Browse wide-ranging research at the frontiers of neuroscience supported by Wu Tsai Neurosciences Institute grants, awards, and training fellowships.
Projects
Restoring vision with epiretinal prostheses
Millions of people are blind, yet we still don’t have the technology to satisfactorily restore vision. I aim to create a prosthetic device to do so. This device can be implanted in the eyes of a blind patient, resting on a tissue layer called the retina.
Improving BCI generalizability with multi-task modeling and autocalibration
Brain-computer interfaces (BCIs) are systems that enable using neural activity to control and interact with external devices. For people who lose the ability to move or speak due to injury or disease, BCIs provide a potential avenue to restore this loss of function.
Using the N400 component to examine variation in monolingual and bilingual language processing
This team aims to understand differences in language processing between bilingual and monolingual speakers and how these differences contribute to neuroplasticity. Their Koret project will use EEG to discover how semantic predictions are formed and whether knowledge of multiple languages influences these predictions.
Vitruvius interface: Augmenting designer with real-time neurocognitive feedback
In this highly interdisciplinary project, PhD candidate Alberto Tono is pursuing the novel application of combined EEG and immersive reality to streamline workflows in building design and construction.
The contribution of temporal dynamics of visual processing to developmental dyslexia: a steady-state visual evoked potential (SSVEP) study
Fang Wang has been developing novel steady-state EEG techniques to reveal the underlying neural dynamics involved in the acquisition of reading skills in children. She will use the Koret award to extend her findings in typically developing children to children with dyslexia, illustrating how cortical challenges in the temporal dynamics of visual processing can contribute to dyslexia.
Massively parallel microwire arrays for deep brain stimulation
Stanford NeuroTechnology Initiative (Phase 2)
Our goal is to develop the next generation of neural interfaces that match the resolution and performance of the biological circuitry. We will focus on two signature efforts to spearhead the necessary advances: high-density wire bundles for electrical recording and stimulation, and analog and digital bi-directional retinal prostheses for restoration of vision.
The NeuroFab: The hub for new ideas in neuro-engineering
Creating an incubator for next-generation neural interface platforms.
Brain-machine interfaces: Science, engineering, and application
Developing technology to interface with the brain and create intelligent prosthetics.
Understanding a complete neural computation in the primate visual system
Understanding the brain requires understanding how the neurons that constitute it perform computations, and how those computations relate to human behavior.
Investigation of synapse formation by novel nanoscale imaging techniques
Synaptic junctions linking individual neurons constitute the fundamental building blocks of our brain. Understanding their inner working is crucial to unravel the mechanisms by which our brain processes information. However, imaging structures at a relevant sub-synaptic level is challenging and has often hampered advances in neuroscience.
Enabling cell-based therapy of spinal cord injury through injectable hydrogels
Spinal cord injury (SCI) causes permanent damage to about 12,000 new patients in the US each year, primarily young adults. A common result of SCI is paralysis, and unfortunately, less than 1% of SCI patients have full neurological recovery by the time of hospital discharge.
Geometric analysis and variability mapping in human white matter brain structures
Understanding the relationship between structure and function in the human brain is a key interest in neuroscience. In recent years the focus is turning to understanding the role of the white matter in human cognition, brain function and neurological disorders.
Understanding cellular responses induced by chronic implantation of electrodes using a novel human neural differentiation platform
Electrodes implanted in the brain have great potential, with applications in neurodegenerative disease, brain-computer interfaces, and more. However, the presence of electrodes in brain tissue causes a response known as gliosis, in which a scar forms around the electrode, reducing its effectiveness and access to neurons.
Modeling proprioceptive deficits for the design of novel sensory augmentation for post-stroke movement rehabilitation
Stroke is the main cause of adult disability; 80% of survivors sustain motor (movement) deficits that interfere with activities of daily living. There exists no proven therapeutic strategy for motor recovery of the upper extremity following stroke.
Neural mechanisms of learning multiple motor skills and implications for motor rehabilitation
A hallmark of the motor system is its ability to execute different skilled movements as the situation warrants, thanks to the flexibility of motor learning. Despite many behavioral studies on motor learning, the neural mechanisms of motor memory formation and modification remain unclear.
Engineering versatile deep neural networks that model cortical flexibility
In the course of everyday functioning, animals (including humans) are constantly faced with real-world environments in which they are required to shift unpredictably between multiple, sometimes unfamiliar, tasks. But how brains support this rapid adaptation of decision making schema, and how they allocate resources towards learning novel tasks is largely unknown both neuroscientifically and algorithmically.
Enabling faster and more responsive voltage imaging through computational biophysics
Remote and localized neural activation using sonomagnetic stimulation
The neural prosthetics translational laboratory
Discovering new volitionally-controllable neural degrees-of-freedom for neural prostheses
A top priority for people with paralysis is reach and grasp ability. Technologies such as robotic arm prostheses or electrically stimulating paralyzed muscles can meet this need. Existing methods rely on the remaining muscles, are unintuitive and require laborious sequences of simple commands. Reading out a patient’s desired movement directly from their brain could overcome these limitations.
Deep brain microstimulation for memory recovery
Yi Lui's project aims to use deep brain microstimulation (DBMS), which causes even less brain damage and has higher spatial resolution than DBS, for memory recovery.
Synaptic rules and circuit architectures for learning from feedback
Dr. Brandon Jay Bhasin will use engineering principles from modern control theory, experimental neuroscience and computational neuroscience to significantly advance understanding of how feedback driven plasticity in a tractable neural circuit is orchestrated across multiple synaptic sites and over various timescales so that circuit dynamics are changed to improve performance.