Browse wide-ranging research at the frontiers of neuroscience supported by Wu Tsai Neurosciences Institute grants, awards, and training fellowships.
Projects
Investigating severe traumatic brain injury using a novel human CSF cell-free mRNA gene panel
This team aims to be the first to study the cellular and molecular impact of traumatic brain injury by studying genetic material in human cerebrospinal fluid. This will help clinicians and researchers ID markers of brain resilience after injury, and ultimately improve treatment for severe TBI.
High-speed force probes for deconstructing the biophysics of mechanotransduction
The purpose of this collaborative project is to study neuronal mechanisms associated with social stress. In particular we will test whether the energy producing systems, known as mitochondria, in a specific set of brain cells are important to confer resilience to stressful stimuli. This research may lead to treatments of stress and anxiety disorders.
High-speed nanomechanical probing of auditory mechano-sensitive cells
Our ability to detect and interpret sounds relies on specialized sensory cells within the snail-shaped hearing organ of the inner ear—the cochlea. These hair cells sense physical movement and then convert that mechanical stimulus into a biological signal that we perceive as sound. These mechano-sensory cells perform this task within microseconds and can do so for sub-nanomechanical stimuli.
Quantitative imaging for multi-scale modeling of neurological diseases
My proposed visit to the Van De Ville lab is centered on the idea to expand our methods beyond brain tumors to other neurological diseases using the Van De Ville lab’s expertise in neuro-imaging. Imaging genomics has been focused mainly on oncology; however, other neurological diseases can be studied in the same way.
Improve reproducibility and transparency in the field of neuroimaging by applying nonparametricstatistical methods and writing R packages.
Brain data analyses involves many steps and every step is prone to errors and uncertainties. Ignoring uncertainties can potentially leading to overconfident conclusions. To improve reproducibility it is important to propagate errors throughout the anlaysis.
Biologically plausible neural algorithms for learning structured sequences
Humans naturally learn to generate and process complicated sequential patterns. For example, a concert pianist can learn an enormous repertoire of memorized music. In neuroscience, it is widely thought that synaptic plasticity – the process by which the connections between neurons change response to experience – underlies such remarkable behavior.
Answering research questions in neural control through crowdsourced challenges
Human movement results from the coordination of muscles, tendons, joints, and other physiological elements.
Novel haptic interfaces for studying human perception in virtual environments
Modelling the Pupil Light Reflex for Non-Image Forming Vision
Although you’re aware of the light that you see, light also affects us in ways that you might not appreciate. These so called “non-image forming” (NIF) pathways were recently discovered, they start in the human eye before projecting to over a dozen brain regions. They modulate aspects of human function including our daily rhythms, our sleep patterns, the way we feel and the way we think.
Controlling schistosomiasis via CRISPR/CAS9-mediated gene drive
Schistosomiasis is a parasitic disease second only to malaria in its human health and economic impact on tropical nations.
Predicting and promoting resilient brain aging trajectories
Using new animal models such as the African killifish, this team aims to develop approaches to predict individual brain aging trajectories early in life based on behaviors that can be modulated to promote healthy memory, executive function and processing speed as well as counter dementia.
Resilience to Synaptic Impairments in Neurodegenerative Disorders
This team will explore the idea that neurotoxic protein aggregates seen in neurodegenerative disorders act at the synaptic connections between cells, and that resilience against these disorders may come from natural synapse-supporting factors that could be transformed into new forms of therapy.
Preserving motor engrams in Parkinson's disease: Neural circuit and transcriptomic studies and strategies for resilient motor control
This team aims to better understand how Parkinson's disease attacks the brain's basic motor programs and to spawn novel therapies against the disease using gene-editing technology.
Mitochondrial DNA and Brain Resilience
This team proposes the first comprehensive study of how mitochondrial DNA is related to cognitive function and susceptibility to dementia in a diverse population of over 11,000 adults. The outcomes of this study will provide insight into possible racial disparities in brain health.
Sleep circuits in neurodegenerative disease and aging
This team plans to study whether changes in neurons in the midbrain that regulate sleep, wakefulness, and immunity could contribute to aging and neurodegeneration. If successful, this information could rescue deficits in sleep and restore a normal immune profile.
Defining the Subcellular Biology of Brain Aging and Neurodegeneration
This team plans to map how age-related dysfunction of cellular waste disposal in lysosomes could lead to neurodegenerative diseases, potentially laying the foundation for a map of organelle function in the brain.
Unlocking brain resilience with HDAC inhibition
This team aims to define a network of genes that contribute to stress resistance in neurons and identify how it could be activated to enhance brain resilience and protect against neurodegenerative disease.
Endocannabinoid metabolism as a driver of brain aging
This team aims to discover whether the brain’s endocannabinoid system is dysregulated during aging, triggering inflammation via molecules called prostaglandins. If so, a drug that decouples these systems might restore a youthful brain state and rescue cognitive function.
Characterizing the Genetic Architecture of Neuropathology with Machine Learning
This team will study the brains of individuals who lived past ninety with their cognitive function intact, using advanced tissue imaging and computer science to understand mechanisms of resilience that could slow neurodegeneration and preserve brain health.