Information Processing Patterns Research Articles

Online health [mis]information processing and evaluation among older adults: Comparing individuals with varied abilities in information discernment

Older adults are vulnerable to online health misinformation. This study fills a research gap by exposing older adults to a mixture of health-related misinformation and factual information and employing the think-aloud protocol in a semi-structured interview to understand information processing and evaluation in the moment of information engagement. The participants were categorized into two groups based on their abilities to discern misinformation. Via thematic analysis, we compared the two groups and found distinctive information processing patterns between them. We propose guidelines for evaluating online misinformation based on the best practices of those who have a high capacity to discern the veracity of the information and pitfalls to avoid based on the experience of those who failed to correctly differentiate true and misinformation.

Emergence of input selective recurrent dynamics via information transfer maximization

Network structures of the brain have wiring patterns specialized for specific functions. These patterns are partially determined genetically or evolutionarily based on the type of task or stimulus. These wiring patterns are important in information processing; however, their organizational principles are not fully understood. This study frames the maximization of information transmission alongside the reduction of maintenance costs as a multi-objective optimization challenge, utilizing information theory and evolutionary computing algorithms with an emphasis on the visual system. The goal is to understand the underlying principles of circuit formation by exploring the patterns of wiring and information processing. The study demonstrates that efficient information transmission necessitates sparse circuits with internal modular structures featuring distinct wiring patterns. Significant trade-offs underscore the necessity of balance in wiring pattern development. The dynamics of effective circuits exhibit moderate flexibility in response to stimuli, in line with observations from prior visual system studies. Maximizing information transfer may allow for the self-organization of information processing functions similar to actual biological circuits, without being limited by modality. This study offers insights into neuroscience and the potential to improve reservoir computing performance.

Learning Styles and Information Processing Patterns of Science, Technology and Engineering (STE) Students

Learning Styles and Information Processing Patterns of Science, Technology and Engineering (STE) Students

Spiking generative adversarial network with attention scoring decoding

Generative models based on neural networks present a substantial challenge within deep learning. As it stands, such models are primarily limited to the domain of artificial neural networks. Spiking neural networks, as the third generation of neural networks, offer a closer approximation to brain-like processing due to their rich spatiotemporal dynamics. However, generative models based on spiking neural networks are not well studied. Particularly, previous works on generative adversarial networks based on spiking neural networks are conducted on simple datasets and do not perform well. In this work, we pioneer constructing a spiking generative adversarial network capable of handling complex images and having higher performance. Our first task is to identify the problems of out-of-domain inconsistency and temporal inconsistency inherent in spiking generative adversarial networks. We address these issues by incorporating the Earth-Mover distance and an attention-based weighted decoding method, significantly enhancing the performance of our algorithm across several datasets. Experimental results reveal that our approach outperforms existing methods on the MNIST, FashionMNIST, CIFAR10, and CelebA. In addition to our examination of static datasets, this study marks our inaugural investigation into event-based data, through which we achieved noteworthy results. Moreover, compared with hybrid spiking generative adversarial networks, where the discriminator is an artificial analog neural network, our methodology demonstrates closer alignment with the information processing patterns observed in the mouse. Our code can be found at https://github.com/Brain-Cog-Lab/sgad.

Personal values and social behavior in early childhood: Understanding the contribution of social information processing and attitudes

Values, defined by Schwartz (1994) as basic motivational cognitive structures, guide life goals, transcend contexts, and affect individuals’ courses of action differently depending on their preferred values. With young children, an important question that emerges is what factors underlie the linkages between their preferred motivations (i.e., preferred values) and their behavior tendencies in key social contexts. This study proposed one potential socio-cognitive mechanism that may explain how children’s values are linked to their prosocial and antisocial behaviors in kindergarten via their values-oriented social information processing patterns (SIP) and their attitudes toward their kindergarten. The sample included 121 children (59 girls; Mage = 67.45 months). Children’s values, values-oriented SIP patterns, and attitudes toward kindergarten class were examined in one-on-one interviews. Teachers reported on the children’s social behaviors. Results showed children’s preferences for self-transcendence values were linked to their more prosocial behaviors and less antisocial behaviors in class via their self-transcendence values-oriented SIP patterns and their positive attitudes toward kindergarten. The findings offer important insights into the socio-cognitive elements that drive values-behavior relationships, as well as the links between various facets of young children’s social cognition and their social behavior in kindergarten.

