Faculty Bibliography

Increasing reports of long-term symptoms following COVID-19 infection, even among mild cases, necessitate systematic investigation into the prevalence and type of lasting illness. Notably, there is limited data regarding the influence of social determinants of health, like perceived discrimination and economic stress, that may exacerbate COVID-19 health risks. Here, 1,584 recovered COVID-19 patients that experienced mild to severe forms of disease provided detailed medical and psychosocial information. Path analyses examined hypothesized associations between discrimination, illness severity, and lasting symptoms. Secondary analyses evaluated sex differences, timing of infection, and impact of prior mental health problems. Post hoc logistic regressions tested social determinants hypothesized to predict neurological, cognitive, or mood symptoms. 70.6% of patients reported presence of one or more lasting symptom after recovery. 19.4% and 25.1% of patients reported lasting mood or cognitive/memory problems. Perceived discrimination predicted increased illness severity and increased lasting symptom count, even when adjusting for sociodemographic factors and mental/physical health comorbidities. This effect was specific to stress related to discrimination, not to general stress levels. Further, patient perceptions regarding quality of medical care influenced these relationships. Finally, illness early in the pandemic is associated with more severe illness and more frequent lasting complaints. Lasting symptoms after recovery from COVID-19 are highly prevalent and neural systems are significantly impacted. Importantly, psychosocial factors (perceived discrimination and perceived SES) can exacerbate individual health risk. This study provides actionable directions for improved health outcomes by establishing that sociodemographic risk and medical care influence near and long-ranging health outcomes. All data from this study have been made publicly available.

INTRODUCTION/BACKGROUND:Varying public views on cannabis use across countries may explain the variation in the prevalence of use, policies and research in individual countries, and global regulation of cannabis. This paper aims to describe the current state of cannabis use, policies, and research across sixteen countries. METHODS:PubMed and Google Scholar were searched for published studies from 2010 to 2020. Searches were conducted by using the relevant country of interest as a search term (e.g. "Iran"), as well as relevant predefined keywords such as "cannabis", "marijuana", "hashish", "bhang "dual diagnosis", "use", "addiction", "prevalence", "co-morbidity", "substance use disorder", "legalization" or "policy" (English and non-English). These keywords were used in multiple combinations to create the search string in studies records' titles and abstracts. Official websites of respective governments and international organizations were also searched in English and non-English (national language country) languages to identify the current state of cannabis use, policies, and research in each of those countries. RESULTS:Inconsistent and heterogeneous reporting of cannabis use, variation in policies (e.g., legalization), and intervention strategies across the reviewed countries were the main findings. European countries have dominated cannabis research output in PubMed, as compared to Asian countries (Thailand, Malaysia, India, Iran and Nepal). CONCLUSIONS:Although global cannabis regulation is ongoing, the existing heterogeneities across countries in terms of policies and epidemiology can increase the burden of cannabis use disorders disproportionately and unpredictably. There is an urgent need to develop global strategies to address these cross-country barriers to improve early detection, prevention, and interventions for cannabis use and related disorders.

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 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 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.

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.