Self-Positivity or Self-Negativity as a Function of the Medial Prefrontal Cortex

Self-prioritization in working memory gating

Working memory (WM) involves a dynamic interplay between temporary maintenance and updating of goal-relevant information. The balance between maintenance and updating is regulated by an input-gating mechanism that determines which information should enter WM (gate opening) and which should be kept out (gate closing). We investigated whether updating and gate opening/closing are differentially sensitive to the kind of information to be encoded and maintained in WM. Specifically, since the social salience of a stimulus is known to affect cognitive performance, we investigated if self-relevant information differentially impacts maintenance, updating, or gate opening/closing. Participants first learned to associate two neutral shapes with two social labels (i.e., "you" vs. "stranger"), respectively. Subsequently they performed the reference-back paradigm, a well-established WM task that disentangles WM updating, gate opening, and gate closing. Crucially, the shapes previously associated with the self or a stranger served as target stimuli in the reference-back task. We replicated the typical finding of a repetition benefit when consecutive trials require opening the gate to WM. In Study 1 (N = 45) this advantage disappeared when self-associated stimuli were recently gated into WM and immediately needed to be replaced by stranger-associated stimuli. However, this was not replicated in a larger sample (Study 2; N = 90), where a repetition benefit always occurred on consecutive gate-opening trials. Overall, our results do not provide evidence that the self-relevance of stimuli modulates component processes of WM. We discuss possible reasons for this null finding, including the importance of continuous reinstatement and task-relevance of the shape-label associations.

The oscillatory fingerprints of self-prioritization: Novel markers in spectral EEG for self-relevant processing

Self-prioritization is a very influential modulator of human information processing. Still, little is known about the time-frequency dynamics of the self-prioritization network. In this EEG study, we used the familiarity-confound free matching task to investigate the spectral dynamics of self-prioritization and their underlying cognitive functions in a drift-diffusion model. Participants (N = 40) repeatedly associated arbitrary geometric shapes with either "the self" or "a stranger." Behavioral results demonstrated prominent self-prioritization effects (SPEs) in reaction time and accuracy. Remarkably, EEG cluster analysis also revealed two significant SPEs, one in delta/theta power (2-7 Hz) and one in beta power (19-29 Hz). Drift-diffusion modeling indicated that beta activity was associated with evidence accumulation, whereas delta/theta activity was associated with response selection. The decreased beta suppression of the SPE might indicate more efficient sensorimotor processing of self-associated stimulus-response features, whereas the increased delta/theta SPE might refer to the facilitated retrieval of self-relevant features across a widely distributed associative self-network. These novel oscillatory biomarkers of self-prioritization indicate their function as an associative glue for the self-concept.

To see or not to see: the parallel processing of self-relevance and facial expressions

The self, like the concept of central "gravity", facilitates the processing of information that is directly relevant to the self. This phenomenon is known as the self-prioritization effect. However, it remains unclear whether the self-prioritization effect extends to the processing of emotional facial expressions. To fill this gap, we used a self-association paradigm to investigate the impact of self-relevance on the recognition of emotional facial expressions while controlling for confounding factors such as familiarity and overlearning. Using a large and diverse sample, we replicated the effect of self-relevance on face processing but found no evidence for a modulation of self-relevance on facial emotion recognition. We propose two potential theoretical explanations to account for these findings and emphasize that further research with different experimental designs and a multitasks measurement approach is needed to understand this mechanism fully. Overall, our study contributes to the literature on the parallel cognitive processing of self-relevance and facial emotion recognition, with implications for both social and cognitive psychology.

Accentuate the positive: Evidence that context dependent self-reference drives self-bias

There is abundant evidence of a self-bias in cognition, with prioritised processing of information that is self-relevant. There is also abundant evidence of a positivity-bias in cognition, with prioritised processing of information that is positively valenced (e.g., positive emotional expressions, rewards). While the effects of self-bias and positivity-bias have been well documented in isolation, they have seldom been examined in parallel, so it is unclear whether one or other of these stimulus classes is prioritised or whether they interact. Addressing this gap, the current research aimed to establish the relative primacy of self-bias and positivity-bias using a classification task that paired self-relevant information with emotional expressions (i.e., Expt. 1) or reward information (i.e., Expt. 2). When the self was paired with relatively more positive information (i.e., smiling faces or high reward) we found evidence of a self-bias but no evidence of a positivity-bias. Whereas when the self was paired with relatively less positive information (i.e., neutral faces or low reward) we found evidence of a positivity-bias but no evidence of a self-bias. These results suggest the relative primacy of prioritised processing is flexible, context dependent and might be caused by a drive towards self-enhancement and the self-positivity bias.

