Temporoparietal Research Articles

Neural Correlates of Social Decision-Making.

Objective: Recent studies have utilized innovative techniques to investigate the neural mechanisms underlying social and individual decision-making, aiming to understand how individuals respond to the world. Method : In this review, we summarized current scientific evidence concerning the neural underpinnings of social decision-making and their impact on social behavior. Results: Critical brain regions involved in social cognition and decision-making are integral to the process of social decision-making. Notably, the medial prefrontal cortex (mPFC) and temporoparietal junction (TPJ) contribute to the comprehension of others' mental states. Similarly, the posterior superior temporal sulcus (pSTS) shows heightened activity when individuals observe faces and movements. On the lateral surface of the brain, the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS) play a role in social cognition. Furthermore, the medial surface of the brain, including the amygdala, anterior cingulate cortex (ACC), and anterior insula (AI), also participates in social cognition processes. Regarding decision-making, functional magnetic resonance imaging (fMRI) studies have illuminated the involvement of a network of brain regions, encompassing the ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and nucleus accumbens (NAcc). Conclusion: Dysfunction in specific subregions of the prefrontal cortex (PFC) has been linked to various psychiatric conditions. These subregions play pivotal roles in cognitive, emotional, and social processing, and their impairment can contribute to the development and manifestation of psychiatric symptoms. A comprehensive understanding of the unique contributions of these PFC subregions to psychiatric disorders has the potential to inform the development of targeted interventions and treatments for affected individuals.

The role of prefrontal cortex and temporoparietal junction in interpersonal comfort and emotional approach

Our perception of physical distance to individuals and stimuli is influenced by our mental distance and relatedness. The present study aimed to investigate the role of the dorsolateral prefrontal cortex (dlPFC), ventromedial prefrontal cortex (vmPFC), and right temporoparietal junction (rTPJ) in interpersonal comfortable distance and approach behaviors towards emotional stimuli. Twenty healthy volunteers received brain stimulation in four separate sessions with a one-week interval, including anodal left dlPFC, anodal right vmPFC, anodal rTPJ, and sham condition, with an extracranial return electrode. Our results revealed an increase in interpersonal distance during anodal rTPJ stimulation and a decrease in distance to positive pictures during anodal vmPFC stimulation. These findings suggest that the rTPJ plays a role in the perceptual component of self-other distancing, while the vmPFC is involved in approaching positive emotions.

Identifying Cognitive Resilience Related Genes Among Genetic Risk Loci of Alzheimer’s Disease

AbstractBackgroundCognitive resilience (CR) in the context of Alzheimer’s disease (AD) describes the ability to maintain cognitive function despite the presence of neuropathology (Hohman et al., 2016). While most studies have focused on investigating genetic risk factors for developing AD, we here examined the association of most robust risk loci (Bellenguez et al., 2021) with CR using a neuroimaging‐based approach that incorporates measures of brain atrophy and cognition into a quantitative CR metric (van Loenhoud, 2017).MethodWe performed magnetic resonance imaging (3T) and DNA testing on n = 440 amyloid‐positive individuals in different clinical stages of AD. Employing a global cognitive composite score, we predicted gray matter volume (GM) in each voxel, adjusted for sex, age, premorbid intracranial volume, disease stage, and scanner type. To operationalize CR, W‐scores were computed for each individual based on the standardized individual difference between predicted and observed GM within temporoparietal (TP) and whole brain (WB) masks. In this approach, positive W‐scores reflect low CR, while negative W‐scores reflect high CR. A total of 83 genetic risk variants for AD (Bellenguez et al., 2021) were each tested for their association with W‐scores in a linear regression model corrected for population substructure (PC1‐5).ResultWe found an association for 6 genetic loci, of which variants rs113706587 in gene RASGEF1c and rs6943429 in gene UMAD1 were associated with higher CR (TP: p<0.01, p<0.02; WB: p<0.02, p<0.01). As expected, APOEe4 was associated with low CR (TP: p<0.01, WB: p<0.01), as were genetic markers of genes CLU, MINDY2 (WB: p<0.04, p<0.04), and BCKDK (WB: p<0.05, TP: p<0.04). Importantly, no association was found between APOEe2 and CR (WB: p = 0.195, TP: p = 0.139).ConclusionAmong genetic risk‐loci for AD, we identified two genetic variants associated with cognitive resilience in amyloid‐positive individuals. Interestingly, APOEe4 associated with low CR, as did genes CLU, MINDY2, and BCKDK, indicating anti‐resilience – possibly through accelerating mechanisms. In addition, our results suggest that CR against AD is independent of the protective relationship found between APOEe2 and developing AD, highlighting the relevance of investigating the mechanisms behind CR.

