scholarly journals Individual differences in response precision correlate with adaptation bias

2018 ◽  
Author(s):  
Marcelo G. Mattar ◽  
Marie V. Carter ◽  
Marc S. Zebrowitz ◽  
Sharon L. Thompson-Schill ◽  
Geoffrey K. Aguirre
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Negative Correlation ◽  
Internal Representation ◽  
Perceptual Representation ◽  
Stimulus Match ◽  
On Line ◽  
Observer Model ◽  
Measure Reliability ◽  
Von Mises

The internal representation of stimuli is imperfect and subject to bias. Noise introduced at initial encoding and during maintenance degrades the precision of representation. Stimulus estimation is also biased away from recently encountered stimuli, a phenomenon known as adaptation. Within a Bayesian framework, greater biases are predicted to result from poor precision. We tested for this effect in individual difference measures. 202 subjects contributed data through an on-line experiment (https://cfn.upenn.edu/iadapt). During separate face and color blocks, subjects performed three different tasks: an immediate stimulus-match (15 trials), a 5 seconds delayed match (30 trials), and 5 seconds of adaptation followed by a delayed match (30 trials). The stimulus spaces were circular and subjects entered their responses using a color/face wheel. Bias and precision of responses were extracted by fitting a mixture of von Mises distributions to account for random guesses. Two blocks of each measure were obtained, allowing for tests of measure reliability. We found that reliable differences between individuals in precision were as great as those between tasks or materials. The adaptation manipulation induced the expected bias in responses (colors: 7.8°; faces: 5.0°), and the magnitude of this bias reliably and substantially varied between subjects. Across subjects, there was a negative correlation between mean precision and bias (color: ρ = −0.26; faces: ρ = −0.13). This relationship was replicated in a new experiment with 192 subjects (color: ρ = −0.22; faces: ρ = −0.19). This result is consistent with a Bayesian observer model, in which individual differences in the precision of perceptual representation influences the magnitude of adaptation bias.

Self-Reported Sense of Smell Predicts Disgust Sensitivity and Disgust Reactivity

2018 ◽  
Vol 39 (4) ◽  
pp. 191-195
Author(s):  
Nicholas J. Kelley ◽  
Adrienne L. Crowell
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Olfactory Stimulus ◽  
Disgust Sensitivity ◽  
Sense Of Smell ◽  
Olfactory Ability ◽  
Good Proxy ◽  
Insight Into

Abstract. Two studies tested the hypothesis that self-reported sense of smell (i.e., metacognitive insight into one’s olfactory ability) predicts disgust sensitivity and disgust reactivity. Consistent with our predictions two studies demonstrated that disgust correlates with self-reported sense of smell. Studies 1 and 2 demonstrated, from an individual difference perspective, that trait-like differences in disgust relate to self-reported sense of smell. Physical forms of disgust (i.e., sexual and pathogen disgust) drove this association. However, the association between self-reported sense of smell and disgust sensitivity is small, suggesting that it is likely not a good proxy for disgust sensitivity. The results of Study 2 extended this finding by demonstrating that individual differences in self-reported sense of smell influence how individuals react to a disgusting olfactory stimulus. Those who reported having a better sense of smell (or better insight into their olfactory ability) found a disgusting smell significantly more noxious as compared to participants reporting having a poor sense of smell (or poor insight into their olfactory ability). The current findings suggest that a one-item measure of self-reported sense of smell may be an effective tool in disgust research.

Cognitive Reflection Effects on Time Discounting

2018 ◽  
Vol 39 (2) ◽  
pp. 99-106 ◽  
Author(s):  
Michał Białek ◽  
Przemysław Sawicki
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Delay Discounting ◽  
Reference Point ◽  
Reference Points ◽  
Cognitive Reflection Test ◽  
Process Information ◽  
Time Discounting ◽  
Cognitive Reflection ◽  
The Way

Abstract. In this work, we investigated individual differences in cognitive reflection effects on delay discounting – a preference for smaller sooner over larger later payoff. People are claimed to prefer more these alternatives they considered first – so-called reference point – over the alternatives they considered later. Cognitive reflection affects the way individuals process information, with less reflective individuals relying predominantly on the first information they consider, thus, being more susceptible to reference points as compared to more reflective individuals. In Experiment 1, we confirmed that individuals who scored high on the Cognitive Reflection Test discount less strongly than less reflective individuals, but we also show that such individuals are less susceptible to imposed reference points. Experiment 2 replicated these findings additionally providing evidence that cognitive reflection predicts discounting strength and (in)dependency to reference points over and above individual difference in numeracy.

