiological disorders like Parkinson, depression, autism. However, the underlying neurophysiological mechanisms are still unclear and only few studies address the effects of particular dance styles. For a first impression, we were interested in the effects of modern jazz dance (MJD) on the brain activation that would contribute to the understanding of these mechanisms. 11 female subjects rehearsed a MJD choreography for three weeks (1h per week) and passed electroencephalographic (EEG) measurements in a crossover-design thereafter. The objectives were to establish the differences between dancing physically and participating just mentally with or without music. Therefore, each subject realized the four following test conditions: dancing physically to and without music, dancing mentally to and without music. Each of the conditions were performed for 15 minutes. Before and after each condition, the EEG activities were recorded under resting conditions (2 min. eyes-open, 2 min. eyes-closed) followed by a subsequent wash-out phase of 10 minutes.The results of the study revealed no time effects for the mental dancing conditions, either to or without music. An increased electrical brain activation was followed by the physical dancing conditions with and without music for the theta, alpha-1, alpha-2, beta and gamma frequency band across the entire scalp. Especially the higher frequencies (alpha-2, beta, gamma) showed increased brain activation across all brain areas. Higher brain activities for the physical dancing conditions were identified in comparison to the mental dancing condition. No statistically significant differences could be found as to dancing to or without music. Our findings demonstrate evidence for the immediate influence of modern jazz dance and its sweeping effects on all brain areas for all measured frequency bands, when dancing physically. In comparison, dancing just mentally does not result in similar effects.

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