Faculty Bibliography

Grid cells or grid-like responses have been reported in the rodent, bat and human brains during various spatial and non-spatial tasks. However, the functions of grid-like representations beyond the classical hippocampal formation remain elusive. Based on accumulating evidence from recent rodent recordings and human fMRI data, we make speculative accounts regarding the mechanisms and functional significance of the sensory cortical grid cells and further make theory-driven predictions. We argue and reason the rationale why grid responses may be universal in the brain for a wide range of perceptual and cognitive tasks that involve locomotion and mental navigation. Computational modeling may provide an alternative and complementary means to investigate the grid code or grid-like map. We hope that the new discussion will lead to experimentally testable hypotheses and drive future experimental data collection.

Objective/UNASSIGNED:Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods/UNASSIGNED:This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results/UNASSIGNED:The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions/UNASSIGNED:Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

Decisions under uncertainty can be differentiated into two classes: risky, which has known probabilistic outcomes, and ambiguous, which has unknown probabilistic outcomes. Across a variety of types of decisions, people find ambiguity extremely aversive, subjectively more aversive than risk. It has been shown that the transient sympathetic arousal response to a choice predicts decisions under ambiguity but not risk, and that lifetime stress uniquely predicts attitudes toward ambiguity. Building on these findings, this study explored whether we could bias ambiguity and risk preferences with an arousal or acute stress manipulation that is incidental to the choice in two independent experiments. One experiment induced sympathetic arousal with an anticipatory threat paradigm, and the other manipulated incidental acute stress via a psychosocial stressor. The efficacy of the manipulations was confirmed via pupil dilation and salivary cortisol, respectively. Participants made choices between a guaranteed $5 option and a lottery with either a known (risky) or unknown (ambiguous) probabilistic outcome. Consistent with previous findings, participants were more averse to a given level of ambiguity than to a numerically equal level of risk. However, in contrast to our hypothesis, we found no evidence that transient arousal or acute stress that is incidental to the choice biases ambiguity preferences.

Brain-derived Neurotrophic Factor (BDNF) binds to the TrkB tyrosine kinase receptor, which dictates the sensitivity of neurons to BDNF. A unique feature of TrkB is the ability to be activated by small molecules in a process called transactivation. Here we report that the brain neuropeptide oxytocin increases BDNF TrkB activity in primary cortical neurons and in the mammalian neocortex during postnatal development. Oxytocin produces its effects through a G protein-coupled receptor (GPCR), however, the receptor signaling events that account for its actions have not been fully defined. We find oxytocin rapidly transactivates TrkB receptors in bath application of acute brain slices of 2-week-old mice and in primary cortical culture by increasing TrkB receptor tyrosine phosphorylation. The effects of oxytocin signaling could be distinguished from the related vasopressin receptor. The transactivation of TrkB receptors by oxytocin enhances the clustering of gephyrin, a scaffold protein responsible to coordinate inhibitory responses. Because oxytocin displays pro-social functions in maternal care, cognition, and social attachment, it is currently a focus of therapeutic strategies in autism spectrum disorders. Interestingly, oxytocin and BDNF are both implicated in the pathophysiology of depression, schizophrenia, anxiety, and cognition. These results imply that oxytocin may rely upon crosstalk with BDNF signaling to facilitate its actions through receptor transactivation.

Recent advances in magnetic resonance imaging are enabling the efficient creation of high-dimensional, multiparametric images, containing a wealth of potential information about the structure and function of many organs, including the cardiovascular system. However, the sizes of these rich data sets are so large that they are outstripping our ability to adequately visualize and analyze them, thus limiting their clinical impact. While there are some intrinsic limitations of human perception and of conventional display devices which hamper our ability to effectively use these data, newer computational methods for handling the data may aid our ability to extract and visualize the salient components of these high-dimensional data sets.

Background/UNASSIGNED:African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW. Methods/UNASSIGNED:Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman's correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits. Results/UNASSIGNED:DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including self-disgust/self-hate (-0.13, 95% CI -0.26, -0.01); difficulty with making decisions (-0.15, 95% CI -0.28, -0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders. Conclusions/UNASSIGNED:Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.

The vast majority of extant vertebrate diversity lies within the bony and cartilaginous fish lineages of jawed vertebrates. There is a long history of elegant experimental investigation of development in bony vertebrate model systems (e.g., mouse, chick, frog and zebrafish). However, studies on the development of cartilaginous fishes (sharks, skates and rays) have, until recently, been largely descriptive, owing to the challenges of embryonic manipulation and culture in this group. This, in turn, has hindered understanding of the evolution of developmental mechanisms within cartilaginous fishes and, more broadly, within jawed vertebrates. The little skate (Leucoraja erinacea) is an oviparous cartilaginous fish and has emerged as a powerful and experimentally tractable developmental model system. Here, we discuss the collection, husbandry and management of little skate brood stock and eggs, and we present an overview of key stages of skate embryonic development. We also discuss methods for the manipulation and culture of skate embryos and illustrate the range of tools and approaches available for studying this system. Finally, we summarize a selection of recent studies on skate development that highlight the utility of this system for inferring ancestral anatomical and developmental conditions for jawed vertebrates, as well as unique aspects of cartilaginous fish biology.

The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.

The neurophysiological footprint of brain activity after cardiac arrest and during near-death experience (NDE) is not well understood. Although a hypoactive state of brain activity has been assumed, experimental animal studies have shown increased activity after cardiac arrest, particularly in the gamma-band, resulting from hypercapnia prior to and cessation of cerebral blood flow after cardiac arrest. No study has yet investigated this matter in humans. Here, we present continuous electroencephalography (EEG) recording from a dying human brain, obtained from an 87-year-old patient undergoing cardiac arrest after traumatic subdural hematoma. An increase of absolute power in gamma activity in the narrow and broad bands and a decrease in theta power is seen after suppression of bilateral hemispheric responses. After cardiac arrest, delta, beta, alpha and gamma power were decreased but a higher percentage of relative gamma power was observed when compared to the interictal interval. Cross-frequency coupling revealed modulation of left-hemispheric gamma activity by alpha and theta rhythms across all windows, even after cessation of cerebral blood flow. The strongest coupling is observed for narrow- and broad-band gamma activity by the alpha waves during left-sided suppression and after cardiac arrest. Albeit the influence of neuronal injury and swelling, our data provide the first evidence from the dying human brain in a non-experimental, real-life acute care clinical setting and advocate that the human brain may possess the capability to generate coordinated activity during the near-death period.

Spinal motoneurons are a remarkably diverse class of neurons responsible for facilitating a broad range of motor behaviors and autonomic functions. Studies of motoneuron differentiation have provided fundamental insights into the developmental mechanisms of neuronal diversification, and have illuminated principles of neural fate specification that operate throughout the central nervous system. Because of their relative anatomical simplicity and accessibility, motoneurons have provided a tractable model system to address multiple facets of neural development, including early patterning, neuronal migration, axon guidance, and synaptic specificity. Beyond their roles in providing direct communication between central circuits and muscle, recent studies have revealed that motoneuron subtype-specific programs also play important roles in determining the central connectivity and function of motor circuits. Cross-species comparative analyses have provided novel insights into how evolutionary changes in subtype specification programs may have contributed to adaptive changes in locomotor behaviors. This chapter focusses on the gene regulatory networks governing spinal motoneuron specification, and how studies of spinal motoneurons have informed our understanding of the basic mechanisms of neuronal specification and spinal circuit assembly.