- All
- Predoctoral Trainees
- Post-Doctoral Fellows
- TNT Former Scholar
My long-term research interests involve understanding behavioral and cognitive deficits in rodent models of Parkinson’s disease. My goal is to unravel the neuronal circuits that correlate these behaviors and use that knowledge to develop treatments for this debilitating disease. The behavioral deficits associated with Parkinson’s disease is widely studied so I would like to shed some light on the lesser known, but still just as harmful, cognitive deficits that seems to be an understudied part of the disease. I hope that my work will be relevant to the growing body of knowledge in cognitive deficits in Parkinson’s disease and will lay novel and impactful groundwork for current and future investigators.
Mentor: William Zeiger, M.D., Ph.D.
Jonathan’s research is focused on peripheral nerve stimulation—specifically vagus nerve stimulation. Studying the mechanisms and modulation techniques of peripheral nerves is a logical precursor to studying the brain, since signals in nerves are much more predictable and easy to study. Jonathan is developing novel stimulation techniques to improve state-of-the-art vagus nerve stimulation, with the intention of translating those techniques to brain stimulation as our knowledge grows.
Mentor: Wentai Liu, Ph.D.
My research interests are focused on achieving a systems-level understanding of behavioral deficits in mouse models of autism and neural circuit mechanisms involved in these behaviors. More specifically, I am interested in behavioral deficits associated with social touch and how network activity in cortical and subcortical brain regions is modulated by social touch in mouse models of autism.
Mentor: Carlos Portera-Cailliau, M.D., Ph.D.
I’m interested in the entorhinal cortical dynamics that drive working memory, temporal processing, and non-spatial sensory encoding. I am developing applications for the newest technological advancements in optogenetics, 2-photon calcium imaging, and miniature microscopes in rodent models.
Mentor: Peyman Golshani, M.D., Ph.D.
Ebrahim Feghhi is a PhD student in the Neuroscience IDP program. He is interested in creating computational models that match human neural activity and behavior, specifically in the domain of language. Outside of research, he enjoys practicing Brazilian Jiu-Jitsu and reading.
Mentor: Jonathan Kao, Ph.D.
Jay records human intracranial activity and physiological markers of arousal during immersive virtual reality experiences to understand the neural network dynamics that mediate threat processing and response. Using state-of-the-art computational methods, Jay hopes to identify neurophysiological signatures of inappropriate fear reactivity that can be used as targets for deep brain stimulation treatment of Post-Traumatic Stress Disorder.
Mentors: Nanthia Suthana, Ph.D.
Neural mechanisms of memory consolidation during sleep and the development of new technologies that leverage knowledge of sleep’s unique attributes to improve learning, memory, and the generation of insights.
Mentor: Gina Poe, Ph.D.
As a Ph.D. candidate in Mechanical Engineering, my research focuses on the vital role of cerebrospinal fluid (CSF) and glymphatic flow in maintaining brain health and function. CSF acts as a protective cushion for the brain, absorbing shocks and reducing the risk of injury, while also playing a crucial role in waste removal by transporting metabolic byproducts and toxins away from the brain. The glymphatic system enhances this waste removal by facilitating the clearance of harmful proteins, such as beta-amyloid, which are linked to neurodegenerative diseases like Alzheimer’s. My research focuses on exploring the mechanisms of fluid, particle, and ion transport within the glymphatic system, as well as investigating the effect of external factors, such as head impact, on the CSF flow. By integrating cutting-edge engineering approaches with bioscience and clinical research, I aim to advance our understanding of brain health and develop innovative solutions. Additionally, I incorporate data science techniques to combine numerical modeling and experimental data, enhancing the accuracy and applicability of the findings for translational research in neurological disorders.
Mentor: Mayumi Prins, Ph.D.
I am interested in using neuromodulating technologies, such as transcranial magnetic stimulation (TMS), to treat traumatic brain injuries. We are testing whether TMS can reset frontoamygdala circuitry to extinguish fear avoidance behavior, autonomic reactivity, and sleep disturbances that prolong symptoms after concussion. Using machine learning, in the largest study of its kind with the most continuous data, I will develop an algorithm that uses at-home measures of autonomic function (heart rate variability (HRV), heart rate, respiratory rate, oxygenation, and sleep/rest temperature) from the Oura Ring to predict in-lab autonomics (HRV and pupillary dynamics before, during, and after TMS and an exposure task as well as central autonomic activity in fMRI). I will develop a software that transforms consumer-based wearable data into biomarkers to predict concussion recovery and guide treatment for patients with prolonged symptoms.
Mentor: Kevin Bickart, M.D., Ph.D.
My research goal is to establish novel neuro-rehabilitation devices and therapies that are affordable and accessible by any patient. To achieve that goal, I am interested in the cellular and molecular mechanisms underlying the therapeutic effect of neuromodulations in patients with spinal cord injury. To be more specific, I am utilizing a comprehensive set of biological (opto-/ chemogenetics, electrophysiology and single nucleus RNA sequencing), engineering (signal processing and electrode fabrication), and computational (machine learning) tools to investigate the short-term and long-term changes of spinal circuit induced by the electrical epidural stimulation.
Mentor: Daniel Lu, M.D., Ph.D
My research interests are in applying brain imaging to TMS treatment to find biomarkers for the aid of treatment. Specifically I want to find a way of utilizing resting state functional MRI data to determine both the best area for treatments in specific populations and improve individual based treatments by finding biomarkers that correlate with participant improvement. My current research involves applying these methods to Smoking populations and using fMRI & TMS to reduce smoking withdrawal symptoms.
Mentor: Nicole Petersen, Ph.D.
