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Remote work presents a challenge to workers’ creativity, especially during the COVID-19 pandemic and the stay-at-home requirements. Individual differences in creativity, considered through the lens of distributional models, and their stability across different conditions are unknown. We assess the between-person variability in common metrics of creativity, despite sharing similar experiences of virtual reality and mindfulness. The paper also assesses the stability of an individual’s creativity over time. We measured the creativity of 20 remote-workers daily, during a 9-week study. Creativity was measured with respect to divergent thinking and convergent thinking. Distributional models show significant individual differences in variability of creativity. Stability analyses also revealed that individuals’ creativity is relatively unstable over time— both within and across conditions. Although one measure of divergent creativity was relatively stable, the other was not. We suggest more research should assess the extent of variability in creativity relative to individual differences and under different conditions.

Computer-mediated social learning contexts have become increasingly popular over the last few years; yet existing models of students' cognitive-affective states have been slower to adopt dyadic interaction data for predictions. Here, we explore the possibility of capitalizing on the inherently social component of collaborative learning by using keystroke log data to make predictions across conversational partners (i.e., using person A's data to make prediction about if person B is mind wandering). Log files from 33 dyads (total N = 66) were used to examine: a) how mind wandering (defined here as task-unrelated thought) during computer-mediated conversations is related to critical outcomes of the conversation (trust, likability, agreement); b) if task-unrelated thought can be predicted by the keystrokes of one's partner; and c) how much data is needed to make predictions by testing var- ious window-sizes of data preceding task-unrelated thought reports. Results indicated a negative relationship between task-unrelated thought and perceptions of the conversation, suggesting that attention is an important factor during computer mediated chat conversations. Finally, in line with our hypothesis, one's level of task-unrelated thought was predicted by the keystroke patterns of their conversational partner, but only using small window sizes (5s worth of data).

Task-unrelated thought (TUT), commonly referred to as mind wandering, is a mental state where a person's attention moves away from the task-at-hand. This state is extremely common, yet not much is known about how to measure it, especially during dyadic interactions. We thus built a model to detect when a person experiences TUTs while talking to another person through a computer-mediated conversation, using their keystroke patterns. The best model was able to differentiate between task-unrelated thoughts and task-related thoughts with a kappa of 0.363, using features extracted from a 15 second window. We also present a feature analysis to provide additional insights into how various typing behaviors can be linked to our ongoing mental states.

The vast majority of disease-associated variants identified in genome-wide association studies map to enhancers, powerful regulatory elements which orchestrate the recruitment of transcriptional complexes to their target genes’ promoters to upregulate transcription in a cell type- and timing-dependent manner. These variants have implicated thousands of enhancers in many common genetic diseases, including nearly all cancers. However, the etiology of most of these diseases remains unknown because the regulatory target genes of the vast majority of enhancers are unknown. Thus, identifying the target genes of as many enhancers as possible is crucial for learning how enhancer regulatory activities function and contribute to disease. Based on experimental results curated from scientific publications coupled with machine learning methods, we developed a cell type-specific score predictive of an enhancer targeting a gene. We computed the score genome-wide for every possible cis enhancer-gene pair and validated its predictive ability in four widely used cell lines. Using a pooled final model trained across multiple cell types, all possible gene-enhancer regulatory links in cis (~17 M) were scored and added to the publicly available PEREGRINE database (www.peregrineproj.org). These scores provide a quantitative framework for the enhancer-gene regulatory prediction that can be incorporated into downstream statistical analyses.

Involuntary thinking occurs when mental states arise without intention. Such thoughts can take different forms, such as involuntary autobiographical memories (IAM), ruminative thoughts, and unexpected thoughts—all of which are popular areas of study, albeit in somewhat disparate literatures. Despite these mental states sharing a common thread of feeling involuntary in nature, it is nevertheless unclear what separates them phenomenologically. We conducted a set of exploratory and confirmatory experiments to elucidate the appraisal dimensions behind these forms of involuntary thought, with a particular interest in understanding the phenomenology behind unexpected thoughts that are predicted to violate expectations of both timing and content. Across two experiments, we found that unexpected thoughts had unique appraisal structures compared to the other two forms of involuntary thought: they were less identifiably cued, more surprising in content and timing, and offered new information (i.e., insight). We discuss how these distinctions support recent theories regarding the nature of unexpected thought and its relation to other forms of involuntary thinking, namely IAM and ruminative thought, which are the more commonly studied forms of involuntary thinking.

