Biology subjects

Isato, A.

Publications and source records attributed to Isato, A..

4 recordsLinked to original sources

bioRxiv2024

Superiority illusion in older adults: volume and functional connectivity of the precuneus

AimPositive thinking, which has been known to extend the lifespan, tends to increase with age. One specific form of positive thinking, the superiority illusion (SI), involves the belief that one is better than others. Despite its potential benefits in aging, the neural basis of the SI in elderly populations remains underexplored. MethodsThis study combined a behavioral task, voxel-based morphometry (VBM), and resting-state functional connectivity (rsFC) analyses to investigate the neural substrates of the SI in a cohort of 100 participants, including young (N = 33), middle-aged (N = 33), and older adults (N = 34). ResultsOur findings indicated that higher SI scores in older adults were correlated with greater gray matter volume in the right precuneus and stronger rsFC between the right precuneus and the left lateral occipital cortex. However, these correlations were not evident in younger and middle-aged groups. ConclusionsOur findings underscore the importance of the right precuneus and its connectivity in the manifestation of the SI, particularly in older adults, highlighting its potential role in adaptive aging processes.

neuroscience↗

bioRxiv2022

Machine learning unveils latent architecture of superiority illusion that predicts visual illusion perception and metacognitive performance

Humans are typically inept at evaluating their abilities and predispositions, while often disregarding such lack of metacognitive insight into their capacities and even augmenting (albeit illusorily) self-evaluation such that they should have more desirable traits than an average peer. This superiority illusion helps maintain a healthy mental state. However, the scope and range of its influence on broader human behavior, especially perceptual tasks, remain elusive. As belief shapes the way people perceive and recognize, the illusory self-superiority belief potentially regulates our perceptual and metacognitive performance. In this study, we used hierarchical Bayesian estimation and machine learning of signal detection theoretic measures to understand how superiority illusion influences visual perception and metacognition for Ponzo illusion. Our results demonstrated that superiority illusion correlated with visual illusion magnitude and metacognitive performance. Next, we used machine learning with a relaxed elastic net and unveiled the latent architecture that underlies the correlations. We revealed that the "extraversion" superiority dimension tapped into visual illusion magnitude and metacognitive ability. In contrast, the "honesty-humility" and "neuroticism" dimensions were only predictive of visual illusion magnitude and metacognitive ability, respectively. These results suggest common and distinct influences of superiority features on perceptual sensitivity and metacognition. Our findings contribute to the accumulating body of evidence indicating that the superiority illusion leverage is far-reaching, even to visual perception. Significance StatementsPeople have a cognitive bias to overestimate their abilities above the mean (superiority illusion) and thereby help maintain a healthy mental state. In this work, we show that the influences of superiority illusion are more extensive than previously thought. We find that superiority illusion correlated with visual illusion magnitude and metacognitive performance. Furthermore, using hierarchical Bayesian estimation and machine learning, we unveil the latent architecture (i.e., overlapping yet dissociable superiority features) that predicts visual illusion magnitude and metacognitive performance. These findings suggest that superiority illusion is a cardinal cognitive bias that involves a vast assortment of behavior as an illusion is an efficient and adaptive tool for humans to somehow thrive in a world of ambiguity.

neuroscience↗

bioRxiv2022

Neural network of superiority illusion predicts the level of dopamine in striatum

In evaluating the personality attributes and performance of the self, people are inclined to view themselves superior to others, a phenomenon known as superiority illusion (SI). This illusive outlook pervades peoples thoughts, creating hope for the future and promoting mental health. Although a specific cortico-striatal functional connectivity (FC) under dopaminergic modulation was previously shown to be implicated in SI, the underlying whole-brain mechanisms have remained unclarified. Herein, to reveal the neural network subserving individuals SI, we conducted a data-driven, machine-learning investigation to explore the resting-state FC network across the whole brain. Using the locally-acquired resting-state functional magnetic resonance imaging data (n = 123), we identified a set of 15 FCs most informative in classifying individuals with higher-versus lower-than-average levels of SI in evaluating positive trait words (area under the curve [AUC] = 0.81). Among the 15 FCs, the contribution level to the classification was 11% by the previously-highlighted cortico-striatal FC alone, but 60% by the encompassing cortico-limbico-striatal network cluster. A newly-identified, cortico-thalamic FC and another FC cluster also demonstrated substantial contribution. The classification accuracy was generalized into an independent cohort (n = 36; AUC = 0.73). Importantly, using the same set of 15 FCs, we achieved prediction on an individuals level of striatal dopamine D2 receptor availability (Pearson correlation, r = 0.46, P = 0.005). This is the first successful identification of the whole-brain neural network that simultaneously predicts the behavioral manifestation and molecular underpinning of an essential psychological process that promotes well-being and mental health. Significance StatementSuperiority illusion (SI) is a basic self-referential framework that pervades peoples thoughts and promotes well-being and mental health. An aberrant form of SI has been reported in psychiatric conditions such as depression. Our hypothesis-free, data-driven investigation revealed the spatially-distributed neural network that for the first time achieved prediction on an individuals levels of SI and the striatal dopaminergic transmission simultaneously. In principle, this multiple-biological-layer framework can be applicable to any behavioral trait to establish a link with its underlying neural network and neurochemical properties, which could quantitatively present the relation of its aberrant form with the pathophysiology of neuropsychiatric disorders. Future clinical research may aid in deriving a diagnostic biomarker for examining the related behavioral and neurochemical characteristics within individuals.

neuroscience↗

bioRxiv2021

Resting-state functional connectivity relates to interindividual variations in positive memory

Individual differences in positive memory recollection are of interest in mental health, as positive memories can help protect people against stress and depression. However, it is unclear how individual differences in positive memory recollection are reflected in brain activity in the resting state. Here, we investigate the resting-state functional connectivity (FC) associated with interindividual variations in positive memory by employing cluster-level inferences based on randomization/permutation region of interest (ROI)-to-ROI analyses. We identified a cluster of FCs that was positively associated with positive memory performance, including the frontal operculum, central operculum, parietal operculum, Heschls gyrus, and planum temporale. The current results suggest that positive memory is innervated by frontotemporal network connectivity, which may have implications for future investigations of vulnerability to stress and depression.

neuroscience↗