The self survives extinction: Self-association biases attention in patients with visual extinction

A multiverse assessment of the reliability of the self-matching task as a measurement of the self-prioritization effect

The self-matching task (SMT) is widely used to investigate the cognitive mechanisms underlying the self-prioritization effect (SPE), wherein performance is enhanced for self-associated stimuli compared to other-associated ones. Although the SMT robustly elicits the SPE, there is a lack of data quantifying the reliability of this paradigm. This is problematic, given the prevalence of the reliability paradox in cognitive tasks: many well-established cognitive tasks demonstrate relatively low reliability when used to evaluate individual differences, despite exhibiting replicable effects at the group level. To fill this gap, this preregistered study investigated the reliability of SPE derived from the SMT using a multiverse approach, combining all possible indicators and baselines reported in the literature. We first examined the robustness of 24 SPE measures across 42 datasets (N = 2250) using a meta-analytical approach. We then calculated the split-half reliability (r) and intraclass correlation coefficient (ICC2) for each SPE measure. Our findings revealed a robust group-level SPE across datasets. However, when evaluating individual differences, SPE indices derived from reaction time (RT) and efficiency exhibited relatively higher, compared to other SPE indices, but still unsatisfied split-half reliability (approximately 0.5). The reliability across multiple time points, as assessed by ICC2, RT, and efficiency, demonstrated moderate levels of test-retest reliability (close to 0.5). These findings revealed the presence of a reliability paradox in the context of SMT-based SPE assessment. We discussed the implications of how to enhance individual-level reliability using this paradigm for future study design.

Causal Roles of Ventral and Dorsal Neural Systems for Automatic and Control Self-Reference Processing: A Function Lesion Mapping Study

Background: Humans perceive and interpret the world through the lens of self-reference processes, typically facilitating enhanced performance for the task at hand. However, this research has predominantly emphasized the automatic facet of self-reference processing, overlooking how it interacts with control processes affecting everyday situations. Methods: We investigated this relationship between automatic and control self-reference processing in neuropsychological patients performing self-face perception tasks and the Birmingham frontal task measuring executive functions. Results: Principal component analysis across tasks revealed two components: one loaded on familiarity/orientation judgments reflecting automatic self-reference processing, and the other linked to the cross task and executive function indicating control processing requirements. Voxel-based morphometry and track-wise lesion-mapping analyses showed that impairments in automatic self-reference were associated with reduced grey matter in the ventromedial prefrontal cortex and right inferior temporal gyrus, and white matter damage in the right inferior fronto-occipital fasciculus. Deficits in executive control were linked to reduced grey matter in the bilateral inferior parietal lobule and left anterior insula, and white matter disconnections in the left superior longitudinal fasciculus and arcuate fasciculus. Conclusions: The causal evidence suggests that automatic and control facets of self-reference processes are subserved by distinct yet integrated ventral prefrontal-temporal and dorsal frontal-parietal networks, respectively.

Self as a prior: The malleability of Bayesian multisensory integration to social salience

Our everyday perceptual experiences are grounded in the integration of information within and across our senses. Due to this direct behavioural relevance, cross-modal integration retains a certain degree of contextual flexibility, even to social relevance. However, how social relevance modulates cross-modal integration remains unclear. To investigate possible mechanisms, Experiment 1 tested the principles of audio-visual integration for numerosity estimation by deriving a Bayesian optimal observer model with perceptual prior from empirical data to explain perceptual biases. Such perceptual priors may shift towards locations of high salience in the stimulus space. Our results showed that the tendency to over- or underestimate numerosity, expressed in the frequency and strength of fission and fusion illusions, depended on the actual event numerosity. Experiment 2 replicated the effects of social relevance on multisensory integration from Scheller & Sui, 2022 JEP:HPP, using a lower number of events, thereby favouring the opposite illusion through enhanced influences of the prior. In line with the idea that the self acts like a prior, the more frequently observed illusion (more malleable to prior influences) was modulated by self-relevance. Our findings suggest that the self can influence perception by acting like a prior in cue integration, biasing perceptual estimates towards areas of high self-relevance.

The self and conscious experience

The primary determinant of the self (S) is the conscious experience (CE) we have of it. Therefore, it does not come as a surprise that empirical research on S mainly resorts to the CE (or lack of CE) that subjects have of their S. What comes as a surprise is that empirical research on S does not tackle the problem of how CE contributes to building S. Empirical research investigates how S either biases the cognitive processing of stimuli or is altered through a wide range of means (meditation, hypnosis, etc.). In either case, even for different reasons, considerations of how CE contributes to building S are left unspecified in empirical research. This article analyzes these reasons and proposes a theoretical model of how CE contributes to building S. According to the proposed model, the phenomenal aspect of consciousness is produced by the modulation-engendered by attentional activity-of the energy level of the neural substrate (that is, the organ of attention) that underpins attentional activity. The phenomenal aspect of consciousness supplies the agent with a sense of S and informs the agent on how its S is affected by the agent's own operations. The phenomenal aspect of consciousness performs its functions through its five main dimensions: qualitative, quantitative, hedonic, temporal, and spatial. Each dimension of the phenomenal aspect of consciousness can be explained by a specific aspect of the modulation of the energy level of the organ of attention. Among other advantages, the model explains the various forms of S as outcomes resulting from the operations of a single mechanism and provides a unifying framework for empirical research on the neural underpinnings of S.

