Xue Han - US grants

Attention is highly critical tp our conscious experience. A failure to focus or to shift attention can be devastating, and may contribute to neurological and psychiatric diseases such as attention deficit hyperactivity disorder (ADHD), dyslexia, and schizophrenia. Experiments from the Desimone lab and others have shown that attention alters neural activity in many visual areas and synchronizes activity across brain regions. There is increasing evidence for the presence of top-down modulatory mechanisms mediating attention. However, the precise neural circuitry underlying these effects is largely unl

DESCRIPTION (provided by applicant): Parkinson's disease (PD) is a neurodegenerative disorder with a hallmark of dopamine neuron degeneration in the Substantia Nigra pars compacta (SNpc), resulting in cardinal motor dysfunctions: resting tremor, bradykinesia (slowness of voluntary movement), muscular rigidity, and gait instability. SNpc dopamine neurons project heavily to the striatum, the main input nucleus of the basal ganglia. Dopamine depletion is thought to shift the balance between two antagonistic striatal output pathways through distinct dopamine receptors on the two populations of projecting medium spiny neurons, which results in an overall reduction in the cortical control of motor functions. In addition, dopamine depletion results in an upregulation of cholinergic tone by modulating cholinergic interneurons, and the imbalanced dopamine-acetylcholine interaction has also been suggested to be critical in PD pathophysiology. Anti-cholinergic drugs, the only available drugs for PD before the development of levodopa treatment in the 1970s, remain to be in clinical use today. Newer therapies such as deep brain stimulation (DBS) highlight the fact that PD involves neural network pathology. Intracranial recordings in PD patients revealed exaggerated oscillations in the cortical-basal ganglion circuit at beta frequencies, 11-30 Hz. Exaggerated beta oscillations closely parallel key PD motor deficits, and are largely suppressed by effective dopamine replacement treatment or DBS. Together, these evidences established a clear link between beta oscillations within the cortical-basal ganglia-thalamic network and PD motor symptoms. However, it remains unknown whether the exaggerated beta oscillation is the cause or a correlate of motor deficits, and where and how beta oscillations arise in PD. Our previous studies combining mathematical and pharmacological approaches have demonstrated that the striatum neural network is capable of generating beta oscillations upon upregulation of striatal acetycholine. Here, we aim to test the novel hypothesis that cholinergic over-activation in the Parkinsonian striatum plays a key role in producing pathological beta oscillations, and beta oscillations play a causal role in PD motor pathology. This novel hypothesis directly links dopamine induced cholinergic malfunction to neural circuit pathology and motor deficits. Because of the explorative nature of this project, we feel that the R21 funding mechanism is most appropriate for this project at this stage. PUBLIC HEALTH RELEVANCE: Parkinson's disease, a neural degenerative disorder, affects over 1 million patients in the US alone, with more than 50,000 newly diagnosed patients each year. This research seeks to understand the neural network mechanisms of pathophysiology in Parkinson's disease.

DESCRIPTION (Provided by the applicant) Abstract: Precise spatiotemporal control of ligand delivery into intact cells, organs, and organisms is important for the time resolved and causal analysis of the functions of neurotransmitters, neuromodulators, and hormones in the operation of complex biological systems, such as the brain. Over the past several decades, some success has been achieved in uncaging several small molecules through the attachment of photolabile chemical groups, which block the bioactivity of the molecule in the absence of light and release a bioactive molecule upon UV light irradiation. However, such photochemical uncaging modifications are difficult to develop for small molecules, and are nearly impossible for large molecules whose active sites are often too large to be blocked by the addition of chemical groups. In addition, caged molecules often exert leak bioactivity even before light delivery, and the use of UV light can be damaging to cellular components; as a result, despite proven utility in vitro, uncaging has been little used in vivo to study intact biological systems. Here, I will describe a novel strategy capable of uncaging arbitrary bioactive molecules and peptides with millisecond time scale resolution, using visible light safe for in vivo use. I will use computational protein and DNA design to construct light controllable 'NanoRobots', and use these NanoRobots to uncage a variety of molecules, peptides, and proteins in the intact organ systems. Such a strategy has the potential to revolutionize the study of ligand functions with unprecedented spatiotemporal precision, opening up new frontiers in basic molecular and systems neuroscience, pharmaceutical development, and side effect assessment.