The flow of thought is persistent, and at times merciless. Mental content is generated throughout the day and into the night, moving forward predictably at times but surprisingly at others. Understanding what influences the trajectory of thought – how thoughts continuously unfold over time – has important implications for the diagnosis and treatment of spontaneous thought disorders like schizophrenia and recurrent nightmares. Here, we examine whether cognitive control (i.e., deliberate constraints) restrict moment-to-moment topical content shifts across sleep and wakefulness, thus acting as a fundamental constraint on thought variability. Thought variability was measured as the semantic distance between sequential thought phrases and was applied to reports from a variety of dreaming and waking experiences. Our results show that within both waking thought and dreams, conditions typically marked by higher levels of cognitive control are associated with decreased thought variability. During wakefulness, on-task conditions were associated with reduced levels of semantic thought variability compared to off-task conditions and semantic thought variability was greater when thoughts wandered around more freely. During sleep, lucid dreams marked by higher levels of metacognition were associated with reduced levels of semantic thought variability compared to non-lucid dreams. These results suggest that cognitive control may limit thought variability across the 24-hour cycle of thought generation. Such results are notably consistent with the Dynamic Framework of Thought, where mental states are expected to vary on continuum of deliberate constraints, with lower cognitive control leading to a categorical cluster of spontaneous thought processes that includes both mind-wandering during wakefulness and non-lucid dreams during sleep.

The true accuracy of a machine learning model is a population-level statistic that cannot be observed directly. In practice, predictor performance is estimated against one or more test datasets, and the accuracy of this estimate strongly depends on how well the test sets represent all possible unseen datasets. Here we present paired evaluation, a simple approach for increasing the robustness of performance evaluation by systematic pairing of test samples, and use it to evaluate predictors of drug response in breast cancer cell lines and of disease severity in patients with Alzheimer’s Disease. Our results demonstrate that the choice of test data can cause estimates of performance to vary by as much as 30%, and that paired evaluation makes it possible to identify outliers, improve the accuracy of performance estimates in the presence of known confounders, and assign statistical significance when comparing machine learning models.

Self-regulated learning (SRL) is a critical component of mathematics problem solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model, proposes that five cognitive operations (i.e., searching, monitoring, assembling, rehearsing, and translating) play a key role in SRL. However, these categories encompass a wide range of behaviors, making measurement challenging – often involving observing individual students and recording their think-aloud activities or asking students to complete labor-intensive tagging activities as they work. In the current study, we develop machine-learned indicators of SMART operations, in order to achieve better scalability than other measurement approaches. We analyzed student's textual responses and interaction data collected from a mathematical learning platform where students are asked to thoroughly ex-plain their solutions and are scaffolded in communicating their problem-solving process to their peers and teachers. We built detectors of four indicators of SMART operations (namely, assembling and translating operations). Our detectors are found to be reliable and generalizable, with AUC ROCs ranging from .76-.89. When applied to the full test set, the detectors are robust against algorithmic bias, performing well across different student populations.

High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g. CellTiter-Glo®). Here we describe a public domain “Dye Drop” method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.

Creative thinking is often viewed as a dynamic process that involves shifts between two distinct modes (or phases) of thought – a generative and an evaluative mode. The generative mode involves the generation of new ideas, whereas the evaluative mode involves cognitive and affective evaluations of these ideas. Although the neurocognitive underpinnings of these two thought modes have received significant attention, the dynamics of transitions between them have remain largely unexplored. Here, we focus on these dynamics and review current evidence from psychology and cognitive neuroscience about the relationships and transitions between the two purported modes of thought. We suggest that two types of evaluative processing—automatic-affective and deliberate (i.e., based in cognitive control)—play pivotal roles in supporting transitions between the generative and evaluative modes. Ultimately, we contend that future research into creative thought should focus on clarifying the timescales at which the two modes of thought may unfold, how the transition rate between them may relate to creative outcomes, and the nature of automatic-affective evaluations made towards thoughts.

Organ donation after medical assistance in dying (MAID) has only been possible for patients having the MAID procedure performed at a hospital facility due to prohibitive warm ischemic times. Herein, we describe a protocol for lung donation following MAID at home and demonstrate excellent postoperative outcomes. Lung donation following MAID at home is possible and should be considered by transplant programs.