Neuroimaging of Individual Differences: A Latent Variable Modeling Perspective

2018 ◽  
Author(s):  
Shelly Renee Cooper ◽  
Joshua James Jackson ◽  
Deanna Barch ◽  
Todd Samuel Braver
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Latent Variable ◽  
Structural Equation ◽  
Behavioral Measure ◽  
Equation Modeling ◽  
Latent Variable Modeling ◽  
Psychometric Theory ◽  
Human Connectome Project ◽  
Neuroimaging Data

Neuroimaging data is being increasingly utilized to address questions of individual difference. When examined with task-related fMRI (t-fMRI), individual differences are typically investigated via correlations between the BOLD activation signal at every voxel and a particular behavioral measure. This can be problematic because: 1) correlational designs require evaluation of t-fMRI psychometric properties, yet these are not well understood; and 2) bivariate correlations are severely limited in modeling the complexities of brain-behavior relationships. Analytic tools from psychometric theory such as latent variable modeling (e.g., structural equation modeling) can help simultaneously address both concerns. This review explores the advantages gained from integrating psychometric theory and methods with cognitive neuroscience for the assessment and interpretation of individual differences. The first section provides background on classic and modern psychometric theories and analytics. The second section details current approaches to t-fMRI individual difference analyses and their psychometric limitations. The last section uses data from the Human Connectome Project to provide illustrative examples of how t-fMRI individual differences research can benefit by utilizing latent variable models.

It Takes Two to Make an Interview Go Right: Round-Robin Designs to Demonstrate Interviewer and Witness Variance

2018 ◽  
Author(s):  
Charlotte A. Hudson ◽  
Liam Satchell ◽  
Nicole M Adams-Quackenbush
Keyword(s):  
Grain Size ◽  
Individual Differences ◽  
Individual Difference ◽  
Round Robin ◽  
Investigative Interviews ◽  
Sources Of Variation ◽  
Interview Performance ◽  
Report Accuracy ◽  
Statistical Demonstration

Purpose: Investigative interviews are complex, dyadic, activities typically studied by focusing on developing techniques to improve witness performance. However, in field settings, interviewers are known to vary in their presentation of good interviewing practice. Thus, it is important to conduct research reflective of complex idiosyncrasies in witnesses, interviewers and unique pairings of both. This study explores such sources of variation in an by making use of a 'round-robin' design. Such methodology allows the statistical demonstration of individual difference and unique partner-generated variance in interview performance. Methods: In our study, a total of 45 witnesses were questioned about five real crime videos. After witnessing each event, witnesses were interviewed by a different interviewer (or a computer self-administered interview). In total, nine 'rounds' of interviews occurred, with five new witnesses being interviewed in the same five interview settings (resulting in 225 interviews). After each interview both interviewers and witnesses were asked to complete subjective interview experience ratings. The quality (grain size) and quantity of information in the statements was coded to index witness report accuracy. Results: Principally, the results demonstrate the degree to which witnesses and interviewers affect statement quality, and highlight the influence of unique interviewer-witness pairs. (Participant personality and interviewer behaviour were also analysed, but with limited effects). Conclusion: This study presents the useful round-robin methodology for studying interviewer-witness behaviour. Whilst the current personality and behavioural measures do not account for these individual differences, we advocate this methodology be adopted more widely to better understand interview performance.

scholarly journals Older Adults’ Adherence to Technology-Based Intervention: The Role of Messaging and Individual Differences