A CenTauR scale based on 18F‐MK6240

AbstractBackgroundA standardized scale for the quantification of tau PET imaging would allow comparison and combination of data across tracers and sites resulting in large meta‐analysis and the application of universal cut‐offs. The proposed approach called CenTauR (CTR) was evaluated on 18F‐MK6240 using both global and regional anchoring.Method375 18F‐MK6240 PET & T1w scan pairs (HC Aß‐ = 179/MCI Aß+ = 98/AD Aß+ = 98) from AIBL&ADNeT were spatially normalised using SPM8 and SUVR normalised using the cerebellar cortex. PET scans were then quantified in 4 composite ROIs [Mesial‐Temporal (Me), Meta‐Temporal (MT), Temporo‐Parietal (TP) and Frontal (FT)] from a previously defined “universal” cortical mask. To anchor the 0 and 100 CTR, we only included HC Aß‐ (<10CL) and AD Aß+ (>25CL) individuals younger than 75y, with MMSE = 20, we also excluded HC participants with a quantification higher than the 75%tile in the Me and AD patients with a quantification lower than the 25%tile in the MT, resulting in 68 HC Aß‐ and 29 AD Aß+. We investigated two CTR scaling approaches using either a single transform based on the TP anchors to transform SUVR into CTR for all composites or using region‐based equations scaled with regional anchors.ResultThe mean and standard deviation (std) for the HC and AD groups are reported in Table 1. Using a single transformation resulted in the following equation: Ct = 100x(SUVR‐0.97)/2.26 Region‐based equations can be extrapolated from Table 1. Figures 1 and 2 show that regional CTR overstretches quantification in FT compared to single equation‐derived CTR. Thresholds set at 2 std above the HC were 2.38, 9.43, 7.66, 1.82, and 6.16 CTR for Me, MT, TP, FT and Global respectively, and were 7.05, 7.48, 7.66, 10.20, 7.68 CTR when using regional equation‐derived CTR.ConclusionThe region‐based approach provided slightly more consistent CTR distributions in the HC across the ROIs however, this approach tends to over‐stretch the CTR values in the frontal region.

A CenTauR scale based on 18F‐MK6240

AbstractBackgroundA standardized scale for the quantification of tau PET imaging would allow comparison and combination of data across tracers and sites resulting in large meta‐analysis and the application of universal cut‐offs. The proposed approach called CenTauR (CTR) was evaluated on 18F‐MK6240 using both global and regional anchoring.Method375 18F‐MK6240 PET & T1w scan pairs (HC Aβ‐ = 179/MCI Aβ+ = 98/AD Aβ+ = 98) from AIBL&ADNeT were spatially normalised using SPM8 and SUVR normalised using the cerebellar cortex. PET scans were then quantified in 4 composite ROIs [Mesial‐Temporal (Me), Meta‐Temporal (MT), Temporo‐Parietal (TP) and Frontal (FT)] from a previously defined “universal” cortical mask. To anchor the 0 and 100 CTR, we only included HC Aβ‐ (<10CL) and AD Aβ+ (>25CL) individuals younger than 75y, with MMSE ≥20, we also excluded HC participants with a quantification higher than the 75%tile in the Me and AD patients with a quantification lower than the 25%tile in the MT, resulting in 68 HC Aβ‐ and 29 AD Aβ+. We investigated two CTR scaling approaches using either a single transform based on the TP anchors to transform SUVR into CTR for all composites or using region‐based equations scaled with regional anchors.ResultThe mean and standard deviation (std) for the HC and AD groups are reported in Table 1.Using a single transformation resulted in the following equation:Ct = 100x(SUVR‐0.97)/2.26Region‐based equations can be extrapolated from Table 1. Figures 1 and 2 show that regional CTR overstretches quantification in FT compared to single equation‐derived CTR. Thresholds set at 2 std above the HC were 2.38, 9.43, 7.66, 1.82, and 6.16 CTR for Me, MT, TP, FT and Global respectively, and were 7.05, 7.48, 7.66, 10.20, 7.68 CTR when using regional equation‐derived CTR.ConclusionThe region‐based approach provided slightly more consistent CTR distributions in the HC across the ROIs however, this approach tends to over‐stretch the CTR values in the frontal region.