Examining the roles of visualizations in people's understanding of uncertain storm surge forecasts, interpretation of risk, and decision-making

Maps and other forms of geovisualizations play a central yet complex role in communicating weather hazard risks and threats to the public. Through designing storm surge risk communication prototypes and testing these visualizations in focus groups with residents of coastal communities in Georgia and South Carolina, this study investigates how different aspects of geospatial visualization influence individuals' understanding and relatability of storm surge information and how different elements of geospatial risk visualization influence people's intent to take protective actions. The focus group discussions revealed common themes and unique perspectives in the interpretation of hurricane storm surge flooding forecasts and illustrated the complexity of communicating risk and uncertainty to diverse populations. This study found a sequential pattern of visual information processing, beginning with understanding the content and its perceived accuracy and uncertainty, followed by personalizing the information and deciding on protective action. Showing storm surge forecast maps at multiple spatial scales was valuable, combined with realistic visualizations in the form of images or 3D animations of flooded buildings. Maps with recognizable places and labels helped study participants locate themselves and assess storm surge risks, although residents of urban, barrier island, and rural coastal communities interpreted the information in their local and personal context. Additional research is needed to understand how people interact with different types of storm surge forecast information and how to improve visual risk communication in ways that enhance people's understanding and responses to storm surge risk in the context of their local environment and prior experiences.

Spatial representation of multidimensional information in emotional faces revealed by fMRI

Face perception is a complex process that involves highly specialized procedures and mechanisms. Investigating into face perception can help us better understand how the brain processes fine-grained, multidimensional information. This research aimed to delve deeply into how different dimensions of facial information are represented in specific brain regions or through inter-regional connections via an implicit face recognition task. To capture the representation of various facial information in the brain, we employed support vector machine decoding, functional connectivity, and model-based representational similarity analysis on fMRI data, resulting in the identification of three crucial findings. Firstly, despite the implicit nature of the task, emotions were still represented in the brain, contrasting with all other facial information. Secondly, the connection between the medial amygdala and the parahippocampal gyrus was found to be essential for the representation of facial emotion in implicit tasks. Thirdly, in implicit tasks, arousal representation occurred in the parahippocampal gyrus, while valence depended on the connection between the primary visual cortex and the parahippocampal gyrus. In conclusion, these findings dissociate the neural mechanisms of emotional valence and arousal, revealing the precise spatial patterns of multidimensional information processing in faces.

Kindergarten children’s academic engagement: A dual-pathway model including social information processing, social behavior in class, and teacher–child relationship quality

Education researchers and practitioners have been exploring for years the key factors impacting children’s academic engagement. Still, relatively little is known about the role of children’s social cognition in their academic engagement. Accordingly, the current study focuses on the potential indirect associations between young children’s social information processing patterns (SIP) and their academic engagement through their social behaviors in class, specifically their prosocial and problem behaviors, and following by the quality of their relationship with their main kindergarten teacher. The study examines these indirect effects in one dual-pathway model which includes both a pathway from children’s competent SIP patterns to higher levels of academic engagement and from children’s aggressive SIP patterns to lower levels of academic engagement. The sample included 300 kindergarten children (151 girls; Mage = 68.76 months). Results showed that competent SIP patterns were positively linked to children’s academic engagement, which encompasses both their academic self-perceptions and their attitudes toward learning, via children’s prosocial behaviors in class and subsequently teacher–child relational closeness. In addition, aggressive SIP patterns were negatively linked to the kindergarteners’ attitudes toward learning via the children’s problem behaviors in class and subsequently teacher–child relational conflict. Results have implications for both research and practice in the understanding of the influence of social cognition, behavior, and social relationships on academic engagement for young learners.