The introduction of direct oral anticoagulants (DOACs) to the market has expanded anticoagulation options for outpatient use. Routine evaluation by health care professionals is recommended as it is with warfarin, therefore requiring adjustments in practices of anticoagulation management services (AMS). This study aims to describe trends that occurred following the incorporation of DOACs into AMS at a large academic medical center. A retrospective chart review of pharmacist-run AMS was used to compare patients on DOAC therapy versus other types of anticoagulation, including warfarin and parenteral agents. Primary outcomes included trends in the number of unique patients, management encounters, and telephone encounters throughout the study period. Secondary outcomes included trends in new encounters, and changes in patient characteristics, resources utilized, and patient satisfaction scores. A total of 2976 unique patients, 74,582 management encounters, and 13,282 telephone encounters were identified. From study beginning to end, results showed stable numbers of unique patients, an increase in management encounters for the DOAC group and decrease in the other anticoagulants group, and stable numbers of telephone encounters. Additionally, the number of new encounters for both groups increased. Throughout the study, pharmacy resources were reallocated within anticoagulation to adapt to the changing trends and patient satisfaction reached targets. Patients' characteristics remained stable, with the DOAC group having fewer comorbid conditions and concomitant medications that could increase bleed risk. This study showed that by reallocating resources within anticoagulation, AMS can maintain stable patient populations while continuing to expand access and satisfy patients following DOAC inclusion.

The prevalence of the acronym tl;dr (“too long; didn’t read”) suggests that people intentionally disengage their attention from long sections of text. We studied this real-world phenomenon in an ed...

Uncontrolled donation after cardiac death (uDCD) has the potential to ameliorate the shortage of suitable lungs for transplant. To date, no lung transplant data from these donors are available from North America. We describe the successful use of these donors using a simple method of in situ lung inflation so that the organ can be protected from warm ischemic injury. Forty-four potential donors were approached, and family consent was obtained in 30 cases (68%). Of these, the lung transplant team evaluated 16 uDCDs on site, and 14 were considered for transplant pending ex vivo lung perfusion assessment. Five lungs were ultimately used for transplant (16.7% use rate from consented donors). The mean warm ischemic time was 2.8 hours. No primary graft dysfunction grade 3 was observed at 24, 48, or 72 hours after transplant. Median intensive care unit stay was 5 days (range: 2-78 days), and median hospital stay was 17 days (range: 8-100 days). The 30-day mortality was 0%. Four of 5 patients are alive at a median of 651 days (range: 121-1254 days) with preserved lung function. This study demonstrates the proof of concept and the potential for uDCD lung donation using a simple donor intervention.

Rumination occurs when an individual becomes mentally stuck and cannot redirect attention away from an unwanted thought demonstrating cognitive inflexibility. Cognitive flexibility is important for various cognitive functions, including episodic memory. Trait rumination is a partial mediator in the relationship between depression and overgeneral episodic memory, suggesting that rumination may negatively influence memory for contextual details. Oscillations in the alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are crucial for various cognitive functions (e.g., attention control and episodic memory) and may help to explain the relationship between trait rumination and memory for contextual details. Our study uses EEG recorded during a source memory task to assess how alpha and beta oscillations during memory for contextual details may change as a function of trait rumination, anxiety, and depression level (n = 43). The source memory task instructs participants to remember objects and their associated contextual details. Memory for contextual details is lessened for participants higher in trait rumination paired with higher trait anxiety. Oscillations were analyzed in posterior parietal/occipital regions. During encoding, an interaction of nonclinical depression level and rumination predicts higher alpha power for items that were later not successfully remembered. During test, depression and rumination interact and predict higher alpha power for both successful and unsuccessful memory. These results suggest that trait anxiety, depression, and rumination impact accuracy and alpha oscillatory dynamics during contextual memory via changes in attention control.

The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with sequence feature annotations by WGSA and functional annotations to Gene Ontology (GO) and pathways in PANTHER. The database operates on an optimized Elasticsearch framework to support real-time complex searches. This implementation enables users to annotate data with the most up-to-date functional annotations via simple queries instead of setting up individual tools. A web interface allows users to interactively browse the annotations, annotate variants and search variant data. Its easy-to-use interface and search capabilities are well-suited for scientists with fewer bioinformatics skills such as bench scientists and statisticians. AnnoQ also has an API for users to access and annotate the data programmatically. Packages for programming languages, such as the R package, are available for users to embed the annotation queries in their scripts. AnnoQ serves researchers with a wide range of backgrounds and research interests as an integrated annotation platform.

In this study, we focus on the impact of daily virtual nature experiences combined with mindfulness practices on remote workers' creativity, stress, and focus over an extended period (9 weeks) during the COVID-19 pandemic. Our results show a positive effect of virtual reality (VR) nature experience on increasing focus and reducing stress. When VR nature and mindfulness practices were combined, we also found an increase in convergent thinking task performance. Our findings demonstrate that 10-minute daily exposure to VR nature and mindfulness practices could compensate for some of the adverse effects of working remotely by improving some aspects of workers' well-being and creativity.