Decoding individual differences in self-prioritization from the resting-state functional connectome

Although the self has traditionally been viewed as a higher-order mental function by most theoretical frameworks, recent research advocates a fundamental self hypothesis, viewing the self as a baseline function of the brain embedded within its spontaneous activities, which dynamically regulates cognitive processing and subsequently guides behavior. Understanding this fundamental self hypothesis can reveal where self-biased behaviors emerge and to what extent brain signals at rest can predict such biased behaviors. To test this hypothesis, we investigated the association between spontaneous neural connectivity and robust self-bias in a perceptual matching task using resting-state functional magnetic resonance imaging (fMRI) in 348 young participants. By decoding whole-brain connectivity patterns, the support vector regression model produced the best predictions of the magnitude of self-bias in behavior, which was evaluated via a nested cross-validation procedure. The out-of-sample generalizability was further authenticated using an external dataset of older adults. The functional connectivity results demonstrated that self-biased behavior was associated with distinct connections between the default mode, cognitive control, and salience networks. Consensus network and computational lesion analyses further revealed contributing regions distributed across six networks, extending to additional nodes, such as the thalamus, whose role in self-related processing remained unclear. These results provide evidence that self-biased behavior derives from spontaneous neural connectivity, supporting the fundamental self hypothesis. Thus, we propose an integrated neural network model of this fundamental self that synthesizes previous theoretical models and portrays the brain mechanisms by which the self emerges at rest internally and regulates responses to the external environment.

Visuospatial perception is not affected by self-related information

Previous research suggests that attention is drawn by self-related information. Three online experiments were conducted to investigate whether self-related stimuli alter visuospatial perceptual judgments. In a matching task, associations were learned between labels ('Yourself'/friend/stranger's name) paired with cues. Cues were coloured outlines (Experiment 1, N = 135), geometric shapes (Experiment 2, N = 102), or coloured gradients (Experiment 3, N = 110). Visuospatial perception bias was measured with a greyscales task. Cues were presented prior to, and/or alongside greyscales. We hypothesized there would be a bias towards the self-related cue. In all experiments, we found a self-related bias in the matching task. Furthermore, there was an overall leftward visuospatial perceptual bias (pseudoneglect). However, we found anecdotal to moderate evidence for the absence of an effect of self-related cues on visuospatial perception judgments. Although self-related stimuli influence how our attention is oriented to stimuli, attention mechanisms that influence perceptual judgements are seemingly not affected by a self-bias.

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.

The upside-down self: One's own face recognition is affected by inversion

One's own face is recognized more efficiently than any other face, although the neural mechanisms underlying this phenomenon remain poorly understood. Considering the extensive visual experience that we have with our own face, some authors have proposed that self-face recognition involves a more analytical perceptual strategy (i.e., based on face features) than other familiar faces, which are commonly processed holistically (i.e., as a whole). However, this hypothesis has not yet been tested with brain activity data. In the present study, we employed an inversion paradigm combined with event-related potential (ERP) recordings to investigate whether the self-face is processed more analytically. Sixteen healthy participants were asked to identify their own face and a familiar face regardless of its orientation, which could either be upright or inverted. ERP analysis revealed an enhanced amplitude and a delayed latency for the N170 component when faces were presented in an inverted orientation. Critically, both the self and a familiar face were equally vulnerable to the inversion effect, suggesting that the self-face is not processed more analytically than a familiar face. In addition, we replicated the recent finding that the attention-related P200 component is a specific neural index of self-face recognition. Overall, our results suggest that the advantage for self-face processing might be better explained by the engagement of self-related attentional mechanisms than by the use of a more analytical visuoperceptual strategy.

Self-prioritization and the attentional systems

Humans prioritize stimuli related to themselves rather than to other people. How we control these priorities is poorly understood, though it is relevant to the nature of self-processing and a wide range of neurological and neuropsychiatric disorders, from cases of strokes, dementia to depression and schizophrenia. We update the Self-Attention Network proposed in 2016 by evaluating how self-prioritization interacts with Peterson and Posner's three attentional systems: alerting, orienting and executive control, based on evidence on a variety of behavioral and neuroscientific studies with healthy participants and patients with brain lesions. We suggest that all the three attentional networks contribute to self-prioritization. Understanding the nature of self-prioritization in attentional contexts may provide important clinical implications for a variety of disorders related to self-processing.

Conscious awareness of self-relevant information is necessary for an incidental self-memory advantage

Co-presenting an item with self-relevant vs. other-relevant information under a non-self-referential encoding context can produce a memory advantage. The present study examined the relative contributions of conscious vs. unconscious processing of self-cues to this incidental self-memory advantage. During encoding, the participant's own or another person's name was presented supraliminally or subliminally prior to the presentation of each target word. Consistent across two experiments, we found better memory for words preceded by the own name vs. another name but only when the names were presented supraliminally. The masked priming effect produced by the own name in Experiment 2 suggests that the absence of a self-memory advantage following subliminal name presentation was unlikely due to subliminal self-processing being too weak. Our findings suggest that conscious awareness of self-cues is necessary for an incidental self-memory advantage. Potential qualitative differences between conscious vs. unconscious self-processing mediating the impact of self on memory are discussed.