Resting state EEG source derived salience network theta connectivity mediates anxiety in community dwelling individuals reporting childhood trauma.

Childhood trauma (CT) has been consistently linked with etiology of anxiety and depression. Finding biomarkers that mediate the relationship between CT and psychopathology is important and electroencephalography (EEG) can be a useful and cost-effective tool serving this purpose. Hence, in the current research we investigated resting state EEG biomarkers associated with CT and how these may link to psychopathology of anxiety and depression in adults.

Novel Technologies to Address the Lower Motor Neuron Injury and Augment Reconstruction in Spinal Cord Injury.

Lower motor neuron (LMN) damage results in denervation of the associated muscle targets and is a significant yet under-appreciated component of spinal cord injury (SCI). Denervated muscle undergoes a progressive degeneration and fibro-fatty infiltration that eventually renders the muscle non-viable unless reinnervated within a limited time window. The distal nerve deprived of axons also undergoes degeneration and fibrosis making it less receptive to axons.

Methylphenidate, but not citalopram, decreases impulsive choice in rats performing a temporal discounting task.

Introduction: Drugs targeting monoamine systems remain the most common treatment for disorders with impulse control impairments. There is a body of literature suggesting that drugs affecting serotonin reuptake and dopamine reuptake can modulate distinct aspects of impulsivity - though such tests are often performed using distinct behavioral tasks prohibiting easy comparisons.

Methods: Here, we directly compare pharmacologic agents that affect dopamine (methylphenidate) vs serotonin (citalopram) manipulations on choice impulsivity in a temporal discounting task where rats could choose between a small, immediate reward or a large reward delayed at either 2 or 10s.

Personalized Machine Learning-Based Prediction of Wellbeing and Empathy in Healthcare Professionals.

Healthcare professionals are known to suffer from workplace stress and burnout, which can negatively affect their empathy for patients and quality of care. While existing research has identified factors associated with wellbeing and empathy in healthcare professionals, these efforts are typically focused on the group level, ignoring potentially important individual differences and implications for individualized intervention approaches. In the current study, we implemented N-of-1 personalized machine learning (PML) to predict wellbeing and empathy in healthcare professionals at the individual level, leveraging ecological momentary assessments (EMAs) and smartwatch wearable data.

Predicting non-response to ketamine for depression: An exploratory symptom-level analysis of real-world data among military veterans.

Ketamine helps some patients with treatment resistant depression (TRD), but reliable methods for predicting which patients will, or will not, respond to treatment are lacking. Herein, we aim to inform prediction models of non-response to ketamine/esketamine in adults with TRD. This is a retrospective analysis of PHQ-9 item response data from 120 patients with TRD who received repeated doses of intravenous racemic ketamine or intranasal eskatamine in a real-world clinic.

Behavioral Interventions Can Improve Brain Injury-Induced Deficits in Behavioral Flexibility and Impulsivity Linked to Impaired Reward-Feedback Beta Oscillations.

Traumatic brain injury (TBI) affects a large population, resulting in severe cognitive impairments. Although cognitive rehabilitation is an accepted treatment for some deficits, studies in patients are limited in ability to probe physiological and behavioral mechanisms. Therefore, animal models are needed to optimize strategies.

COVID-19 Vaccination and Gout Flare Risk in Patients With Infrequent or Frequent Flares: A Prospective Cohort Study.

Objective: To assess post-COVID-19 vaccination gout flare risk with differing baseline flare burden.

Methods: We prospectively studied gout patients with infrequent or frequent flares, defined as ≤1 flare/year or ≥2 flares/year, respectively. COVID-19 vaccine-naive patients managed with urate-lowering therapy between February and June 2021 were included and voluntarily decided on vaccination.

A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs.

Human cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model.

Parietal alpha underlies slower cognitive responses during interference processing in adolescents.

Adolescence is a critical period when cognitive control is rapidly maturing across several core dimensions. Here, we evaluated how healthy adolescents (13-17 years of age, n = 44) versus young adults (18-25 years of age, n = 49) differ across a series of cognitive assessments with simultaneous electroencephalography (EEG) recordings. Cognitive tasks included selective attention, inhibitory control, working memory, as well as both non-emotional and emotional interference processing.

Distinct neural activations correlate with maximization of reward magnitude versus frequency.

Choice selection strategies and decision-making are typically investigated using multiple-choice gambling paradigms that require participants to maximize expected value of rewards. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains such that users often choose smaller frequent gains over larger rarely occurring gains, also referred to as melioration. To understand the basis of this subjective tradeoff, we used a simple 2-choice reward task paradigm in 186 healthy human adult subjects sampled across the adult lifespan.

EEG source derived salience network coupling supports real-world attention switching.

While the brain mechanisms underlying selective attention have been studied in great detail in controlled laboratory settings, it is less clear how these processes function in the context of a real-world self-paced task. Here, we investigated engagement on a real-world computerized task equivalent to a standard academic test that consisted of solving high-school level problems in a self-paced manner. In this task, we used EEG-source derived estimates of effective coupling between brain sources to characterize the neural mechanisms underlying switches of sustained attention from the attentive on-task state to the distracted off-task state.

Simultaneous Gut-Brain Electrophysiology Shows Cognition and Satiety Specific Coupling.