It has been argued that high restrained eaters (i.e., people who fluctuate between restrictive food intake and overeating) are characterised by a heightened attentional bias to high calorie foods. However, the validity of this hypothesis has not yet been convincingly established. The current study sought to empirically evaluate this hypothesis using two directional measures of attentional bias: the well-established dot probe bias assessment task and the more novel Chase the Food bias assessment task. The latter attentional assessment approach has the capacity to differentiate between attentional switching and attentional maintenance within a complex and dynamic food environment. Participants (61 high restrained eaters and 38 low restrained eaters) completed the dot probe task and the Chase the Food task. Findings obtained on the dot probe task did not reveal a group difference in terms of biased attentional responding towards high calorie vs. low calorie food. Conversely, the two groups were found to differ on one of the measures obtained on the Chase the Food task. Specifically, high restrained eaters, as compared to low restrained eaters, demonstrated speeded attentional switching to high calorie foods, rather than a greater ability to maintain attention on high calorie foods when required to do so. These novel findings imply that high restrained eaters are potentially characterised by facilitated attentional switching towards high calorie foods. Implications are discussed including the possibility of targeting biased attentional switching using training variants of the Chase the Food task in interventions designed to reduce maladaptive eating behaviours.

We zone out roughly 20-40% of the time during reading – a rate that is concerning given the negative relationship between mind-wandering and comprehension. We tested if Eye-Mind Reader – an intelli...

We investigate the use of commercial off-the-shelf (COTS) eye-trackers to automatically detect mind wandering—a phenomenon involving a shift in attention from task-related to task-unrelated thoughts—during computerized learning. Study 1 (N = 135 high-school students) tested the feasibility of COTS eye tracking while students learn biology with an intelligent tutoring system called GuruTutor in their classroom. We could successfully track eye gaze in 75% (both eyes tracked) and 95% (one eye tracked) of the cases for 85% of the sessions where gaze was successfully recorded. In Study 2, we used this data to build automated student-independent detectors of mind wandering, obtaining accuracies (mind wandering F1 = 0.59) substantially better than chance (F1 = 0.24). Study 3 investigated context-generalizability of mind wandering detectors, finding that models trained on data collected in a controlled laboratory more successfully generalized to the classroom than the reverse. Study 4 investigated gaze- and video- based mind wandering detection, finding that gaze-based detection was superior and multimodal detection yielded an improvement in limited circumstances. We tested live mind wandering detection on a new sample of 39 students in Study 5 and found that detection accuracy (mind wandering F1 = 0.40) was considerably above chance (F1 = 0.24), albeit lower than offline detection accuracy from Study 1 (F1 = 0.59), a finding attributable to handling of missing data. We discuss our next steps towards developing gaze-based attention-aware learning technologies to increase engagement and learning by combating mind wandering in classroom contexts.

In university classrooms, the use of laptops or smartphones for purposes unrelated to the lecture is on the rise. Consequently, it is important to understand how frequently this behavior occurs, to track whether it increases throughout a lecture, and to quantify the potential costs to learning. In two studies, we measured rates of disengagement during lectures related to media use (i.e. media multitasking; Studies 1 & 2) and lecture-unrelated thoughts (i.e. mind wandering; Study 2). We also measured the impact of these behaviors on learning using quiz questions at the end of each lecture, and students’ actual course tests. In both Study 1 and 2, we found that rates of media multitasking were relatively high and increased as time elapsed in a lecture, while in Study 2, consistent with prior work, rates of mind wandering remained relatively stable. Interestingly, media multitasking - but not mind wandering - was associated with negative learning outcomes.

Task-unrelated thoughts (TUTs) are frequent distractions from our everyday tasks, which can reduce productivity and safety during task performance. This necessitates the examination of factors that modulate TUT occurrence in daily life. One factor that has previously been implicated as a source of TUT is personally salient concerns. External factors such as news media serve as cues for these concerns, potentially increasing TUT occurrence. However, this has not been thoroughly examined in everyday life settings. We thus utilized Ecological Momentary Assessment to survey participants throughout the day for ten days, on their TUTs and news consumption in two separate studies. Study 1 focused on the impact of news related to the Coronavirus Disease (COVID-19) pandemic, as a common and global concern. We found that TUT occurrence was significantly predicted by COVID-19 news consumption, such that TUT occurrence increased with COVID-19 news consumption. To extend these findings, we implemented Study 2 using similar methods, but focusing on the consumption of news media in general. TUT occurrence was predicted by general news consumption, with an increase in reports of TUT following consumption of news media in general. We thus extended the association found between TUT and COVID-19-related news in Study 1, to any news topic in Study 2. We speculate that the increase in TUTs was due to heightened salience of current concerns, cued by the news. These findings highlight the importance of considering when we choose to consume news media and the value of examining contextual factors when studying TUTs in daily life.