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 555-555
Author(s):  
Walter Boot ◽  
Nelson Roque ◽  
Erin Harrell ◽  
Neil Charness
Keyword(s):  
Older Adults ◽  
Individual Differences ◽  
Health Behaviors ◽  
Individual Difference ◽  
Cognitive Training ◽  
Self Efficacy ◽  
Message Framing ◽  
Training Intervention ◽  
Home Technology

Abstract Adherence to health behaviors is often poor, including adherence to at-home technology-based interventions. This study (N=120) explored adherence to a cognitive training intervention delivered via computer tablet, assessed adherence over a 4.5 month period, explored how individual difference factors shaped adherence, and tested the efficacy of message framing manipulations (positive vs. negative framing) in boosting adherence. Individual difference factors predicted adherence, including variations in self-efficacy and belief in the efficacy of cognitive training. Overall message framing had little impact. However, during the final portion of the study in which participants were asked to play as much or as little as they wanted instead of following a schedule, participants who received positively framed messages engaged with the intervention more. Implications for predicting and boosting adherence to home delivered technology-based interventions will be discussed.

scholarly journals Relationship between Nutrient Intake and Human Gut Microbiota in Monozygotic Twins

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 275
Author(s):  
Natsuko Matsumoto ◽  
Jonguk Park ◽  
Rie Tomizawa ◽  
Hitoshi Kawashima ◽  
Koji Hosomi ◽  
...  
Keyword(s):  
Individual Differences ◽  
Environmental Factors ◽  
Gut Microbiota ◽  
Human Health ◽  
Negative Correlation ◽  
Nutrient Intake ◽  
Monozygotic Twins ◽  
Human Gut ◽  
Positive Correlation ◽  
Human Gut Microbiota

Background and Objectives: The gut microbiota is associated with human health and dietary nutrition. Various studies have been reported in this regard, but it is difficult to clearly analyze human gut microbiota as individual differences are significant. The causes of these individual differences in intestinal microflora are genetic and/or environmental. In this study, we focused on differences between identical twins in Japan to clarify the effects of nutrients consumed on the entire gut microbiome, while excluding genetic differences. Materials and Methods: We selected healthy Japanese monozygotic twins for the study and confirmed their zygosity by matching 15 short tandem repeat loci. Their fecal samples were subjected to 16S rRNA sequencing and bioinformatics analyses to identify and compare the fluctuations in intestinal bacteria. Results: We identified 12 genera sensitive to environmental factors, and found that Lactobacillus was relatively unaffected by environmental factors. Moreover, we identified protein, fat, and some nutrient intake that can affect 12 genera, which have been identified to be more sensitive to environmental factors. Among the 12 genera, Bacteroides had a positive correlation with retinol equivalent intake (rs = 0.38), Lachnospira had a significantly negative correlation with protein, sodium, iron, vitamin D, vitamin B6, and vitamin B12 intake (rs = −0.38, −0.41, −0.39, −0.63, −0.42, −0.49, respectively), Lachnospiraceae ND3007 group had a positive correlation with fat intake (rs = 0.39), and Lachnospiraceae UCG-008 group had a negative correlation with the saturated fatty acid intake (rs = −0.45). Conclusions: Our study is the first to focus on the relationship between human gut microbiota and nutrient intake using samples from Japanese twins to exclude the effects of genetic factors. These findings will broaden our understanding of the more intuitive relationship between nutrient intake and the gut microbiota and can be a useful basis for finding useful biomarkers that contribute to human health.

scholarly journals Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

2020 ◽  
Vol 117 (32) ◽  
pp. 19061-19071 ◽  
Author(s):  
Samantha Joel ◽  
Paul W. Eastwick ◽  
Colleen J. Allison ◽  
Ximena B. Arriaga ◽  
Zachary G. Baker ◽  
...  
Keyword(s):  
Machine Learning ◽  
Individual Differences ◽  
Relationship Quality ◽  
Individual Difference ◽  
Large Scale ◽  
Well Being ◽  
Attachment Anxiety ◽  
Self Report ◽  
Individual Difference Variables ◽  
Partner Satisfaction

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.