Uncovering individual variations in bystander intervention of injustice through intrinsic brain connectivity patterns

When confronted with injustice, individuals often intervene as third parties to restore justice by either punishing the perpetrator or helping the victim, even at their own expense. However, little is known about how individual differences in third-party intervention propensity are related to inter-individual variability in intrinsic brain connectivity patterns and how these associations vary between help and punishment intervention. To address these questions, we employed a novel behavioral paradigm in combination with resting-state fMRI and inter-subject representational similarity analysis (IS-RSA). Participants acted as third-party bystanders and needed to decide whether to maintain the status quo or intervene by either helping the disadvantaged recipient (Help condition) or punishing the proposer (Punish condition) at a specific cost. Our analyses focused on three brain networks proposed in the third-party punishment (TPP) model: the salience (e.g., dorsal anterior cingulate cortex, dACC), central executive (e.g., dorsolateral prefrontal cortex, dlPFC), and default mode (e.g., dorsomedial prefrontal cortex, dmPFC; temporoparietal junction, TPJ) networks. IS-RSA showed that individual differences in resting-state functional connectivity (rs-FC) patterns within these networks were associated with the general third-party intervention propensity. Moreover, rs-FC patterns of the right dlPFC and right TPJ were more strongly associated with individual differences in the helping propensity rather than the punishment propensity, whereas the opposite pattern was observed for the dmPFC. Post-hoc predictive modeling confirmed the predictive power of rs-FC in these regions for intervention propensity across individuals. Collectively, these findings shed light on the shared and distinct roles of key regions in TPP brain networks at rest in accounting for individual variations in justice-restoring intervention behaviors.

Cognitive analysis based on EEG measurements on children with stunting-indicated in East Nusa Tenggara

Children with stunting have been associated with delayed brain development and poor cognitive performance by a lack of attentional control. The aim of the present study was to determine characteristics of stunting children based on theta (4-8 Hz), alpha (8-12 Hz) and beta (12-30 Hz) oscillation at anterofrontal (AF) and temporoparietal (TP). This research involved two groups: Stunting Group (SG, N=14) and Control Group (C; N=8) from East Nusa Tenggara. EEG was recorded during an eyes-open condition at baseline and puzzle task. Our result revealed alteration of theta oscillation in SG AF8 and TP10 during puzzle task, supporting role of theta oscillation in higher working memory loads although it was not accompanied by proper TP connectivity. Higher alpha and beta AF7 activity in SG compared to control group implying decreasing attentional processing and higher arousal. According to Laterality Index (LI), we revealed alteration in temporoparietal SG during puzzle task. These findings provide new insights about theta, alpha, and beta oscillation in stunting children may reflect that declining attentional functioning during the puzzle task leads to poor cognitive performance.

Neural Mechanisms Underlying Trust to Friends, Community Members, and Unknown Peers in Adolescence.