This protocol is for the high-throughput transcriptome screening method called, 3’ Digital Gene Expression (3’-DGE). In this method RNA is purified from cell lysate and cDNA is generated by oligo dT priming, during which unique molecular identifiers (UMIs) are incorporated and strand-specificity is preserved. The 3’-DGE protocol has been optimized for 384 well plate experiments with a few thousand cells per well. The 3’-DGE method and a similar method known as DRUG-seq have been shown to be able to recapitulate 85% of the transcriptome you can obtain with standard mRNA-seq. In our experience using 3’-DGE we sequence each well at a low depth, aiming for ~1 million reads per sample which allows us to asses 40-80% of the transcriptome depending on the cell type. It is possible to sequence these samples to a greater depth if warranted. It is important to keep in mind that in 3’-DGE, and most low-input methods, only the 3’ poly-A end of the transcript is preserved. Therefore, this technique cannot be used if it is important to capture splice-isoforms or transcripts that do not have a poly-A tail. This is a modification of the SCRB-seq protocol originally published here: https://www.biorxiv.org/content/10.1101/003236v1; Recognition also goes to the Enard group and their modifications to SCRB-seq found here: https://www.protocols.io/view/mcscrb-seq-protocol-p9kdr4w The home-brew SPRI beads used in this study are made with this protocol: dx.doi.org/10.17504/protocols.io.bkppkvmn

Much of our knowledge about the correlates of mind-wandering comes from assessing task-unrelated thought. Less is known about the correlates of freely moving thought, a dimension that assesses the degree to which thoughts arise and unfold with low levels of guidance or constraints. Task-unrelated thought is consistently associated with more negative affective valence compared with being on task; however, it is unclear whether freely moving thought shares the same relationship with affect. We conducted two ecological momentary assessment studies in the context of everyday life and found that the two dimensions have different affective correlates. In Study 1, task-unrelated thought was associated with less positive concurrent valence than being on-task. However, freely moving thought was associated with more positive concurrent valence and was predictive of more positive valence at a subsequent timepoint. Freely moving thought, but not task-unrelated thought, also positively predicted concurrent arousal. Computational sentiment analyses of participants' thought descriptions offered convergent evidence of differential relationships between the two thought dimensions and affect. Study 2 used different measurement scales to assess whether (a) the pattern of findings replicated and (b) if the effects were robust to changes in measurement. The main findings were replicated: task-unrelated thought was negatively associated with concurrent valence, whereas freely moving thought was positively associated with concurrent valence. However, freely moving thought did not predict subsequent valence and was not related to concurrent arousal. The most robust findings related to concurrent valence. Although mind-wandering has acquired a relatively negative reputation to date, our findings suggest that there might be positive aspects that remain unexplored. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Humans spend much of their lives engaging with their internal train of thoughts. Traditionally, research focused on whether or not these thoughts are related to ongoing tasks, and has identified reliable and distinct behavioral and neural correlates of task-unrelated and task-related thought. A recent theoretical framework highlighted a different aspect of thinking—how it dynamically moves between topics. However, the neural correlates of such thought dynamics are unknown. The current study aimed to determine the electrophysiological signatures of these dynamics by recording electroencephalogram (EEG) while participants performed an attention task and periodically answered thought-sampling questions about whether their thoughts were 1) task-unrelated, 2) freely moving, 3) deliberately constrained, and 4) automatically constrained. We examined three EEG measures across different time windows as a function of each thought type: stimulus-evoked P3 event-related potentials and non–stimulus-evoked alpha power and variability. Parietal P3 was larger for task-related relative to task-unrelated thoughts, whereas frontal P3 was increased for deliberately constrained compared with unconstrained thoughts. Frontal electrodes showed enhanced alpha power for freely moving thoughts relative to non-freely moving thoughts. Alpha-power variability was increased for task-unrelated, freely moving, and unconstrained thoughts. Our findings indicate distinct electrophysiological patterns associated with task-unrelated and dynamic thoughts, suggesting these neural measures capture the heterogeneity of our ongoing thoughts.