Inspiration from animal’s collective behavior for home energy demand management

An interdisciplinary approach towards managing energy demand through users’ behavior is discussed, drawing on knowledge from studies on collective behavior in nature. Studies on home energy demand management have focused mainly on social, technical and, more recently, socio-technical aspects that are considered largely at the individual levels only. However, emerging trends in social studies call for explorations across different social and spatial scales beyond the individual levels. This work distinguishes several principles and mechanisms of collective foraging decision-making from nature that respond to demand, including aspects of self-organization and stigmergy. The scoping of potential biological systems and behavioral aspects emulation aims to provide a foundation for agent-based modelling (ABM). Collective behavior emerges from local interactions of the individuals within a group, and nonlinear interactions between individuals and their environment enable them to accomplish tasks, such as structural construction, without the involvement of centralized control systems. Response to demand in nature is significantly influenced by information flow, processing, perception, and communication and coordination patterns between individuals, groups, and their environment. By studying these interactions and adapting their principles to the context of home energy management, we can develop new, more efficient, sustainable, and resilient approaches.

Cross-cultural applicability of eye-tracking in assessing attention to emotional faces in preschool-aged children.

Humans show an attention bias toward emotional versus neutral information, which is considered an adaptive pattern of information processing. Deviations from this pattern have been observed in children with socially withdrawn behaviors, with most research being conducted in controlled settings among children from urban areas. The goal of the current study was to examine the cross-cultural applicability of two eye-tracking-based measures in assessing attention biases and their relations to children's symptoms of socially withdrawn behaviors in two independent and diverse samples of preschool children. The cross-cultural comparison was conducted between the Navajo Birth Cohort study (NBCS), an indigenous cohort with relatively low socioeconomic status (SES), and the Illinois Kids Development study (IKIDS), a primarily Non-Hispanic White and high SES cohort. Children in both cohorts completed eye-tracking tasks with pictures of emotional faces, and mothers reported on children's symptoms of socially withdrawn behaviors. Results showed that general patterns of attention biases were mostly the same across samples, reflecting heightened attention toward emotional versus neutral faces. The differences across two samples mostly involved the magnitude of attention biases. NBCS children were slower to disengage from happy faces when these emotional faces were paired with neutral faces. Additionally, socially withdrawn children in the NBCS sample showed a pattern of attentional avoidance for emotional faces. The comparability of overall patterns of attention biases provides initial support for the cross-cultural applicability of the eye-tracking measures and demonstrates the robustness of these methods across clinical and community settings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Research on the standardization strategy of granular computing

As intelligent systems continue to evolve, problems are becoming increasingly complex. The constant abundance of data puts a higher demand on the value of data utilization. Granular computing is a new computational paradigm for complex problem-solving. It takes structured thinking, structured problem-solving methods, and structured information processing patterns as its research objects and belongs to the scope of higher-level human cognitive mechanism research. The development and application of granular computing must be more standardized and unified. The granular computing standardization strategy is the most direct means to promote the regularization of granular computing. In this paper, we first sort out the main applications of granular computing in standards. According to the characteristics of granular computing, a framework of its standard system is proposed to provide a reference for the subsequent research of granular computing standards. The next direction of the granular computing standards strategy is discussed, and solutions are given.

Rule-based process indicators of information processing explain performance differences in PIAAC web search tasks

BackgroundA priori assumptions about specific behavior in test items can be used to process log data in a rule-based fashion to identify the behavior of interest. In this study, we demonstrate such a top-down approach and created a process indicator to represent what type of information processing (flimsy, breadth-first, satisficing, sampling, laborious) adults exhibit when searching online for information. We examined how often the predefined patterns occurred for a particular task, how consistently they occurred within individuals, and whether they explained task success beyond individual background variables (age, educational attainment, gender) and information processing skills (reading and evaluation skills).MethodsWe analyzed the result and log file data of ten countries that participated in the Programme for the International Assessment of Adult Competencies (PIAAC). The information processing behaviors were derived for two items that simulated a web search environment. Their explanatory value for task success was investigated with generalized linear mixed models.ResultsThe results showed item-specific differences in how frequently specific information processing patterns occurred, with a tendency of individuals not to settle on a single behavior across items. The patterns explained task success beyond reading and evaluation skills, with differences across items as to which patterns were most effective for solving a task correctly. The patterns even partially explained age-related differences.ConclusionsRule-based process indicators have their strengths and weaknesses. Although dependent on the clarity and precision of a predefined rule, they allow for a targeted examination of behaviors of interest and can potentially support educational intervention during a test session. Concerning adults’ digital competencies, our study suggests that the effective use of online information is not inherently based on demographic factors but mediated by central skills of lifelong learning and information processing strategies.