Trust plays an important role during adolescence for developing social relations. Although prior developmental studies give us insight into adolescents' development of differentiation between close (e.g., friends) and unknown (e.g., unknown peers) targets in trust choices, less is known about the development of trust to societal targets (e.g., members of a community organization) and its underlying neural mechanisms. Using a modified version of the Trust Game, our preregistered fMRI study examined the underlying neural mechanisms of trust to close (friend), societal (community member), and unknown others (unknown peer) during adolescence in 106 participants (aged 12-23 years). Adolescents showed most trust to friends, less trust to community members, and the least trust to unknown peers. Neural results show that target differentiation in adolescents' trust behavior is associated with activity in social brain regions implicated during mentalizing, reward processing, and cognitive control. Recruitment of the medial prefrontal cortex (mPFC) and OFC was higher for closer targets (i.e., friend and community member). For the mPFC, this effect was most pronounced during no trust choices. Trust to friends was additionally associated with increased activity in the precuneus and bilateral temporal parietal junction. In contrast, bilateral dorsolateral prefrontal cortex and anterior cingulate cortex were most active for trust to unknown peers. The mPFC showed increased activity with age and consistent relations with individual differences in feeling needed/useful.

Data‐driven neuroanatomical subtype trajectories of primary progressive aphasia

AbstractBackgroundPrimary progressive aphasia (PPA) is an atypical neurodegenerative dementia with three main clinical variants: semantic (svPPA), non‐fluent/agrammatic (nfvPPA) and logopenic (lvPPA). While svPPA is typically associated with left anterior temporal lobe atrophy, neuroimaging findings in nfvPPA, lvPPA and PPA not otherwise specified (PPA‐nos) are more variable. We therefore applied unsupervised machine learning to one of the largest databases of PPA magnetic resonance imaging (MRI) scans ever acquired.MethodBaseline MRI scans were collected from 273 people with PPA participating in the longitudinal research programme in the Queen Square Dementia Research Centre (svPPA n = 97; nfvPPA n = 109; lvPPA n = 51; PPA‐nos n = 16). Longitudinal scans were collected from 138 participants. We used Subtype and Stage Inference (SuStaIn), a model that combines disease progression modelling with unsupervised machine learning to identify subgroups of patients following a similar trajectory. We standardised the data with respect to cognitively normal controls (n = 360). Based on clinicians’ input we chose 19 brain regions of interest to model from those generated by GIF (Cardoso et al. 2012). The model was fit using baseline data, selecting the appropriate number of subtypes using cross‐validation (Young et al. 2018).ResultCross‐validation supported four subtypes of spatiotemporal atrophy (Figure 1). Clinical variant representation per subtype assignment (1/2/3/4) was: svPPA (n = 74/15/4/4), nfvPPA (n = 3/35/21/44), lvPPA (n = 1/18/30/2) and PPA‐nos (n = 7/4/3/2) (Figure 2). Subtype 1 showed early decline in the left anterior temporal lobe and sparing of the left frontal lobe. Subtype 2 showed early decline of the left insula and sparing of the temporal pole. Subtype 3 showed initial atrophy of the left temporoparietal junction; Subtype 4 showed early atrophy in the left precentral gyrus. Statistical analysis of posterior distributions found low similarity between subtypes (Hellinger distance > 0.66) (Figure 3), validating the presence of four distinct subtypes.ConclusionWhile the data‐driven atrophy subtypes did not align perfectly with clinical variants, we found a correspondence between Subtype 1 and svPPA, the most coherent PPA variant. Subtypes 2,3 and 4 were associated with nfvPPA and lvPPA, corroborating work suggesting these diagnostic terms encompass multiple clinical phenotypes. Future work will investigate the association between clinical diagnosis, longitudinal subtype, and clinical measures.