Off-task thought has been found to occur at high rates and is related to impairment in ADHD. However, off-task thought is heterogenous and it remains unclear which specific dimensions of off-task thought are more prevalent in this disorder. It is therefore important to dissociate different aspects of off-task thought in order to better understand the mechanisms underlying impairment. The current study focused on the dimension of constrained (focused) to freely moving off-task thought. Self-report and neurophysiological measures during a computerized attention tasks provided convergent evidence that individuals with ADHD not only have more off-task thought than those without, but also engaged in a greater proportion of freely moving off-task thought than non-ADHD controls. Overall, this work demonstrated differences in both the quantity and type of off-task thought in adults with ADHD. It provides novel insight into both the phenomenology of off-task thought, as well as potential mechanisms underlying impairment in ADHD.

There is a growing interest in the ability to detect where people are looking in real-time to support learning, collaboration, and efficiency. Here we present an overview of computational methods for accurately classifying the area of visual attention on a horizontal surface that we use to represent an interactive display (i.e. tabletop). We propose a new model that utilizes a neural network to estimate the area of visual attention, and provide a close examination of the factors that contribute to the accuracy of the model. Additionally, we discuss the use of this technique to model joint visual attention in collaboration. We achieved a mean classification accuracy of 75.75% with a standard deviation of 0.14 when data from four participants was used in training the model and then tested on the fifth participant. We also achieved a mean classification accuracy of 98.8% with 0.02 standard deviation when different amounts of overall data was used to test the model.

PANTHER (Protein Analysis Through Evolutionary Relationships, http://www.pantherdb.org) is a resource for the evolutionary and functional classification of protein-coding genes from all domains of life. The evolutionary classification is based on a library of over 15,000 phylogenetic trees, and the functional classifications include Gene Ontology terms and pathways. Here, we analyze the current coverage of genes from genomes in different taxonomic groups, so that users can better understand what to expect when analyzing a gene list using PANTHER tools. We also describe extensive improvements to PANTHER made in the past two years. The PANTHER Protein Class ontology has been completely refactored, and 6101 PANTHER families have been manually assigned to a Protein Class, providing a high level classification of protein families and their genes. Users can access the TreeGrafter tool to add their own protein sequences to the reference phylogenetic trees in PANTHER, to infer evolutionary context as well as fine-grained annotations. We have added human enhancer-gene links that associate non-coding regions with the annotated human genes in PANTHER. We have also expanded the available services for programmatic access to PANTHER tools and data via application programming interfaces (APIs). Other improvements include additional plant genomes and an updated PANTHER GO-slim.

Mind wandering is often characterized by attention oriented away from an external task towards our internal, self-generated thoughts. This universal phenomenon has been linked to numerous disruptive functional outcomes, including performance errors and negative affect. Despite its prevalence and impact, studies to date have yet to identify robust behavioral signatures, making unobtrusive, yet reliable detection of mind wandering a difficult but important task for future applications. Here we examined whether electrophysiological measures can be used in machine learning models to accurately predict mind wandering states. We recorded scalp EEG from participants as they performed an auditory target detection task and self-reported whether they were on task or mind wandering. We successfully classified attention states both within (person-dependent) and across (person-independent) individuals using event-related potential (ERP) measures. Non-linear and linear machine learning models detected mind wandering above-chance within subjects: support vector machine (AUC = 0.715) and logistic regression (AUC = 0.635). Importantly, these models also generalized across subjects: support vector machine (AUC = 0.613) and logistic regression (AUC = 0.609), suggesting we can reliably predict a given individual’s attention state based on ERP patterns observed in the group. This study is the first to demonstrate that machine learning models can generalize to “never-seen-before” individuals using electrophysiological measures, highlighting their potential for real-time prediction of covert attention states.

Individual and organizational computer security rests on how people interpret and use the security information they are presented. One challenge is determining whether a given URL is safe or not. This paper explores the visual behaviors that users employ to gauge URL safety. We conducted a user study on 20 participants wherein participants classified URLs as safe or unsafe while wearing an eye tracker that recorded eye gaze (where they look) and pupil dilation (a proxy for cognitive effort). Among other things, our findings suggest that: users have a cap on the amount of cognitive resources they are willing to expend on vetting a URL; they tend to believe that the presence of www in the domain name indicates that the URL is safe; and they do not carefully parse the URL beyond what they perceive as the domain name.