scholarly journals A Study of Educational Achievement of Standard XI Students in Context of their Learning Style in Reference to Area

2017 ◽  
Vol 4 (3) ◽  
Author(s):  
Ajay B. Raval
Keyword(s):  
Individual Differences ◽  
Data Collection ◽  
Learning Style ◽  
Individual Difference ◽  
Educational Achievement ◽  
Visual Learning ◽  
Learning Style Inventory ◽  
Kinesthetic Learning ◽  
The Individual ◽  
Selection Of

In the Era of Change, teacher should consider the individual differences while teaching in the classroom. In fact teacher must keep in mind the individual differences for teaching. Students have so many talent, we as a teacher must have that angel of view of identifying it. This individual difference can be divided in dimension of Learning Style, too. Researcher was giving service in High School as a teacher, he observe such an Individual difference in context to learning style in class room. Is there any relationship between Educational Achievement and Learning Style? Is there any effect of Learning Style on Educational Achievement in reference to Area? To find the answer of this question present study was conducted. Population & Sample: Population for present study was students studying in Standard-XI of Gujarati Medium School of Gandhinagar District. The selection of schools was by Stratified Randomization Technique and selection of students was selected by Cluster Method. In last, the Sample size was 607. Method: Survey Method was used for Data Collection. Tool: Self constructed Learning Style Inventory (L.S.I.) was used for Data Collection. Learning Style Inventory (L.S.I.) was three Point Likert type Scale. Findings: 1) There was no significance different in educational achievement among students having Visual Learning Style, Auditorial Learning Style and Kinesthetic Learning Style. 2) In matter of educational achievement, students of Rural are superior to students of Urban among students having Visual Learning Style. 3) In matter of educational achievement, students of Rural are superior to students of Urban among students having Auditorial Learning Style. 4) In matter of educational achievement, students of Urban are superior to students of Rural among students having Kinesthetic Learning Style.

Conclusion: I Wouldn’t Know Him from Adam

2019 ◽  
pp. 181-192
Author(s):  
Andrew LaZella
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
De Re ◽  
Affective Attitudes ◽  
Per Se ◽  
The Senses ◽  
Aristotelian Tradition

The conclusion engages problems facing our cognition of ultimate differences, in particular ultimate individual difference. Against the more orthodox Aristotelian tradition, which held that the intellect grasps universals, the senses sense individuals, Scotus argues that there is nothing per seunintelligible about singulars. Rather, as the culmination of being, singularity marks the culmination of intelligibility. With respect to the wayfarer, however, neither the intellect nor the senses grasp singulars. The conclusion shows why Scotus holds that ultimate individual differences resist direct cognition. Despite our incapacity for de reintellectual states, some scattered claims Scotus makes regarding the possibility for de revolitional states are explored. That is, Scotus thinks that we need to form beliefs about and establish affective attitudes toward individuals, and not merely something similar to them. This discussion leads us back to Solomon’s difficulty. This difficulty should be understood not so much as a burden inflicted upon us in the wayfarer state due to our embodiment or sinful fallenness, but rather as an example of a more general Franciscan celebration of creatures in their singularity.

Meaningful Individual Differences in Statistics Cognition

2017 ◽  
pp. 188-234
Keyword(s):  
Individual Differences ◽  
Cognitive Development ◽  
Goal Orientation ◽  
Individual Difference ◽  
Online Courses ◽  
Self Determination Theory ◽  
Self Determination ◽  
Scholarly Research ◽  
Motivational Profiles ◽  
The Continuum

This chapter focuses on the understanding and use of individual differences in statistics cognition. We argue that individual differences can be classified along a continuum ranging from within an individual (internally derived) to an outside source (externally prescribed), and that where an individual differences falls on the continuum may have important implications for how individual differences are used to describe, control for, predict, or explain findings in scholarly research. We argue that individual differences are more useful when they meaningfully pertain to cognitive development, and outline how motivation (using goal orientation and self-determination theory) can be used as an individual difference. We conclude with a discussion of aligning motivational goals and how online courses could adapt themselves to student motivational profiles.

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