Data‐driven neuroanatomical subtype trajectories of primary progressive aphasia

AbstractBackgroundPrimary progressive aphasia (PPA) is an atypical neurodegenerative dementia with three main clinical variants: semantic (svPPA), non‐fluent/agrammatic (nfvPPA) and logopenic (lvPPA). While svPPA is typically associated with left anterior temporal lobe atrophy, neuroimaging findings in nfvPPA, lvPPA and PPA not otherwise specified (PPA‐nos) are more variable. We therefore applied unsupervised machine learning to one of the largest databases of PPA magnetic resonance imaging (MRI) scans ever acquired.MethodBaseline MRI scans were collected from 273 people with PPA participating in the longitudinal research programme in the Queen Square Dementia Research Centre (svPPA n = 97; nfvPPA n = 109; lvPPA n = 51; PPA‐nos n = 16). Longitudinal scans were collected from 138 participants. We used Subtype and Stage Inference (SuStaIn), a model that combines disease progression modelling with unsupervised machine learning to identify subgroups of patients following a similar trajectory. We standardised the data with respect to cognitively normal controls (n = 360). Based on clinicians’ input we chose 19 brain regions of interest to model from those generated by GIF (Cardoso et al. 2012). The model was fit using baseline data, selecting the appropriate number of subtypes using cross‐validation (Young et al. 2018).ResultCross‐validation supported four subtypes of spatiotemporal atrophy (Figure 1). Clinical variant representation per subtype assignment (1/2/3/4) was: svPPA (n = 74/15/4/4), nfvPPA (n = 3/35/21/44), lvPPA (n = 1/18/30/2) and PPA‐nos (n = 7/4/3/2) (Figure 2). Subtype 1 showed early decline in the left anterior temporal lobe and sparing of the left frontal lobe. Subtype 2 showed early decline of the left insula and sparing of the temporal pole. Subtype 3 showed initial atrophy of the left temporoparietal junction; Subtype 4 showed early atrophy in the left precentral gyrus. Statistical analysis of posterior distributions found low similarity between subtypes (Hellinger distance > 0.66) (Figure 3), validating the presence of four distinct subtypes.ConclusionWhile the data‐driven atrophy subtypes did not align perfectly with clinical variants, we found a correspondence between Subtype 1 and svPPA, the most coherent PPA variant. Subtypes 2,3 and 4 were associated with nfvPPA and lvPPA, corroborating work suggesting these diagnostic terms encompass multiple clinical phenotypes. Future work will investigate the association between clinical diagnosis, longitudinal subtype, and clinical measures.

Characterizing EEG signals of meditative states using persistent homology and Hodge spectral entropy

We present a novel topological characterization of EEG time series signals associated with two meditative states: autobiographical self-reflection and mantra-based meditation. The results demonstrate significant information geometric differences among the two groups of meditators and the control group for two brain regions, namely anterior frontal (AF) and temporoparietal (TP). The analysis involves global topological invariants and persistent homology features of the point cloud data constructed from the EEG time series using Takens’s embedding. While traditional EEG analyses face the well-known issues of noise and artefacts, the persistent homology approach is robust to them due to its emphasis on the overall topological changes rather than the transient structures. We analyse the characteristics of the Betti areas, peak location of Betti curves, persistent entropy, persistent amplitude and Hodge spectral entropy of the meditative states for up to the second homology dimension. We find that the mantra- based meditative state is rich in persistent features compared to autobiographical self-reflection. Also, the entropic measures indicate reduced chaotic dynamics and enhanced topological structure formation for the former. Moreover, the correlation of Hodge spectral entropy with persistent entropy or Betti area in a group is a key feature in differentiating the TP and AF channels. These topological features can be used to classify the meditative states with more than 95% accuracy.