As a National Science Foundation funded student, I work on developing novel microscopy techniques to probe multisensory integration in the Drosophila Melanogaster brain. Similar to the mammalian hippocampus, the central complex may serve as a critical indexing and integration site to coordinate spatial navigation. Building off my previous work on the UCLA Miniscope Project, I will refine a new two-photon microscope capable of patterned optogenetic stimulation in fruit flies. I hope to manipulate the neural circuits that coordinate synaptic plasticity in the central complex to reveal how vision, odor, and atmospheric polarized light integrate so that flies may produce complex navigation paths while traversing the earth.
Mentor: Mark Frye, Ph.D.
I’m interested in how the brain processes reward in both direct and vicarious experiences, and in particular, how these processes may alter one’s neural representations of the environment. My research approach will incorporate recordings of human intracranial activity and physiological markers of arousal as participants either ambulate freely or remain stationary during immersive augmented reality experiences.
Mentor: Nanthia Suthana, Ph.D.
Sam is a Ph.D. student in the Bioengineering Department at the University of California, Los Angeles. He received his M.S. degree from UCLA in bioengineering with a specialization in NeuroEngineering in 2023. He previously attended Azusa Pacific University where he played collegiate football and received a B.S. in Systems Engineering in 2019. His current research with the Brain Injury Research Center at UCLA focuses on the system design of a synchronous behavioral and functional ultrasound imaging platform to acquire information about functional network connectivity changes after traumatic brain injury. His research interests include computational neuroscience, machine learning, and graph theory to understand plasticity and working memory in the whole brain. He previously worked as an electrical engineer at Raytheon Technologies from 2019 to 2021 where he automated the testing of various satellite modules. Outside of research, he enjoys going to the gym, reading, and spending time with friends and family.
Mentor: Paul Mathews, Ph.D.
I am interested in how the brain encodes episodic memories, particularly the contextual and spatial features of an experience, and how the neural substrates of memory and spatial encoding remap across different experiences. My research approach involves recording single-unit and intracranial oscillatory electrophysiology in human participants performing virtual and augmented reality tasks, both while ambulating freely and while remaining stationary.
Mentor: Nanthia Suthana, Ph.D
Integrated software platform for healthcare applications. Application Programming Interface and Graphical User Interface for healthcare systems. Online data process optimization and acceleration.
Mentor: Dejan Markovic, Ph.D.
I study how the human brain controls gait and balance while navigating the world around us. Using immersive virtual reality to simulate real-world scenarios, I examine how intracranial and scalp electrophysiology signals can predict the motor behaviors that keep the body upright and moving. I aim to leverage these neural markers to guide rehabilitation strategies for improving gait function in neurological populations at risk for falls.
Mentor: Katy Cross, M.D., Ph.D.
I’m interested in using deep learning to improve patient outcomes and to further our understanding of neural processes and brain physiology. Currently, I am exploring how different deep learning approaches can be used to improve BCIs for motor imagery, as well as how we might elucidate neural mechanisms of pediatric epilepsy and gait freezing in Parkinson’s disease.
Mentor: William Speier, Ph.D.
My research combines insights from neuroscience, psychology, and computer science to understand human learning and memory. I am interested in how the brain supports working memory and context-dependent statistical learning where temporal regularities are consistent within an environment but interfere between environments. I use machine learning algorithms to relate brain activity to behavioral measures, and I model behavioral results with neural networks.
Mentor: Jesse Rissman, Ph.D.
Jihye’s research interest broadly centers on agency – specifically, on how an individual obtains a sense of control over one’s body, and thus establish a sense of self. She approaches this question from an embodied perspective, where different layers of the nervous systems interact with one another in a complex manner to produce behaviors at will.
Mentor: Ausaf Bari, M.D., Ph.D., and Nanthia Suthana, Ph.D.
My name is Ricky Savjani, a resident physician in the Department of Radiation Oncology at UCLA. My research interests lie in leveraging population inferences to understand the underpinnings of human cognition and to better guide oncological care for cancer patients. This also includes functional sparing and optimal delivery of radiation to the brain to minimize toxicity and cognitive impairments. I am interested in functional and structural neuroimaging using MRI to tackle these challenges. Additionally, I am interested in AI, brain brachytherapy, and functional radiosurgery. I am thrilled to be able to participate in the UCLA TNT program to turn ideas into technologies to optimize individual patient care.
Mentor: Daniel Low, Ph.D.
Norman Spivak is an MD/PhD student at the University of California Los Angeles (UCLA), where he is conducting research on low-intensity focused ultrasound neuromodulation for applications in psychiatry and neurosurgery. His work has included the development of clinical trials investigating the technology for treating disorders of consciousness and generalized anxiety.
Mentor: Martin Monti
I study the differential contribution of cell-types in the mouse medial prefrontal cortex to the brain’s encoding of task-relevant information during adaptive decision-making. By comparing neural activity from mice with recordings from humans during a similar task, I hope to gain insight into the roles discrete neuron types play during cognitive tasks in humans.
Mentor: Peyman Golshani, M.D., Ph.D.
My research combines animal models with electrophysiology and chemogenetics to investigate the neural signatures of Parkinson’s disease and Levodopa-induced dyskinesia. Specifically, I am interested in identifying causal patterns of electrical activity in the frontocoritcal regions that are associated with the cognitive impairments of Parkinson’s disease, with the ultimate goal of using these neural signatures as novel therapeutic targets.
Mentor: Alicia Izquierdo, Ph.D.
Memory is an active process that allows for the recall of previous experiences, shaping how we interpret the present moment and plan future behavior. My research seeks to understand the mechanisms and function of how memories organize and reorganize in the brain across time. To achieve this, I use a combination of techniques from molecular, systems, and behavioral neuroscience within a rodent model system and classical fear memory paradigms.
Mentor: Laura DeNardo, Ph.D.