Faculty Bibliography

The role of fetal surveillance for the prediction and timely assessment of fetal distress is widely established. Fetal ECG (fECG) monitoring via wearable devices is a feasible solution for performing continuous monitoring of fetal wellbeing and it has seen a net increase in popularity in recent years. In this paper, we propose a novel adaptation of the Smart AdaptiVe Ecg Recognition (SAVER) algorithm for the detection of fECG in long-duration recordings acquired in clinical as well as unconventional settings. The methodology was trained and tested on 50 recordings of duration 1 hour ( 59.33 ±5.54 min) obtained using the Monica AN24 fetal monitor. We validated the performance against the automatic extraction performed by the Monica DK software. Our results show superior reliability of the proposed methodology in extracting fECG and associated estimates of fetal heart rate (fHR). Clinical relevance- The proposed methodology provides an efficient and reliable approach for the extraction of fECG signals acquired via wearable technologies, enabling continuous monitoring of fECG in and outside clinical settings.

The present study tested outcomes of the Transdiagnostic Sleep and Circadian Intervention (TranS-C) among midlife and older adults with serious mental illness (SMI). Further, we tested predictors-credibility, expectancy, usefulness, and utilization-that may affect TranS-C outcomes. Midlife and older participants from a community setting (>49 years, 62.3% female, 37.7% African American or Black) with sleep and circadian problems and SMI were randomized to receive TranS-C plus usual care (TranS-C+UC, n = 27) or usual care followed by delayed treatment with TranS-C (UC-DT, n = 26). Immediate and delayed TranS-C data were combined to increase power (combined n = 52). Outcomes were assessed at pretreatment, posttreatment, and 6-month follow-up. Credibility and expectancy were assessed during the second session. Usefulness and utilization of TranS-C skills were assessed at posttreatment and 6-month follow-up. TranS-C+UC, relative to UC-DT, was associated with improvements in depression symptoms, sleep disturbance, overall sleep health, and select sleep/wake outcomes, though not all improvements were sustained at 6-month follow-up. Lower usefulness of TranS-C skills predicted more severe sleep disturbance at posttreatment and daytime sleep-related impairment at posttreatment and 6-month follow-up. Lower utilization predicted more severe psychiatric symptoms at posttreatment, sleep disturbance at posttreatment and 6-month follow-up, and overall impairment and daytime sleep-related impairment at 6-month follow-up. Higher credibility and expectancy predicted greater usefulness of TranS-C skills at posttreatment and 6-month follow-up and greater utilization at 6-month follow-up. Together, findings highlight benefits of TranS-C for midlife and older adults with SMI. However, boosting credibility, expectancy, utilization, and usefulness may meaningfully improve TranS-C outcomes.

The presence of perinatal mood and anxiety disorders has typically been associated with decreases in the quality of mother-infant interactions. However, maternal anxiety symptoms during the postpartum period have been less studied than other mental health disorders like depression. In the current study, we examined associations among symptoms of maternal anxiety, maternal perceived stress, and mother-infant behavioral synchrony in the early postnatal period. Eighty-one mother-infant dyads participated in this study when the infants were 3 months old. Surveys were given to obtain demographic information and current maternal mental health symptoms, and dyads completed a 5-min free-play task to measure behavioral synchrony. Results indicated that maternal anxiety symptoms were positively associated with behavioral synchrony, but only for mothers reporting moderate levels of perceived stress. These findings highlight the differential impact of maternal postpartum mental health on behavioral synchrony and suggest that higher maternal anxiety symptoms during the postnatal period may play an adaptive role in fostering more dynamic mother-infant interactions.

Using a community-partnered research framework, the goal of this study was to rapidly assess coronavirus disease (COVID-19) impact on teachers, students, and families and guidance received to navigate distance learning. Participants were teachers (N = 430) working in elementary schools (n = 301), middle schools (n = 56), high schools (n = 60), and other schools (n = 13) in two large urban school districts heavily impacted by COVID-19. Results indicated teacher concerns regarding student instructional loss and exposure to direct and indirect COVID-related trauma. There were mean differences in teacher concern by school level (p = .001, η² = .033) with elementary teachers reporting the greatest concerns regarding instructional loss. Over 40% of teachers reported that more than 20% of their students had a family member infected with COVID-19 or employed as a frontline healthcare worker. Approximately 99% of teachers reported a significant gap in student access to the internet and distance learning devices. Teachers reported receiving more school than district guidance regarding distance learning, student engagement, and using social emotional learning (SEL) programs. Results informed professional development priorities for educators and immediate supports needed for students and families. Study limitations and future directions for research and practice are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The electrocardiogram (ECG) is a common source of electrical artifact in electroencephalogram (EEG). Here, we present a novel method for removing ECG artifact that requires neither simultaneous ECG nor transformation of the EEG signals. The approach relies upon processing a subset of EEG channels that contain ECG artifact to identify the times of each R-wave of the ECG. Within selected brief epochs, data in each EEG channel is signal-averaged ± 60 ms around each R-wave to derive an ECG template specific to each channel. This template is subtracted from each EEG channel which are aligned with the R-waves. The methodology was developed using two cohorts of infants: one with 128-lead EEG including an ECG reference and another with 32-lead EEG without ECG reference. The results for the first cohort validated the methodology the ECG reference and the second demonstrated its feasibility when ECG was not recorded. This method does not require independent, simultaneous recording of ECG, nor does it involve creation of an artifact template based on a mixture of EEG channel data as required by other methods such as Independent Component Analysis (ICA). Spectral analysis confirms that the method compares favorably to results using simultaneous recordings of ECG. The method removes ECG artifact on an epoch by epoch level and does not require stationarity of the artifact. Clinical Relevance - This approach facilitates the removal of ECG noise in frequency bands known to play a central role in brain mechanisms underlying cognitive processes.

