Faculty Bibliography

Background and Aims/UNASSIGNED:Screen media activity (SMA) may impact neurodevelopment in youth. Cross-sectionally, SMA has been linked to brain structural patterns including cortical thinning in children. However, it remains unclear whether specific brain structural co-variation patterns are related to SMA and other clinically relevant measures such as psychopathology, cognition and sleep in children. Methods/UNASSIGNED:Adolescent Brain Cognitive Development (ABCD) participants with useable baseline structural imaging (N = 10,691; 5,107 girls) were analyzed. We first used the Joint and Individual Variation Explained (JIVE) approach to identify cortical and subcortical covariation pattern(s) among a set of 221 brain features (i.e., surface area, thickness, or cortical and subcortical gray matter (GM) volumes). Then, the identified structural covariation pattern was used as a predictor in linear mixed-effect models to investigate its associations with SMA, psychopathology, and cognitive and sleep measures. Results/UNASSIGNED:A thalamus-prefrontal cortex (PFC)-brainstem structural co-variation pattern (circuit) was identified. The pattern suggests brainstem and bilateral thalamus proper GM volumes covary more strongly with GM volume and/or surface area in bilateral superior frontal gyral, rostral middle frontal, inferior parietal, and inferior temporal regions. This covariation pattern highly resembled one previously linked to alcohol use initiation prior to adulthood and was consistent in girls and boys. Subsequent regression analyses showed that this co-variation pattern associated with SMA (β = 0.107, P = 0.002) and externalizing psychopathology (β = 0.117, P = 0.002), respectively. Discussion and Conclusions/UNASSIGNED:Findings linking SMA-related structural covariation to externalizing psychopathology in youth resonate with prior studies of alcohol-use initiation and suggest a potential neurodevelopmental mechanism underlying addiction vulnerability.

We performed a scientometric analysis of the scientific literature on ADHD to evaluate key themes and trends over the past decades, informing future lines of research. We conducted a systematic search in Web of Science Core Collection up to 15 November, 2021 for scientific publications on ADHD. We retrieved 28,381 publications. We identified four major research trends: 1) ADHD treatment, risks factors and evidence synthesis; 2) neurophysiology, neuropsychology and neuroimaging; 3) genetics; 4) comorbidity. In chronological order, identified clusters of themes included: tricyclic antidepressants, ADHD diagnosis/treatment, bipolar disorder, EEG, polymorphisms, sleep, executive functions, pharmacology, genetics, environmental risk factors, emotional dysregulation, neuroimaging, non-pharmacological interventions, default mode network, Tourette, polygenic risk score, sluggish cognitive tempo, evidence-synthesis, toxins/chemicals, psychoneuroimmunology, Covid-19, and physical exercise. In conclusion, research on ADHD over the past decades has been driven mainly by a medical model. Whereas the neurobiological correlates of ADHD are undeniable and crucial, we look forward to further research on relevant psychosocial aspects related to ADHD, such as societal pressure, the concept of neurodiversity, and stigma.

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.

OBJECTIVE:We meta-analyzed studies comparing perceptual timing abilities in the range of milliseconds to several seconds in individuals with ADHD and neurotypical participants, using the well-established time discrimination, time estimation, time production, and time reproduction paradigms. METHOD/METHODS:We searched Pubmed, OVID databases and WEB OF KNOWLEDGE through September 17, 2020. From 2,266 records, 55 studies were retained and meta-analyzed with random effects models. We conducted meta-regression analyses to explore moderating effects of task parameters and neuropsychological measures of working memory, attention, and inhibition on timing performance. RESULTS:Compared with those without ADHD, individuals with ADHD had significantly more severe difficulties in discriminating stimuli of very brief durations, especially in the sub-second range. They also had more variability in estimating the duration of stimuli lasting several seconds. Moreover, they showed deficits in time estimation and time production accuracy, indicative of an accelerated internal clock. Additional deficits in individual with ADHD were also found in the time reproduction paradigm, involving attentional (slower counting at short time intervals due to distraction) and motivational (faster counting at long time intervals due to increased delay aversion) functions. CONCLUSION/CONCLUSIONS:There is meta-analytic evidence of a broad range of timing deficits in individuals with ADHD. Results have implications for advancing our knowledge in the field (e.g., for refinement of recent timing models in ADHD) and clinical practice (e.g., testing timing functions to characterize the clinical phenotype of the patient and implementation of interventions to improve timing abilities).

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 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.

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.

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.