A5008467091- Neural dynamics and brain function
- Advanced Memory and Neural Computing
- Neuroscience and Neural Engineering
- Birth, Development, and Health
- Epigenetics and DNA Methylation
- Maternal Mental Health During Pregnancy and Postpartum
- Neural Networks and Applications
- Obsessive-Compulsive Spectrum Disorders
- Ocular Oncology and Treatments
- Acute Myeloid Leukemia Research
- Tryptophan and brain disorders
- Cell Image Analysis Techniques
- Cancer-related Molecular Pathways
- Neuroscience, Education and Cognitive Function
- Neuroscience and Neuropharmacology Research
- EEG and Brain-Computer Interfaces
- Bipolar Disorder and Treatment
- Retinoids in leukemia and cellular processes
- Grief, Bereavement, and Mental Health
- stochastic dynamics and bifurcation
- Neuroendocrine regulation and behavior
- Neonatal and fetal brain pathology
- Functional Brain Connectivity Studies
- Genetic Associations and Epidemiology
- Substance Abuse Treatment and Outcomes
University of Pennsylvania
2019-2021
Johns Hopkins Medicine
2016-2020
Johns Hopkins University
2014-2020
Alcohol use disorder (AUD) is a common and chronic with substantial effects on personal public health. The underlying pathophysiology poorly understood but strong evidence suggests significant roles of both genetic epigenetic components. Given that alcohol affects many organ systems, we performed cross-tissue cross-phenotypic analysis genome-wide methylomic variation in AUD using samples from 3 discovery, 4 replication, 2 translational cohorts. We identified differentially methylated region...
Accumulating evidence implicates the potassium voltage-gated channel, KQT-like subfamily, member 2 and 3 (KCNQ2 KCNQ3) genes in etiology of bipolar disorder (BPD). Reduced KCNQ2 or KCNQ3 gene expression might lead to a loss inhibitory M-current an increase neuronal hyperexcitability disease. The goal present study was evaluate epigenetic associations with BPD.DNA methylation levels alternative transcripts capable binding ankyrin G (ANK3) were evaluated using bisulfite pyrosequencing...
Physiological experiments have highlighted how the dendrites of biological neurons can nonlinearly process distributed synaptic inputs. However, it is unclear aspects a dendritic tree, such as its branched morphology or repetition presynaptic inputs, determine neural computation beyond this apparent nonlinearity. Here we use simple model where dendrite implemented sequence thresholded linear units. We manipulate architecture to investigate impacts binary branching constraints and inputs on...
Physiological experiments have highlighted how the dendrites of biological neurons can nonlinearly process distributed synaptic inputs. This is in stark contrast to units artificial neural networks that are generally linear apart from an output nonlinearity. If dendritic trees be nonlinear, may far more computational power than their counterparts. Here we use a simple model where dendrite implemented as sequence thresholded units. We find such readily solve machine learning problems, MNIST...
Neuroscientists fit morphologically and biophysically detailed neuron simulations to physiological data, often using evolutionary algorithms. However, such gradient-free approaches are computationally expensive, making convergence slow when models have many parameters. Here we introduce a gradient-based algorithm differentiable ODE solvers that scales well high-dimensional problems. GPUs make parallel fast gradient calculations optimization efficient. We verify the utility of our approach...