Self-Prioritization Reconsidered: Scrutinizing Three Claims

Such is the power of self-relevance, it has been argued that even arbitrary stimuli (e.g., shapes, lines, colors) with no prior personal connection are privileged during information processing following their association with the self (i.e., self-prioritization). This prioritization effect, moreover, is deemed to be stimulus driven (i.e., automatic), grounded in perception, and supported by specialized processing operations. Here, however, we scrutinize these claims and challenge this viewpoint. Although self-relevance unquestionably influences information processing, we contend that, at least at present, there is limited evidence to suggest that the prioritization of arbitrary self-related stimuli is compulsory, penetrates perception, and is underpinned by activity in a dedicated neural network. Rather, self-prioritization appears to be a task-dependent product of ordinary cognitive processes.

Altered regional brain activity and functional connectivity in resting-state brain networks associated with psychological erectile dysfunction

Introduction

Erectile dysfunction (ED), especially psychological ED (pED), is usually accompanied with psychological factors, which are related to abnormal activity in brain regions involved in sexual behavior. However, the mechanisms underlying functional changes in the brain of pED are still unclear. The present study aimed to explore the abnormalities of brain function, as well as their relationships with sexual behavior and emotion in pED patients.

Materials and methods

Resting state functional magnetic resonance imaging (rs-fMRI) data were collected from 31 pED patients to 31 healthy controls (HCs). The values of amplitude of fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) were calculated and compared between groups. In addition, the associations between abnormal brain regions and clinical features were evaluated by Pearson correlation analyses.

Results

Compared to HCs, pED patients demonstrated decreased fALFF values in the left medial superior frontal gyrus (had decreased FC values with the left dorsolateral superior frontal gyrus), the left lingual gyrus (had decreased FC values with the left parahippocamal gyrus and insula), the left putamen (had decreased FC values with the right caudate) and the right putamen (had decreased FC values with the left putamen and the right caudate). The fALFF values of the left medial superior frontal gyrus were negatively correlated with the fifth item scores of International Index of Erectile Function (IIEF-5). Negative relationships were found between fALFF values of the left putamen and the second item scores of Arizona Sexual Scale (ASEX). FC values between the right putamen and caudate were negatively related to the state scores of State-Trait Anxiety Inventory (STAI-S).

Conclusion

Altered brain function were found in the medial superior frontal gyrus and caudate-putamen of pED patients, which were associated with sexual function and psychological condition. These findings provided new insights into the central pathological mechanisms of pED.

The relationship between self, value-based reward, and emotion prioritisation effects

People show systematic biases in perception, memory, attention, and decision-making to prioritise information related to self, reward, and positive emotion. A long-standing set of experimental findings points towards putative common properties of these effects. However, the relationship between them remains largely unknown. Here, we addressed this question by assessing and linking these prioritisation effects generated by a common associative matching procedure in three experiments. Self, reward, and positive emotion prioritisation effects were assessed using cluster and shift function analyses to explore and test associations between these effects across individuals. Cluster analysis revealed two distinct patterns of the relationship between the biases. Individuals with faster responses showed a smaller reward and linear positive association between reward and emotion biases. Individuals with slower responses demonstrated a large reward and no association between reward and emotion biases. No evidence of the relationship between self and value-based reward or positive emotion prioritisation effects was found among the clusters. A shift function indicated a partial dominance of high-reward over low-reward distributions at later processing stages in participants with slower but not faster responses. Full stochastic dominance of self-relevance over others and positive over neutral emotion was pertinent to each subgroup of participants. Our findings suggest the independent origin of the self-prioritisation effect. In contrast, commonalities in cognitive mechanisms supporting value-based reward and positive emotion processing are subject to individual differences. These findings add important evidence to a steadily growing research base about the relationship between basic behavioural drivers.

