Variability within and across individuals during auditory category learning

The ability to organize variable acoustic signals into discrete categories is a fundamental process supporting speech perception. Adult learners can acquire complex, multidimensional auditory categories via feedback. There is substantial variability across individuals in how quickly and how well they learn auditory categories; however, it is unclear how the same individual approaches different category learning problems. We trained the same participants on three types of multidimensional auditory categories with different distributional structure (rule-based, information-integration) and from different auditory domains (nonspeech, speech). Consistent with prior work, there was substantial variability in both how well individuals learned the different categories and the strategies they used. As a novel contribution, we found that within an individual, learning outcomes were related across all three tasks and success across tasks was related to working memory capacity. Across tasks, we found that the same individual tailored their strategies for the specific task at hand, rather than systematically applying the same kind of strategy across different tasks. It was also uncommon for participants to shift toward an optimal strategy across different tasks and, instead, most participants used a mix of optimal and suboptimal strategies. These results indicate that auditory category learning may be supported by a category-general learning ability and highlight the importance of considering variability within an individual as they learn categories with different requirements.

HERMES: a molecular formula-oriented method to target the metabolome

ABSTRACTComprehensive metabolome analyses are hampered by low identification rates of metabolites due to suboptimal strategies in MS and MS2 acquisition, and data analysis. Here we present a molecular formula-oriented and peak detection-free method, HERMES, that improves sensitivity and selectivity for metabolite profiling in MS and structural annotation in MS2. An analysis of environmental water, E. coli, and human plasma extracts by HERMES showed increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared to iterative data-dependent acquisition (DDA). HERMES is available as an R package with a user-friendly graphical interface to allow data analysis and interactive tracking of compound annotations.

Developing an Individual Profile of Attentional Control Strategy

What makes one person better at controlling attention than the next person? Attempts to answer this question have largely focused on measuring individuals’ cognitive abilities. However, variation in attentional performance can also be due to differences in strategy. Here, we describe research showing that individuals vary dramatically in how they choose to control attention, with many reliably choosing suboptimal strategies. Optimal strategy choice appears to be unrelated to attentional control ability, general cognitive ability, or even strategy choice on other attention tasks. It does, however, correlate with how effortful individuals find the optimal strategy, which suggests that strategy choice may be driven by subjective, task-specific effort demands. These findings represent initial steps toward fully characterizing an individual profile of attentional control strategies.

Characterizing Individual Differences in a Dynamic Stabilization Task Using Machine Learning

INTRODUCTION: Being able to identify individual differences in skilled motor learning during disorienting conditions is important for spaceflight, military aviation, and rehabilitation.METHODS: Blindfolded subjects (N = 34) were strapped into a device that behaved like an inverted pendulum in the horizontal roll plane and were instructed to use a joystick to stabilize themselves across two experimental sessions on consecutive days. Subjects could not use gravitational cues to determine their angular position and many soon became spatially disoriented.RESULTS: Most demonstrated minimal learning, poor performance, and a characteristic pattern of positional drifting during horizontal roll plane balancing. To understand the wide range of individual differences observed, we used a Bayesian Gaussian Mixture method to cluster subjects into three statistically distinct groups that represent Proficient, Somewhat Proficient, and Not Proficient performance. We found that subjects in the Not Proficient group exhibited a suboptimal strategy of using very stereotyped large magnitude joystick deflections. We also used a Gaussian Naive Bayes method to create predictive classifiers. As early as the second block of experimentation (out of ten), we could predict a subject’s final group with 80% accuracy.DISCUSSION: Our findings indicate that machine learning can help predict individual performance and learning in a disorienting dynamic stabilization task and identify suboptimal strategies in Not Proficient subjects, which could lead to personalized and more effective training programs.Vimal VP, Zheng H, Hong P, Fakharzadeh LN, Lackner JR, DiZio P. Characterizing individual differences in a dynamic stabilization task using machine learning. Aerosp Med Hum Perform. 2020; 91(6):479–488.