Functional Connectivity Alterations of Within and Between Networks in Schizophrenia: A Retrospective Study

Introduction: Schizophrenia (SZ) is a chronic brain disorder characterized by diverse cognitive dysfunctions due to abnormal brain connectivity. Evaluating these connectivity alterations between and within such networks (intra- and inter-connectivity) may improve the understanding of disrupted information processing patterns in SZ patients. Methods: Resting-state fMRI analysis was performed on 24 SZ patients and 27 matched healthy controls. A functional connectivity matrix was constructed for each participant based on 129 gray matter regions. All regions were classified into eight distinct functional networks. Afterward, all functional connections were segregated into inter- and intra-network connections considering the eight networks. The Mean values of connectivity weights and nodal strength were examined for within- and between-network connections in SZ patients and healthy controls. Results: This analysis revealed that the within-network connections in the somatomotor (SM) network significantly reduced (P<0.001) in SZ patients. Additionally, intra-network connections within the visual and the ventral attention (VA) networks were significantly lower (P<0.01) in the SZ group. Moreover, disrupted intra-network connectivity was detected between the following network pairs: The visual-limbic, the somatomotor-limbic, the dorsal attention-limbic, and the ventral attention-dorsal attention system. Conclusion: The results showed an extensive reduction in functional connectivity strength for SZ patients, with a particularly significant decrease in intra-network connections when compared to the inter-networks. These findings can impact the understanding of the important dysregulated connections that are implicated in the incidence of schizophrenia.

Stakeholder Focus or Strategy Focus? An Eye-Tracker Study on the Effect of Presentation Format on Nonprofessional Investors’ Information Processing Patterns

Using eye-tracking technology, we examine whether the information processing patterns of nonprofessional investors with a directional investment preference are affected by performance information presented based on either a focus on stakeholders (stakeholder format) or on strategic goals (strategic theme format). We find that when a company’s financial performance has declined but nonfinancial performance has improved, a strategic theme (stakeholder) format causes investors in a long investment position to focus on negative financial information to a lesser (greater) extent than those in a short investment position. These results indicate that a strategic theme format encourages biased investors to draw on favorable nonfinancial information to support their position, whereas a stakeholder format causes them to closely scrutinize unfavorable financial information. We also find that the level of bias in investors’ earnings forecasts is lower when information is presented in a strategic theme format than in a stakeholder format; however, a supplementary experiment finds that this result is reversed when a company’s financial performance has improved but its nonfinancial performance has declined. Our results have implications for external report preparers, standard setters, and analysts.

Interoceptive awareness: MBSR training alters information processing of salience network.

Mindfulness refers to a mental state of awareness of internal experience without judgment. Studies have suggested that each mindfulness practice may involve a unique mental state, but the underlying neurophysiological mechanisms remain unknown. Here we examined how distinct mindfulness practices after mindfulness-based intervention alter brain functionality. Specifically, we investigated the functional alterations of the salience network (SN) using functional magnetic resonance imaging (fMRI) among the two interoceptive mindfulness practices-breathing and body scan-associated with interoceptive awareness in fixed attention and shifted attention, respectively. Long-distance functional connectivity (FC) and regional homogeneity (ReHo) approaches were applied to measure distant and local neural information processing across various mental states. We hypothesized that mindful breathing and body scan would yield a unique information processing pattern in terms of long-range and local functional connectivity (FC). A total of 18 meditation-naïve participants were enrolled in an 8-week mindfulness-based stress reduction (MBSR) program alongside a waitlist control group (n = 14), with both groups undergoing multiple fMRI sessions during breathing, body scan and resting state for comparison. We demonstrated that two mindfulness practices affect both the long-distance FC SN and the local ReHo, only apparent after the MBSR program. Three functional distinctions between the mindfulness practices and the resting state are noted: (1) distant SN connectivity to occipital regions increased during the breathing practice (fixed attention), whereas the SN increased connection with the frontal/central gyri during the body scan (shifting attention); (2) local ReHo increased only in the parietal lobe during the body scan (shifting attention); (3) distant and local connections turned into a positive correlation only during the mindfulness practices after the MBSR training, indicating a global enhancement of the SN information processing during mindfulness practices. Though with limited sample size, the functional specificity of mindfulness practices offers a potential research direction on neuroimaging of mindfulness, awaiting further studies for verification.