Recent studies, using high resolution magnetoencephalography (MEG) and electrogastrography (EGG), have shown that during resting state, rhythmic gastric physiological signals are linked with cortical brain oscillations. Yet, gut-brain coupling has not been investigated with electroencephalography (EEG) during cognitive brain engagement or during hunger-related gut engagement. In this study in 14 young adults (7 females, mean ± SD age 25.

Neural dynamics during emotional video engagement relate to anxiety.

Inter-subject correlations (ISCs) of physiological data can reveal common stimulus-driven processing across subjects. ISC has been applied to passive video viewing in small samples to measure common engagement and emotional processing. Here, in a large sample study of healthy adults ( = 163) who watched an emotional film (The Lion Cage by Charlie Chaplin), we recorded electroencephalography (EEG) across participants and measured ISC in theta, alpha and beta frequency bands.

Utility of Cognitive Neural Features for Predicting Mental Health Behaviors.

Cognitive dysfunction underlies common mental health behavioral symptoms including depression, anxiety, inattention, and hyperactivity. In this study of 97 healthy adults, we aimed to classify healthy vs. mild-to-moderate self-reported symptoms of each disorder using cognitive neural markers measured with an electroencephalography (EEG).

Circadian rhythm disruption in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Implications for the post-acute sequelae of COVID-19.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a common and disabling disorder primarily characterized by persistent fatigue and exercise intolerance, with associated sleep disturbances, autonomic dysfunction, and cognitive problems. The causes of ME/CFS are not well understood but may coincide with immune and inflammatory responses following viral infections. During the current SARS-CoV2 coronavirus pandemic, ME/CFS has been increasingly reported to overlap with persistent "long COVID" symptoms, also called the post-acute sequelae of COVID-19 (PASC).

Association of acidic urine pH with impaired renal function in primary gout patients: a Chinese population-based cross-sectional study.

Background: Patients with gout frequently have low urinary pH, which is associated with the nephrolithiasis. However, the specific distribution of urinary pH and potential relationship of acidic urine pH to broader manifestations of kidney disease in gout are still poorly understood.

Methods: A 2016-2020 population-based cross-sectional study was conducted among 3565 gout patients in the dedicated gout clinic of the Affiliated Hospital of Qingdao University to investigate the association between low urinary pH and kidney disease.

Personalized machine learning of depressed mood using wearables.

Depression is a multifaceted illness with large interindividual variability in clinical response to treatment. In the era of digital medicine and precision therapeutics, new personalized treatment approaches are warranted for depression. Here, we use a combination of longitudinal ecological momentary assessments of depression, neurocognitive sampling synchronized with electroencephalography, and lifestyle data from wearables to generate individualized predictions of depressed mood over a 1-month time period.

SimBSI: An open-source Simulink library for developing closed-loop brain signal interfaces in animals and humans.

Objective: A promising application of BCI technology is in the development of personalized therapies that can target neural circuits linked to mental or physical disabilities. Typical BCIs, however, offer limited value due to simplistic designs and poor understanding of the conditions being treated. Building BCIs on more solid grounds may require the characterization of the brain dynamics supporting cognition and behavior at multiple scales, from single-cell and local field potential (LFP) recordings in animals to non-invasive electroencephalography (EEG) in humans.

Mapping cognitive brain functions at scale.

A fundamental set of cognitive abilities enable humans to efficiently process goal-relevant information, suppress irrelevant distractions, maintain information in working memory, and act flexibly in different behavioral contexts. Yet, studies of human cognition and their underlying neural mechanisms usually evaluate these cognitive constructs in silos, instead of comprehensively in-tandem within the same individual. Here, we developed a scalable, mobile platform, "BrainE" (short for Brain Engagement), to rapidly assay several essential aspects of cognition simultaneous with wireless electroencephalography (EEG) recordings.

Measuring health related quality of life for dengue patients in Iquitos, Peru.

Previous studies measuring the health-related quality of life (HRQoL) of individuals with dengue focused on treatment seeking populations. However, the vast majority of global dengue cases are unlikely to be detected by health systems. Representative measurements of HRQoL should therefore include patients with disease not likely to trigger treatment-seeking behavior.

Exploration of metformin as novel therapy for osteoarthritis: preventing cartilage degeneration and reducing pain behavior.

Background: Metformin could activate adenosine monophosphate-activated protein kinase (AMPK) which was postulated as a potential therapeutic target for osteoarthritis. This study aimed to examine the effects of metformin on cartilage and pain in osteoarthritis mouse model.

Methods: Eighty 10-week-old male C57BL/6 mice were randomized to 6 groups: non-operation, sham-operation, destabilization of the medial meniscus (DMM)-operation with intragastric saline/metformin, and DMM-operation with intraarticular saline/metformin.

Respiratory regulation & interactions with neuro-cognitive circuitry.

It is increasingly being recognized that active control of breathing - a key aspect of ancient Vedic meditative practices, can relieve stress and anxiety and improve cognition. However, the underlying mechanisms of respiratory modulation of neurophysiology are just beginning to be elucidated. Research shows that brainstem circuits involved in the motor control of respiration receive input from and can directly modulate activity in subcortical circuits, affecting emotion and arousal.