Depression screening using a non-verbal self-association task: A machine-learning based pilot study

BACKGROUND

Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clinical use of non-verbal depression screening is nascent, yet a promising and viable candidate to supplement verbal screening. Differential self- and emotion-processing in depression patients were previously reported by non-verbal behavioural assessments, corroborated by neuroimaging findings of distinct neuroanatomical markers. Thus non-verbal validated brain-behaviour based self-emotion-related assessment data reflect physiological differences and may support individual level screening of depression.

METHODS

In this pilot study (n = 84) we collected two longitudinal sessions of behavioural assessment data in a laboratory setting. Depression was assessed using Beck Depression Inventory II (BDI-II), to explore optimal screening methods with machine-learning, and to establish the validity of adapting a novel behavioural assessment focusing on self and emotions for depression screening.

RESULTS

The best machine-learning model achieved high performance in depression screening, 10-Fold cross-validation (CV) Area Under the receiver operating characteristic Curve (AUC) of 0.90 and balanced accuracy of 0.81, using a Gradient Boosting algorithm. Prospective prediction using a model trained with session 1 data to predict session 2 depression status achieved a 10-Fold CV AUC of 0.77 and balanced accuracy of 0.66. We also identified interpretable behavioural signatures for depression patients based on the best model.

CONCLUSION

The study supports the utility of using behavioural data as a viable and cost-effective solution for depression screening, with a potential wide range of applications in clinical settings.

Inferring Brain State Dynamics Underlying Naturalistic Stimuli Evoked Emotion Changes With dHA-HMM

The brain functional mechanisms underlying emotional changes have been primarily studied based on the traditional task design with discrete and simple stimuli. However, the brain state transitions when exposed to continuous and naturalistic stimuli with rich affection variations remain poorly understood. This study proposes a dynamic hyperalignment algorithm (dHA) to functionally align the inter-subject neural activity. The hidden Markov model (HMM) was used to study how the brain dynamics responds to emotion during long-time movie-viewing activity. The results showed that dHA significantly improved inter-subject consistency and allowed more consistent temporal HMM states across participants. Afterward, grouping the emotions in a clustering dendrogram revealed a hierarchical grouping of the HMM states. Further emotional sensitivity and specificity analyses of ordered states revealed the most significant differences in happiness and sadness. We then compared the activation map in HMM states during happiness and sadness and found significant differences in the whole brain, but strong activation was observed during both in the superior temporal gyrus, which is related to the early process of emotional prosody processing. A comparison of the inter-network functional connections indicates unique functional connections of the memory retrieval and cognitive network with the cerebellum network during happiness. Moreover, the persistent bilateral connections among salience, cognitive, and sensorimotor networks during sadness may reflect the interaction between high-level cognitive networks and low-level sensory networks. The main results were verified by the second session of the dataset. All these findings enrich our understanding of the brain states related to emotional variation during naturalistic stimuli.

Differences in working memory coding of biological motion attributed to oneself and others

The question how the brain distinguishes between information about self and others is of fundamental interest to both philosophy and neuroscience. In this functional magnetic resonance imaging (fMRI) study, we sought to distinguish the neural substrates of representing a full‐body movement as one's movement and as someone else's movement. Participants performed a delayed match‐to‐sample working memory task where a retained full‐body movement (displayed using point‐light walkers) was arbitrarily labeled as one's own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self‐association was coded. Movement specific activation patterns were found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain‐general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self‐associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

Neural Connectivity Underlying Reward and Emotion-Related Processing: Evidence From a Large-Scale Network Analysis

Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritized effects in decision-making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention, and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behavior in relation to mental health.