Rumination occurs when an individual becomes mentally stuck and cannot redirect attention away from an unwanted thought demonstrating cognitive inflexibility. Cognitive flexibility is important for various cognitive functions, including episodic memory. Trait rumination is a partial mediator in the relationship between depression and overgeneral episodic memory, suggesting that rumination may negatively influence memory for contextual details. Oscillations in the alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are crucial for various cognitive functions (e.g., attention control and episodic memory) and may help to explain the relationship between trait rumination and memory for contextual details. Our study uses EEG recorded during a source memory task to assess how alpha and beta oscillations during memory for contextual details may change as a function of trait rumination, anxiety, and depression level (n = 43). The source memory task instructs participants to remember objects and their associated contextual details. Memory for contextual details is lessened for participants higher in trait rumination paired with higher trait anxiety. Oscillations were analyzed in posterior parietal/occipital regions. During encoding, an interaction of nonclinical depression level and rumination predicts higher alpha power for items that were later not successfully remembered. During test, depression and rumination interact and predict higher alpha power for both successful and unsuccessful memory. These results suggest that trait anxiety, depression, and rumination impact accuracy and alpha oscillatory dynamics during contextual memory via changes in attention control.

The question of how to evaluate creativity in the context of creative writing has been a subject of ongoing discussion. A key question is whether something as elusive as creativity can be evaluated in a systematic way that goes beyond subjective judgments. To answer this question, we tested whether human evaluations of the creativity of short stories can be predicted by: (1) established measures of creativity and (2) computerized linguistic analyses of the stories. We conducted two studies, in which college students (with and without interest and experience in creative writing) wrote short stories based on a writing prompt. Independent raters (six in Study 1, five in Study 2) assessed the stories using an evaluation rubric specifically designed to assess aspects of creativity, on which they showed high interrater reliability. We provide evidence of convergent validity, in that the rubric evaluations correlated with established creativity measures, including measures of divergent thinking, associative fluency, and self-reported creative behavior and achievements. Linguistic properties of the short stories were analyzed with two computerized text analysis tools: Coh-Metrix, which analyzes aspects of text cohesion and readability, and Linguistic Inquiry and Word Count, which identifies meaningful psychological categories of the text content. Linguistic features predicted the human ratings of creativity to a significant degree. These results provide novel evidence that creative writing can be evaluated reliably and in a systematic way that captures objective features of the text. The results further establish our evaluation rubric as a useful tool to assess creative writing.

Abstract. Material re-exposure (e.g., re-reading) is a popular mnemonic strategy, however, its utility has been questioned. We extend research on re-reading to re-watching – an emerging mnemonic technique given the increased use of recorded lectures today (e.g., in online courses). Consistent with findings from recent investigations of re-reading, there were no benefits of massed re-watching on memory for lecture material and re-watching increased rates of mind wandering. We discuss implications for understanding the cognitive consequences of re-exposure-based mnemonics.

Online education provides the opportunity to present lecture material to students in different formats or modalities, however there is debate about which lecture formats are best. Here, we conducted four experiments with 19–68 year old online participants to address the question of whether visuals of the instructor in online video lectures benefit learning. In Experiments 1 (N = 168) and 2 (N = 206) participants were presented with a lecture in one of three modalities (audio, audio with text, or audio with visuals of the instructor). Participants reported on their attentiveness – mind wandering (MW) – throughout the lecture and then completed a comprehension test. We found no evidence of an advantage for video lectures with visuals of the instructor in terms of a reduction in MW or increase in comprehension. In fact, we found evidence of a comprehension cost, suggesting that visuals of instructors in video lectures may act as a distractor. In Experiments 3 (N = 88) and 4 (N = 109) we explored learners' subjective evaluations of lecture formats across 4 different lecture formats (audio, text, audio + text, audio + instructor, audio + text + instructor). The results revealed learners not only find online lectures with visuals of the instructor more enjoyable and interesting, they believe this format most facilitates their learning. Taken together, these results suggest visuals of the instructor potentially impairs comprehension, but learners prefer and believe they learn most effectively with this format. We refer to as the Instructor Presence Effect and discuss implications for multimedia learning and instructional design.

Despite increasing scientific interest in self-generated thought-mental content largely independent of the immediate environment-there has yet to be any comprehensive synthesis of the subjective experience and neural correlates of affect in these forms of thinking. Here, we aim to develop an integrated affective neuroscience encompassing many forms of self-generated thought-normal and pathological, moderate and excessive, in waking and in sleep. In synthesizing existing literature on this topic, we reveal consistent findings pertaining to the prevalence, valence, and variability of emotion in self-generated thought, and highlight how these factors might interact with self-generated thought to influence general well-being. We integrate these psychological findings with recent neuroimaging research, bringing attention to the neural correlates of affect in self-generated thought. We show that affect in self-generated thought is prevalent, positively biased, highly variable (both within and across individuals), and consistently recruits many brain areas implicated in emotional processing, including the orbitofrontal cortex, amygdala, insula, and medial prefrontal cortex. Many factors modulate these typical psychological and neural patterns, however; the emerging affective neuroscience of self-generated thought must endeavor to link brain function and subjective experience in both everyday self-generated thought as well as its dysfunctions in mental illness.

