Laura Germine’s research while affiliated with McLean Hospital and other places

Background: Phenylketonuria (PKU) is a rare, hereditary disease that causes disruption in phenylalanine (Phe) metabolism. Despite early intervention, individuals with PKU may have difficulty in several different cognitive domains, including verbal fluency, processing speed, and executive functioning. Objective: The overarching goal of the Evaluating Fluctuations in Cognitive and Speech Characteristics in Phenylketonuria study (CSP Study) is to characterize the relationships among cognition, speech, mood, and blood-based biomarkers (Phe, Tyr) in individuals with early treated PKU. We describe our initial optimization pilot results that are guiding the ongoing CSP Study, while establishing feasibility and reliability of using ecological momentary assessment (EMA) in this clinical population. Methods: Twenty adults with PKU were enrolled in this study between December 2022 and March 2023 through the National PKU Alliance. Eighteen participants completed an extended baseline assessment followed by six EMAs over one month. The EMAs included digital cognitive tests measuring processing speed, sustained attention, executive functioning, as well as speech (semantic fluency) and mood measures. Participants had 60 minutes to complete the assessment; completion rates were around 70% (on average 4.78 out of 6 EMAs). Results: Completion rates of EMAs were above 70%, with stable performances across baseline measures and EMAs. Between person reliability (BPR) of the EMAs, representing the variance due to differences between individuals versus within individuals, is satisfactory with values close to (semantic fluency BPR: 0.7, sustained attention BPR: 0.72) or exceeding (processing speed: 0.93, executive functioning: 0.88) those data collected from a large normative database (N= 5039-10703), as well as slightly below or matching a prior study using a clinical group (N=18). As applicable, within person reliability was also computed; we demonstrated strong reliability for processing speed (0.87). A control analyses ensured that time of day (i.e., morning, afternoon, evening) did not impact performance; performance on tasks did not decrease if tested earlier versus later in the day (all ps>0.09). Similarly, to assess variability in task performance over the course of all EMAs, the coefficient of variability was computed: 28% for the task measuring sustained attention, 37% percent for semantic fluency, 15.8 % for the task measuring executive functioning, and 17.6% for processing speed. Performance appears more stable in tasks measuring processing speed and executive functioning than on tasks of sustained attention and semantic fluency. Conclusions: Preliminary results of this study demonstrate strong reliability of cognitive EMA, indicating that EMA is a promising tool for evaluating fluctuations in cognitive status in this population. Future work should refine and expand the utility of these digital tools, determine how variable EMA frequencies might better characterize changes in functioning as they relate to blood-based biomarkers, and validate a singular battery that could be rapidly administered at scale and in clinical trials to determine progression of disease.

Cognitive variability is associated with fall risk, cardiovascular mortality, and cognitive decline. Identifying factors that influence cognitive variability may inform evidence-based guidelines aimed at supporting cognitive and physical health across the lifespan. This goal is particularly salient in Type I Diabetes (T1D), an autoimmune condition characterized by large glucose fluctuations. T1D confers risk for neurodegeneration, and laboratory studies suggest that cognition is reduced when glucose is very low or very high. The present study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to clarify the impact of naturally-occurring glucose fluctuations on cognitive performance (sustained attention, processing speed) in 200 adults with T1D. Using hierarchical Bayesian modeling, we observed that large glucose fluctuations were associated with slower and less accurate processing speed. Glucose fluctuations were not related to sustained attention, and some individuals exhibited greater cognitive vulnerability to glucose fluctuations than others. Using data-driven lasso regression, we identified seven clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and characteristics (e.g. neck circumference) previously linked with weight and sleep apnea. These results establish the impact of glucose on processing speed in naturalistic environments and indicate that minimizing glucose fluctuations is important for optimizing processing speed. Beyond T1D, this work demonstrates how data from physiological sensors and EMA can be integrated to better understand individual differences in daily cognitive functioning and clinical risk.

Previous work indicates that (1) changes in diurnal cycles are associated with the onset and progression of dementia and cognitive impairment and (2) that cognitive function itself tends to show diurnal cycles in the laboratory. But no work to date has examined whether cognitive function assessed via ecological momentary assessment can recover such daily cycles and whether individual differences in those cycles are associated with short- and long-term outcomes. In this presentation, we examine whether ambulatory cognitive assessments assessed via ecological momentary assessment (EMA) demonstrate intra-day cycles of cognitive performance. This study specifically aims to test whether such cycles emerge, whether there are individual differences in those cycles, and whether individual differences are associated with cross-sectional measures of cognitive health and psychosocial risk factors. At baseline, 200 (Mean age = 55; 50.1% female) participants responded to five surveys per day for 20 days capturing their cognitive function, contextual factors, and psychological experiences. We will examine nonlinear changes in cognitive function through the day using both multilevel time series decomposition and cosinor models, which also allow us to examine individual differences in these patterns. We will then examine whether these individual differences are concurrently associated with global cognitive functioning, cognitive impairment, personality traits, and other psychosocial factors.