Self-prioritization is supported by interactions between large-scale brain networks

Resting-state functional magnetic resonance imaging (fMRI) has provided solid evidence that the default-mode network (DMN) is implicated in self-referential processing. The functional connectivity of the DMN has also been observed in tasks where self-referential processing leads to self-prioritization (SPE) in perception and decision-making. However, we are less certain about whether (i) SPE solely depends on the interplay within parts of the DMN or is driven by multiple brain networks; and (ii) whether SPE is associated with a unique component of interconnected networks or can be explained by related effects such as emotion prioritization. We addressed these questions by identifying and comparing topological clusters of networks involved in self-and emotion prioritization effects generated in an associative-matching task. Using network-based statistics, we found that SPE controlled by emotion is supported by a unique component of interacting networks, including the medial prefrontal part of the DMN (MPFC), Frontoparietal network (FPN) and insular Salience network (SN). This component emerged as a result of a focal effect confined to few connections, indicating that interaction between DMN, FPC and SN is critical to cognitive operations for the SPE. This result was validated on a separate data set. In contrast, prioritization of happy emotion was associated with a component formed by interactions between the rostral prefrontal part of SN, posterior parietal part of FPN and the MPFC, while sad emotion reveals a cluster of the DMN, Dorsal Attention Network (DAN) and Visual Medial Network (VMN). We discussed theoretical and methodological aspects of these findings within the more general domain of social cognition.

Perceiving the Self and Emotions with an Anxious Mind: Evidence from an Implicit Perceptual Task

Anxiety disorders cause mental distress and low wellbeing in many people worldwide. Theories of anxiety describe negative worldviews and self-views as maintaining factors of the disorders. Recent research in social cognition has found a link between depression and altered perceptual biases to emotions, but the same research on anxiety is still missing. In this study, we measured perceptual biases to emotional and self-related stimuli in sub-clinically anxious participants and healthy controls using a self-emotional shape-label matching task. Results demonstrate that anxious participants had a diminished perceptual self-bias compared with healthy controls. Furthermore, the severity of anxiety was related to an emotional bias towards valanced other-related stimuli. The findings confirm the hypothesis that anxious individuals display an altered self-prioritisation effect in comparison with healthy individuals and that anxiety severity is linked to altered responses to emotionally valanced others. These findings have potential implications for early diagnosis and treatment of anxiety disorders.

A pre-existing self-referential anchor is not necessary for self-prioritisation

Self-prioritisation effect (SPE) has consistently occurred in perceptual matching tasks in which neutral stimuli are paired with familiar labels representing different identities (e.g., triangle-Self, square-Friend). Participants are faster and more accurate at judging self-related shape-label pairings than the pairings associated with others. Much evidence has suggested that the SPE is driven by the self acting as an integrative hub that enhances stimulus processing (e.g., triangle). However, there is a growing debate as to whether the SPE is genuine or determined by the labels (e.g., 'me', 'you') being pre-existing self-referential anchor points. We investigated this in an adapted perceptual matching task in which participants were instructed to associate arbitrary stimulus pairs (visual features: shape and colour) with different people and then immediately carried out a colour-shape matching task. The results showed the standard pattern of the SPE in this perceptual matching task without familiar labels, indicating that the effect is not critically dependent on familiar labels. Further analysis revealed that the SPE emerged only when the complete shape-colour pairing was presented rather than individual elements (self-shape or self-colour). The theoretical implications of these findings are considered.

Neurostructural correlates of dispositional self-compassion

Self-compassion is an important emotion regulation strategy predicting positive psychological health and fewer psychopathological problems, but little is known about its structural neural basis. In the current study, we investigated the neurostructural correlates of dispositional self-compassion and its components using voxel-based morphometry (VBM). We found that self-compassion was inversely correlated with gray matter volume (GMV) in the left dorsolateral prefrontal cortex (DLPFC), which was primarily driven by the reduced self-judgment component. We also found that the mindfulness component was associated with greater GMV in the dorsomedial prefrontal cortex/anterior cingulate cortex and the left supplementary motor area, while the isolation and the over-identification components were both correlated with greater GMV in the right inferior temporal gyrus, and over-identification additionally related to less GMV in visual areas. Our findings suggest that dispositional self-compassion and its components are associated with brain structure in regions involved in emotion regulation, self-referential and emotion processing, with implications for the cognitive and neural mechanisms of self-compassion as well as those underlying the effects of self-compassion on its health outcomes.

The divided brain: Functional brain asymmetry underlying self-construal

Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.