We investigated how affective states influence expository text comprehension and whether text valence moderates the effects (i.e., mood congruency). In Experiment 1 participants were randomly assigned to a happy or sad affective state (elicited via films) before reading a positive or negative version of a scientific text on animal adaptations. Participants (n = 79) in the sad (film) group had higher scores on deep-reasoning (d = .312) but not surface-level questions on a subsequent multiple-choice comprehension assessment; there was also no evidence for mood congruence. Using a neutral version of the same text, in Experiment 2 participants (n = 52) in a fearful condition performed better on surface-level comprehension questions (d = .594) compared with a sad condition, but the groups were on par for deep-reasoning questions. Experiment 3 (n = 595) did not replicate the findings from Experiment 2 (no comprehension differences between the sad and fear groups) and there were no differences between th...

Background Teratogenic medications increase risks of miscarriage, fetal death, and/or birth defects. It is important to identify whether women of childbearing potential are taking these medications and to minimize exposure to these agents through change in drug therapy before conception and/or use of effective contraception to prevent conception. Objective To determine the utility of reproductive life plans as tools to identify women using potentially teratogenic medications. Methods A retrospective review was conducted on reproductive life plans completed by women receiving services as part of the Toledo-Lucas County Healthy Start program. The medication section of the reproductive life plan was reviewed to determine: if it was completed; categories of medications reported (prescription, over-the-counter, vitamin/herbal); potentially teratogenic medications listed; contraception use and method. Results Medication lists were completed for 437 of the 580 reproductive life plans reviewed (75%). Thirty-five women (8%) reported use of a potentially teratogenic medication; most commonly reported agents included blood pressure medications and antidepressants. Only 10 women taking a potentially teratogenic medication (29%) reported using some form of contraception, half of which reported use of a less effective method such as condoms. Conclusion The reproductive life plan can be a useful tool to identify women of childbearing age who require intervention due to use of potentially teratogenic medications. Efforts are needed to ensure complete and accurate reporting of medication use in reproductive life plans, and to promote effective contraceptive use among women taking potentially teratogenic medications.

We hypothesize that cognitively engaged readers dynamically adjust their reading times with respect to text complexity (i.e., reading times should increase for difficult sections and decrease for easier ones) and failure to do so should impair comprehension. This hypothesis is consistent with theories of text comprehension but has surprisingly been untested. We tested this hypothesis by analyzing 4 datasets in which participants (N = 484) read expository texts using a self-paced reading paradigm. Participants self-reported mind wandering in response to pseudorandom thought-probes during reading and completed comprehension assessments after reading. We computed two measures of cognitive coupling by regressing each participant's paragraph-level reading times on two measures of text complexity: Flesch-Kincaid Grade Level and Word Concreteness scores. The two coupling measures yielded convergent findings: coupling was a negative predictor of mind wandering and a positive predictor of both text- and inference-level comprehension. Goodness-of-fit, measured with Akaike information criterion, also improved after adding coupling to the reading-time only models. Furthermore, cognitive coupling mediated the relationship between mind wandering and comprehension, supporting the hypothesis that mind wandering engenders a decoupling of attention from external stimuli. (PsycINFO Database Record

Despite the ubiquitous nature of boredom, the definition, function, and correlates of boredom are still poorly understood. In this review, we summarize the "known" (consistent evidence) and "unknown" (inconsistent evidence) correlates of boredom. We show that boredom is consistently related to negative affect, task-unrelated thought, over-estimation of elapsed time, reduced agency, as well as to over- and under-stimulation. Activation of the default mode network was consistent across the few available fMRI studies, while the recruitment of other brain areas such as the hippocampus and anterior insular cortex, was a notable but less consistent correlate of boredom. Other less consistent correlates of boredom are also reviewed, such as the level of arousal and the mental attributions given to fluctuations of attention. Finally, we identify two critical factors that may contribute to current inconsistencies in the literature and may hamper further progress in the field. First, there is relatively little consistency in the way in which boredom has been operationalized across studies to date, with operationalizations of boredom ranging from negative affect paired with under-stimulation, over-stimulation, to negative affect paired with a lack of goal-directed actions. Second, preliminary evidence suggests the existence of distinct types of boredom (e.g., searching vs. apathetic) that may have different and sometimes even opposing correlates. Adopting a more precise and consistent way of operationalizing boredom, and arriving at an empirically validated taxonomy of different types of boredom, could serve to overcome the current roadblocks to facilitate further progress in our scientific understanding of boredom.