Prospects for the use of artificial intelligence methods in autism spectrum disorders

IntroductionASD is a heterogeneous group of pathological conditions.ObjectivesSensory Functions in Children with AutismMethodsA brief review of scientific publications is presented, formed by the search result for the keywords: autism spectrum disorders, artificial intelligence, machine learning.ResultsPatients with ASD respond to sensory information hyper-reactively and hypo-reactively. Patients, regardless of age and severity of ASD, have atypical information processing patterns in all sensory modalities. Atypical processing of stimuli correlates with social, cognitive and communication disorders.ConclusionsTo normalize sensory deviations, it is necessary to build corrective and prognostic models of the child’s connection with the environment. Machine learning models, Data Mining methods to make medical management decisions and develop personalized therapeutic strategies.Disclosure of InterestNone Declared

Stakeholder Focus or Strategy Focus? An Eye-Tracker Study on the Effect of Presentation Format on Nonprofessional Investors’ Information Processing Patterns

Stakeholder Focus or Strategy Focus? An Eye-Tracker Study on the Effect of Presentation Format on Nonprofessional Investors’ Information Processing Patterns

A study of parental decision-making over the vaccination of girls, based on the protection motivation theory and the elaboration likelihood model.

This study proposed a new theoretical framework that combines the protection motivation theory and the elaboration likelihood model to examine how health information processing patterns influence parents' vaccination decision-making on behalf of their daughters. Based on survey data from 359 parents of girls aged 9-15, we tested the theoretical model by using structural equation model. The results showed that the central route, represented by information quality, affected the parents' perceptions of HPV severity and susceptibility; the peripheral route, represented by source credibility, influenced their perceptions of HPV severity, HPV susceptibility, vaccine response efficacy, and secondary risks. Also, Chinese parents' perceptions of HPV vaccines, not perceptions of HPV, affected their intention to vaccinate their daughters. The study suggests in addition to improving the quality of health information, the peripheral route, such as the release of vaccination photos, public immunization evaluations, and case narratives, should also be used to change parents' perceptions. Besides, reducing the traditional stigmatization of female sexuality and improving parents' understanding of the new generation's sexual attitudes will increase parents' intention to have their daughters vaccinated against HPV.

Task-dependent fractal patterns of information processing in working memory

We applied detrended fluctuation analysis, power spectral density, and eigenanalysis of detrended cross-correlations to investigate fMRI data representing a diurnal variation of working memory in four visual tasks: two verbal and two nonverbal. We show that the degree of fractal scaling is regionally dependent on the engagement in cognitive tasks. A particularly apparent difference was found between memorisation in verbal and nonverbal tasks. Furthermore, the detrended cross-correlations between brain areas were predominantly indicative of differences between resting state and other tasks, between memorisation and retrieval, and between verbal and nonverbal tasks. The fractal and spectral analyses presented in our study are consistent with previous research related to visuospatial and verbal information processing, working memory (encoding and retrieval), and executive functions, but they were found to be more sensitive than Pearson correlations and showed the potential to obtain other subtler results. We conclude that regionally dependent cognitive task engagement can be distinguished based on the fractal characteristics of BOLD signals and their detrended cross-correlation structure.

Information transmission in action video gaming experts: Inferences from the lateralized readiness potential.

Research showed that action real-time strategy gaming (ARSG) experience is related to cognitive and neural plasticity, including visual selective attention and working memory, executive control, and information processing. This study explored the relationship between ARSG experience and information transmission in the auditory channel. Using an auditory, two-choice, go/no-go task and lateralized readiness potential (LRP) as the index to partial information transmission, this study examined information transmission patterns in ARSG experts and amateurs. Results showed that experts had a higher accuracy rate than amateurs. More importantly, experts had a smaller stimulus-locked LRP component (250 – 450 ms) than amateurs on no-go trials, while the response-locked LRP component (0 – 300 ms) on go trials did not differ between groups. Thus, whereas amateurs used an asynchronous information transmission pattern, experts used a reduced asynchronous information transmission pattern or a synchronous pattern where most of processing occurred prior to response execution – an information transmission pattern that supports rapid, error-free performance. Thus, experts and amateurs may use different information transmission patterns in auditory processing. In addition, the information transmission pattern used by experts is typically observed only after long-term auditory training according to past research. This study supports the relationship between ARSG experience and the development of information processing patterns.