Attention-deficit/hyperactivity disorder (ADHD) significantly worsens quality of life and long-term functional outcomes in adults. Individual impairments in adults with ADHD can be further contextualized within considerable costs to society at large. Food and Drug Administration (FDA) approved stimulants and nonstimulant medications can significantly improve ADHD symptoms in adults. In the past 2 decades, the United States FDA has expanded approval of pharmacotherapeutic options for adult ADHD. However, limitations still persist in available psychotropics for certain patient populations such as those with comorbid substance use or cardiovascular illness. Clinicians therefore must appreciate several ongoing investigations into medications with unique mechanisms of action. This article reviews the current FDA approved and emerging medication options while providing guidelines for pharmacologic management of adult ADHD.

The first months of life are critical for establishing neural connections relevant for social and cognitive development. Yet, the United States lacks a national policy of paid family leave during this important period of brain development. This study examined associations between paid leave and infant electroencephalography (EEG) at 3 months in a sociodemographically diverse sample of families from New York City (N = 80; 53 males; 48% Latine; data collection occurred 05/2018-12/2019). Variable-centered regression results indicate that paid leave status was related to differences in EEG power (ps < .02, R² s > .12). Convergent results from person-centered latent profile analyses demonstrate that mothers with paid leave were 7.39 times as likely to have infants with EEG profiles characterized by increased higher-Hz power (95% CI, 1.9-36.9), potentially reflecting more mature patterns of brain activity.

Increased study and methodological innovation have led to growth in the field of fetal brain fMRI. An important gap yet to be addressed is optimization of fetal fMRI preprocessing. Rapid developmental changes, imaged within the maternal compartment using an abdominal coil, introduce novel constraints that challenge established methods used in adult fMRI. This study evaluates the impact of (1) normalization to a group mean-age template versus normalization to an age-matched template; (2) independent components analysis (ICA) denoising at two criterion thresholds; and (3) smoothing using three kernel sizes. Data were collected from 121 fetuses (25-39 weeks, 43.8% female). Results indicate that the mean age template is superior in older fetuses, but less optimal in younger fetuses. ICA denoising at a more stringent threshold is superior to less stringent denoising. A larger smoothing kernel can enhance cross-hemisphere functional connectivity. Overall, this study provides improved understanding of the impact of specific steps on fetal image quality. Findings can be used to inform a common set of best practices for fetal fMRI preprocessing.

OBJECTIVE:(1) investigate the associations of attention-deficit/hyperactivity disorder (ADHD) with systolic and diastolic blood pressure, resting heart rate, pulse pressure (PP), physical fitness, and BMI; (2) explore whether cardiovascular risk factors and ADHD share genetic and environmental influences; (3) assess if pharmacological treatment for ADHD influences these associations. METHODS:We identified 395,978 individuals born between 1973 and 1991 who had military conscription examinations at a mean age of 18.3 years (SD = 0.57) and their full-siblings within the same cohort (N = 208,060) by linking population-based registers in Sweden. RESULTS:Significantly increased risk of ADHD was observed in individuals with low systolic blood pressure (SBP) and PP, low physical fitness, and in those who had overweight or obesity after adjustments (adjusted Odds Ratio [OR] ranging from 1.10 to 1.45). Full siblings of individuals with low SBP, low physical fitness, and obesity were more likely to receive an ADHD diagnosis compared to full siblings without those risk factors (OR ranging from 1.17 to 1.31). Additionally, analyses showed robust associations between ADHD and low SBP, low physical fitness, and obesity, even in ADHD medication-naïve individuals. CONCLUSIONS:Individuals with several cardiovascular risk factors are more often diagnosed with ADHD, regardless of psychiatric comorbidity. These association are not explained by ADHD pharmacotherapy, rather, they are in part due to shared familial risk factors.

Neural plasticity in subareas of the rodent amygdala is widely known to be essential for Pavlovian threat conditioning and safety learning. However, less consistent results have been observed in human neuroimaging studies. Here, we identify and test three important factors that may contribute to these discrepancies: the temporal profile of amygdala response in threat conditioning, the anatomical specificity of amygdala responses during threat conditioning and safety learning, and insufficient power to identify these responses. We combined data across multiple studies using a well-validated human threat conditioning paradigm to examine amygdala involvement during threat conditioning and safety learning. In 601 humans, we show that two amygdala subregions tracked the conditioned stimulus with aversive shock during early conditioning while only one demonstrated delayed responding to a stimulus not paired with shock. Our findings identify cross-species similarities in temporal- and anatomical-specific amygdala contributions to threat and safety learning, affirm human amygdala involvement in associative learning and highlight important factors for future associative learning research in humans.