Which Emotion Regulation Strategies are Most Associated with Trait Emotion Dysregulation? A Transdiagnostic Examination

Although definitions of emotion dysregulation infer difficulties in selecting and implementing emotion regulation (ER) strategies, surprisingly few studies have examined the relationship between trait emotion dysregulation and a wide range of specific ER strategies. The present study used a data-driven approach to assess trait- and state-related ER strategy use in 99 women (aged 18-55) recruited from the community with varying levels of trait emotion dysregulation. Participants completed self-report questionnaires assessing habitual ER strategy implementation and self-ratings of ER strategy use in vivo during negative mood inductions. Principal components analysis revealed four self-report questionnaire-based and three mood-induction-based groupings comprising both optimal and suboptimal strategies. After adjusting for demographic and clinical variables, results from self-report questionnaires indicated that trait emotion dysregulation was significantly associated with higher endorsements of suboptimal strategies in two groupings (e.g., self-criticism, rumination, and social withdrawal; catastrophizing and blaming others) and lower endorsements of optimal ER strategies in one grouping (e.g., cognitive reappraisal and problem solving). In the context of mood induction, trait emotion dysregulation was significantly associated with higher endorsements of suboptimal ER strategies from one cluster only (e.g., expressive suppression, thought avoidance, and self-criticism). Such transdiagnostic, data-driven approaches can uncover how the application of specific ER strategies both habitually and during negative mood states is associated with trait emotion dysregulation.

Developing an individual profile of attentional control strategy

What makes one person better at controlling attention than the next? Attempts to answer this question have largely focused on measuring individuals’ cognitive abilities. However, variation in attentional performance can also be due to differences in strategy. Here we describe research showing that individuals vary dramatically in how they choose to control attention, with many reliably choosing suboptimal strategies. Optimal strategy choice appears to be unrelated to attentional control ability, general cognitive ability, or even strategy choice on other attention tasks. It does, however, correlate with how effortful individuals find the optimal strategy, suggesting strategy choice may be driven by subjective, task-specific effort demands. These findings represent initial steps toward fully characterizing an individual profile of attentional control strategies.

Learning and choosing in an uncertain world: An investigation of the explore-exploit dilemma in static and dynamic environments

How do people solve the explore–exploit trade-off in a changing environment? In this paper we present experimental evidence from an “observe or bet” task, in which people have to determine when to engage in information-seeking behavior and when to switch to reward-taking actions. In particular we focus on the comparison between people’s behavior in a changing environment and their behavior in an unchanging one. Our experimental work is motivated by rational analysis of the problem that makes strong predictions about information search and reward seeking in static and changeable environments. Our results show a striking agreement between human behavior and the optimal policy, but also highlight a number of systematic differences. In particular, we find that while people often employ suboptimal strategies the first time they encounter the learning problem, most people are able to approximate the correct strategy after minimal experience. In order to describe both the manner in which people’s choices are similar to but slightly different from an optimal standard, we introduce four process models for the observe or bet task and evaluate them as potential theories of human behavior.

I Take Care of My Own: A Field Study on How Leadership Handles Conflict between Individual and Collective Incentives

In most collective actions, individuals' incentives are not perfectly aligned with the goals of the group/team they are part of. We investigate how individual specific incentives affect both individuals and team leaders' strategies in a natural setting. We use a discontinuity in individual rewards in batsmen scoring in cricket to identify the causal effect of such incentives on behavior. We find that batsmen react to the presence of individual-specific incentives by adopting strategies that may be suboptimal at the team level. More surprisingly, we also find that team captains react to these individual incentives by adopting suboptimal strategies at the team level, which may bring large benefits to the individual players. These results suggest a complex interplay of individual and team incentives which we conjecture may arise in repeated team interactions.

Consultations between Immigrant Patients, Their Interpreters, and Their General Practitioners: Are They Real Meetings or Just Encounters? A Qualitative Study in Primary Health Care

Objective. In Sweden, about 19% of residents have a foreign background. Previous studies reported immigrant patients experience communication difficulties despite the presence of interpreters during consultations. The objective of this study was to gain insights into the participants’ perceptions and reflections of the triangular meeting by means of in-depth interviews with immigrant patients, interpreters, and general practitioners (GPs). Method. A total of 29 participants—10 patients, 9 interpreters, and 10 GPs—participated in face-to-face interviews. Content analysis was used to process the interview material. Results. Six themes were generated and arranged under two subject areas: the interpretation process (the means of interpreting and means of informing) and the meeting itself (individual tailored approaches, consultation time, the patient’s feelings, and the role of family members). Conclusion. This paper highlights feelings including frustration and insecurity when interpretation and relationships are suboptimal. Strategies for immigrant patients, interpreters, and GPs for getting a successful consultation may be needed. To transform the triangular meeting from an encounter to a real meeting, our results indicate a need for professional interpreters, for GPs to use a patient-tailored approach, and sufficient consultation time. Practice Implications. Use of professional interpreters is recommended, as is developing cultural competence.