Background: Ecological momentary assessment (EMA) is a promising tool for understanding temporal dynamics of behavior and mental health. EMAs are administered in naturalistic environments, however, and are therefore susceptible to interference from competing demands on a participant’s attention, which can lead to interruptions during EMA completion. Interruptions can compromise the completeness, validity, or interpretation of results, and/or indicate problems with participant burden. Methods: To understand who is impacted most by interruptions, we analyzed data from 517 participants who completed a 21-day EMA protocol assessing emotion and cognition (3x/day at pseudo-random intervals). At the end of each EMA, participants indicated if they experienced any interruptions. We used linear regression to examine the relationship between person-level factors (age, gender, race/ethnicity, baseline mental health symptoms) and the proportion of EMAs that were interrupted.Results: On average, participants reported interruptions on 12% of completed EMAs with 77.4% of participants reporting at least one interruption over the course of the study. Identifying as female (p<0.001), Hispanic (p<0.01), African American (p<0.05), as well as higher levels of baseline depression, ADHD symptoms, and cross-cutting symptom severity (all p<0.01) were associated with a higher proportion of interruptions. Having young children in the home moderated the impact of gender on self-reported interruptions (p<0.05). The presence of young children was associated with more interruptions for female participants (p<0.01), but not male participants (p=0.55). EMA completion rate, age, education, and substance use were not significantly associated with interruptions.Conclusion: Participants differed in the extent to which they experienced interruptions during EMA. In general, female participants (especially those with young children), racial minorities, and individuals with more mental health concerns were more likely to experience interruptions. Our results suggest that psychosocial factors may contribute to barriers to engaging with EMA protocols.

BACKGROUND Emotional disorders like depression and anxiety are characterized by high levels of negative affect (NA), frequent fluctuations in NA, and deficits in cognitive performance. College students are among the most vulnerable to emotional disorders. OBJECTIVE Despite recent advances in cognitive ecological momentary assessment (EMA), it remains unclear how daily experiences of NA impact momentary cognitive performance in emerging adults. Our primary objective was to test the hypothesis was that fluctuations in NA would be associated with RT inconsistency. METHODS Undergraduate and graduate students (N=99) completed an online baseline assessment as part of a 14-day EMA protocol. Baseline included self-report questionnaires measuring emotional disorder symptoms (neuroticism, anxiety, depression, insomnia) and a battery of cognitive tasks. Daily EMAs measured affect using the Positive and Negative Affect Schedule and cognition using a Choice Reaction Time (RT) task. We evaluated correlations among emotional disorder symptoms at baseline as a validity check. We ran multilevel models examining within- person associations between NA and trial-level RT inconsistency. RESULTS Between individuals, NA, neuroticism, depression, and anxiety symptoms were all positively and significantly correlated at baseline. Within individuals, greater NA predicted greater RT inconsistency, controlling for several demographic and clinical variables. CONCLUSIONS Partially consistent with hypotheses, we observed greater RT inconsistency on days when NA was higher than usual. However, this main effect was moderated by practice effects, and within-person effect of NA on RT inconsistency diminished over time in the study. Results have implications for mental health and academic performance. Specifically, performance may be more inconsistent when individuals experience higher NA and stress. CLINICALTRIAL NA