Transcranial direct current stimulation of the right temporoparietal junction facilitates hippocampal spatial learning in Alzheimer’s disease and mild cognitive impairment

ObjectiveSpatial memory deficits are an early symptom in Alzheimer’s disease (AD), reflecting the neurodegenerative processes in the neuronal navigation network such as in hippocampal and parietal cortical areas. As no effective treatment options are available, neuromodulatory interventions are increasingly evaluated. Against this backdrop, we investigated the neuromodulatory effect of anodal transcranial direct current stimulation (tDCS) on hippocampal place learning in patients with AD or mild cognitive impairment (MCI). MethodsIn this randomized, double-blind, sham-controlled study with a cross-over design anodal tDCS of the right temporoparietal junction (2 mA for 20 minutes) was applied to 20 patients diagnosed with AD or MCI and in 22 healthy controls while they performed a virtual navigation paradigm testing hippocampal place learning. ResultsWe show an improved recall performance of hippocampal place learning after anodal tDCS in the patient group compared to sham stimulation but not in the control group. ConclusionsThese results suggest that tDCS can facilitate spatial memory consolidation via stimulating the parietal-hippocampal navigation network in AD and MCI patients. SignificanceOur findings suggest that tDCS of the temporoparietal junction may restore spatial navigation and memory deficits in patients with AD and MCI.

Lower cortical thickness and increased brain aging in adults with cocaine use disorder.

Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.

Decisional brain of lawyers at the workplace. A neurolaw pilot study

Decisional brain of lawyers at the workplace. A neurolaw pilot study

Cortical microstructural brain network mediates the association between personality trait of agreeableness and life satisfaction.

Personality traits are commonly regarded as relatively stable, whereas life satisfaction can fluctuate with time and circumstances, shaped by external influences and personal encounters. The correlation between personality traits and life satisfaction is well-established, yet the underlying neural mechanisms of the myelin-based microstructural brain network connecting them remain unclear. Here, we constructed individual-level whole-brain myelin microstructural networks from the MRI data of 1,043 healthy adults and performed correlation analysis to detect significant personality trait-related and life satisfaction-related subnetworks. A mediation analysis was used to verify whether the shared structural basis of personality traits and life satisfaction significantly mediated their association. The results showed that agreeableness positively correlated with life satisfaction. We identified a shared structural basis of the personality trait of agreeableness and life satisfaction. The regions comprising this overlapping network include the superior parietal lobule, inferior parietal lobule, and temporoparietal junction. Moreover, the shared microstructural connections mediate the association between the personality trait of agreeableness and life satisfaction. This large-scale neuroimaging investigation substantiates a mediation framework for understanding the microstructural connections between personality and life satisfaction, offering potential targets for assessment and interventions to promote human well-being.

Neural tracking ofsocial hierarchies inadolescents' real-world social networks.

In the current study, we combined sociometric nominations and neuroimaging techniques to examine adolescents' neural tracking of peers from their real-world social network that varied in social preferences and popularity. Adolescent participants from an entire school district (N = 873) completed peer sociometric nominations of their grade at school, and a subset of participants (N = 117, Mage = 13.59 years) completed a neuroimaging task in which they viewed peer faces from their social networks. We revealed two neural processes by which adolescents track social preference: (1) the fusiform face area, an important region for early visual perception and social categorization, simultaneously represented both peers high in social preference and low in social preference; (2) the dorsolateral prefrontal cortex (DLPFC), which was differentially engaged in tracking peers high and low in social preference. No regions specifically tracked peers high in popularity and only the inferior parietal lobe, temporoparietal junction, midcingulate cortex and insula were involved in tracking unpopular peers. This is the first study to examine the neural circuits that support adolescents' perception of peer-based social networks. These findings identify the neural processes that allow youths to spontaneously keep track of peers' social value within their social network.

Transitioning from childhood into adolescence: A comprehensive longitudinal behavioral and neuroimaging study on prosocial behavior and social inclusion