BACKGROUND Phenylketonuria (PKU) is a rare, hereditary disease that causes disruption in phenylalanine (Phe) metabolism. Despite early intervention, individuals with PKU may have difficulty in several different cognitive domains, including verbal fluency, processing speed, and executive functioning. OBJECTIVE The overarching goal of the Evaluating Fluctuations in Cognitive and Speech Characteristics in Phenylketonuria study (CSP Study) is to characterize the relationships among cognition, speech, mood, and blood-based biomarkers (Phe, Tyr) in individuals with early treated PKU. We describe our initial optimization pilot results that are guiding the ongoing CSP Study, while establishing feasibility and reliability of using ecological momentary assessment (EMA) in this clinical population. METHODS Twenty adults with PKU were enrolled in this study between December 2022 and March 2023 through the National PKU Alliance. All participants completed an extended baseline assessment followed by six ecological momentary assessments (EMAs) over the span of one month. The EMAs included digital cognitive tests measuring processing speed, sustained attention, executive functioning, and semantic fluency, as well as speech and mood measures. Participants had 60 minutes to complete the assessment; completion rates were around 70% (on average 4.78 measurements out of six). RESULTS Based on scores recorded and completion rates above 70%, results suggest stable performance across EMAs, as well as baseline measures, and reflect the ability of participants to complete this type of repeated assessment. Between person reliability (BP reliability) of the EMA measures, representing the variance that is due to differences between individuals versus within individuals, is satisfactory with values close to (semantic fluency BP reliability: 0.7, sustained attention BP reliability: 0.72) or exceeding (processing speed: 0.93, executive functioning: 0.88) those data collected from a large normative database (N= 5039-10703), as well as slightly below or matching a prior study using a clinical group (N=18). CONCLUSIONS : Individuals with PKU face a substantial healthcare burden, often enduring numerous hospital visits and requiring continuous self-monitoring. Preliminary results of this study have demonstrated strong reliability of cognitive EMA, indicating that EMA is a promising tool for evaluating fluctuations in cognitive status this population. Future work should refine and expand the utility of these digital tools, determine how variable EMA frequencies might better characterize changes in functioning as they relate to blood-based biomarkers, and validate a singular battery that could be rapidly administered at scale and in clinical trials to determine progression of disease.

Research on individual differences in face recognition has provided important foundational insights: their broad range, cognitive specificity, strong heritability, and resilience to change. Elusive, however, has been the key issue of practical relevance: do these individual differences correlate with aspects of life that go beyond the recognition of faces, per se? Though often assumed, especially in social realms, such correlates remain largely theoretical, without empirical support. Here, we investigate an array of potential social correlates of face recognition. We establish social relationship quality as a reproducible correlate. This link generalises across face recognition tasks and across independent samples. In contrast, we detect no robust association with the sheer quantity of social connections, whether measured directly via number of social contacts or indirectly via extraversion-related personality indices. These findings document the existence of a key social correlate of face recognition and provide some of the first evidence to support its practical relevance. At the same time, they challenge the naive assumption that face recognition relates equally to all social outcomes. In contrast, they suggest a focused link of face recognition to the quality, not quantity, of one’s social connections.

STEM-related work is increasingly critical to economic development. Yet STEM education is leaky, with many individuals prematurely writing off STEM training and STEM careers. Could modern mind and brain research produce tools that identify STEM talent? Such tools would be most useful if they did not require learned STEM knowledge attained through prior education. Here, we reveal a prime candidate: multiple object tracking (MOT). A prominent test of spatial attention, MOT has well-documented links to math-related neural mechanisms. Yet it has not been systematically studied as a correlate of STEM outcomes. In a cognitively and demographically diverse cross-sectional sample of over 20,000 participants, we link MOT performance selectively to four separate indicators of STEM talent across the lifespan: K-12 school performance, college admissions test scores, college major, and occupation. MOT relates: (1) more strongly to self-reported K-12 math and science performance than writing performance, (2) more strongly to math SAT scores than verbal SAT scores, (3) more strongly than vocabulary performance to pursuing a STEM major in college, and (4) more strongly than vocabulary performance to obtaining a STEM profession. The selectivity of these links rules out broad cognitive or motivational mechanisms. At the same time, these links are demographically general, persisting across age, gender, and native language. We conclude that MOT is an efficient, focused correlate of STEM achievement. Plausibly, a STEM-linked tool, like MOT, that requires no prior STEM knowledge, could help to recruit and retain individuals to STEM who might otherwise be lost to a leaky pipeline.

This study examines the association between brain dynamic functional network connectivity (dFNC) and current/future posttraumatic stress (PTS) symptom severity, and the impact of sex on this relationship. By analyzing 275 participants’ dFNC data obtained ~2 weeks after trauma exposure, we noted that brain dynamics of an inter-network brain state link negatively with current (r=-0.179, p corrected = 0.021) and future (r=-0.166, p corrected = 0.029) PTS symptom severity. Also, dynamics of an intra-network brain state correlated with future symptom intensity (r = 0.192, p corrected = 0.021). We additionally observed that the association between the network dynamics of the inter-network brain state with symptom severity is more pronounced in females (r=-0.244, p corrected = 0.014). Our findings highlight a potential link between brain network dynamics in the aftermath of trauma with current and future PTSD outcomes, with a stronger protective effect of inter-network brain states against symptom severity in females, underscoring the importance of sex differences.