Acting prosocially and feeling socially included are important factors for developing social relations. However, little is known about the development of neural trajectories of prosocial behavior and social inclusion in the transition from middle childhood to early adolescence. In this pre-registered study, we investigated the development of prosocial behavior, social inclusion, and their neural mechanisms in a three-wave longitudinal design (ages 7–13 years; NT1 = 512; NT2 = 456; NT3 = 336). We used the Prosocial Cyberball Game, a ball tossing game in which one player is excluded, to measure prosocial compensating behavior. Prosocial compensating behavior showed a linear developmental increase, similar to parent-reported prosocial behavior, whereas parent-reported empathy showed a quadratic trajectory with highest levels in late childhood. On a neural level we found a peak in ventral striatum activity during prosocial compensating behavior. Neural activity during social inclusion showed quadratic age effects in anterior cingulate cortex, insula, striatum, and precuneus, and a linear increase in temporo-parietal junction. Finally, changes in prosocial compensating behavior were negatively associated with changes in ventral striatum and mPFC activity during social inclusion, indicating an important co-occurrence between development in brain and social behavior. Together these findings shed a light on the mechanisms underlying social development from childhood into adolescence.

Neurocomputational mechanisms of biased impression formation in lonely individuals

Social impressions are fundamental in our daily interactions with other people but forming accurate impressions of our social partners can be biased to different extents. Loneliness has previously been suggested to induce biases that hinder the formation of accurate impressions of others for successful social bonding. Here, we demonstrated that despite counterfactual evidence, negative first impressions bias information weighting, leading to less favorable trustworthiness beliefs. Lonely individuals did not only have more negative expectations of others’ social behavior, but they also manifested a stronger weighting bias. Reduced orbitofrontal cortex (OFC) activity was associated with a stronger weighting bias in lonelier individuals and mediated the relationship between loneliness and this weighting bias. Importantly, stronger coupling between OFC and temporoparietal junction compensated for such effects, promoting more positive trustworthiness beliefs especially in lonelier individuals. These findings bear potential for future basic and clinical investigations on social cognition and the development of clinical symptoms linked to loneliness.

Causal roles ofprefrontal andtemporo-parietal theta oscillations forinequity aversion.

The right temporo-parietal junction (rTPJ) and the right lateral prefrontal cortex (rLPFC) are known to play prominent roles in human social behaviour. However, it remains unknown which brain rhythms in these regions contribute to trading-off fairness norms against selfish interests as well as whether the influence of these oscillations depends on whether fairness violations are advantageous or disadvantageous for a decision maker. To answer these questions, we used non-invasive transcranial alternating current stimulation (tACS) to determine which brain rhythms in rTPJ and rLPFC are causally involved in moderating aversion to advantageous and disadvantageous inequity. Our results show that theta oscillations in rTPJ strengthen the aversion to unequal splits, which is statistically mediated by the rTPJ's role for perspective taking. In contrast, theta tACS over rLPFC enhanced the preference for outcome-maximizing unequal choices more strongly for disadvantageous compared to advantageous outcome distributions. Taken together, we provide evidence that neural oscillations in rTPJ and rLPFC have distinct causal roles in implementing inequity aversion, which can be explained by their involvement in distinct psychological processes.

Inter-brain neural mechanism and influencing factors underlying different cooperative behaviors: a hyperscanning study.

Cooperative behavior is a vital social interaction which plays a vital role in improving human survival and reproduction. However, few empirical studies have examined the differences between cooperative behaviors and the underlying neural substrates. In the present study, the brain activity of familiar dyads of the same sex was measured using functional near-infrared spectroscopy during three cooperative tasks (cooperative button-press, tangram, and Jenga tasks). We also measured the dyads' empathic abilities and personality traits to investigate the relationships between individual characteristics and neural markers. The results showed that first, there were significant differences in intra-brain activation and inter-brain synchronization among different cooperative tasks in three dimensions: social cognition, behavioral response, and cognitive processing. Second, male participants require stronger intra-brain activation to achieve the same inter-brain synchronization level as women in cooperative tasks. Third, when performing cooperative tasks involving high cognitive demands, Big Five Neuroticism may be an important predictor of neural activation in female participants. Inter-brain synchronization plays an important role in the frontal and temporoparietal junctions during interpersonal cooperation. Furthermore, this study demonstrates that mutual prediction theory is crucial for understanding the neural mechanisms of cooperative behavior.