1264434
Rothschild

The research will involve three laboratories at the BU Photonics Center (Rothschild, Erramilli and Han) and utilize advanced spectroscopic and biophysical/bioengineering techniques along with collaborators at UC Davis Center for Biophotonics, MIT, Harvard University, and University of Texas. A central feature of the research will be the use of time-resolved FTIR difference spectroscopic, ultra-fast laser spectroscopy and confocal near-IR Raman techniques to measure molecular changes in optogenetic rhodopsins upon light excitation on a time-scale of seconds to femtoseconds. Preliminary work has demonstrated that a variety of optogenetic rhodopsins can be reconstituted into proteolipid membranes including nanolipidparticles and studied using advanced spectroscopic methods to obtain detailed molecular information about their function. In addition, spectroscopic studies have been extended to living cells allowing these proteins to be studied in their native environment in order to determine molecule effects of such factors as membrane potential. Collaborators on this project include: Dr. Ed Boyden at MIT, widely recognized as one of the co-founders of optogenetics and a leading developer of new neurophotonic technology; Dr. Matt Coleman at UCD, who has developed methods of expressing rhodopsins into nanolipidparticles (NLPs) and forming microcrystals suitable for coherent x-ray diffraction imaging (CXDI), Dr. John Spudich, at the U. Texas Med. School, a pioneer in the field of microbial rhodopsins and co-discoverer of channelrhodopsins and Dr. Adam Cohen, whose laboratory at Harvard University has recently demonstrated that rhodopsins can be used to monitor transmembrane voltage in living nerves.

DESCRIPTION (provided by applicant): In many subfields in neuroscience, neural circuits are thought of as primarily composed of neurons connected by chemical synapses. For example, connectomics is largely focused on locating chemical synaptic connections between neurons; imaging of neural communication through fluorescent tools is also largely focused on chemical synapses, and the vast majority of electrophysiology studies in vitro and in vivo focus on chemical synaptic transmission. However, another class of neural communication mechanism exists that could well govern how neurons work together in intact neural circuits to generate computations: electrical synapses, mediated by gap junction connections that directly electrically couple cells together. Pioneering studies have shown that chronic deletion of gap junction genes can alter hippocampal oscillatory dynamics that may be important for learning and epilepsy, change response of the brain to electrical neuromodulation therapies, alter neural migration and brain development. In astrocytes, gap junctions mediate inter-astrocyte calcium waves and glial communication, a process that might be compromised in psychiatric patients. In cell types outside the brain, genetic deletion of gap junctions can result in inner ear cell loss, and gap junctions are also implicated in retinal function. However, it remains impossible to inactivate gap junction functionality in a transient and reversible fashion, so that their roles ca be analyzed in a time-resolved fashion, i.e. at defined time points in behavioral tasks or during specific neural computation. Accordingly, we propose to develop a fully genetically encoded toolbox for controlling and observing gap junction functionality in defined cell types in neural networks.

? DESCRIPTION (provided by applicant): Multiphoton laser scanning microscopy has revolutionized neuroscience since it is less invasive than traditional electrophysiology methods for probing neuronal processes. In most cases, such imaging is limited to the observation of a single fluorescent species at modest depths (the depth penetration of standard 2-photon microscopy in brain tissue is limited a few 100s of microns). Recent proposals to extend this depth penetration have made use of 3-photon excitation. But to avoid heating due to water absorption, long wavelengths were employed, providing access to only deep red fluorescent markers. We propose to improve the versatility of multiphoton microscopy by enhancing its multiplexing capacity and its depth penetration. To do this, we will develop a novel laser design that can emit light at different colors simultaneously, that are chosen to enable 2- or 3-photon imaging using non-degenerate (as opposed to traditional degenerate) multiphoton imaging. The key novelty here is a tuneable laser that emits, on demand, a pair of colors across the wavelength ranges that avoid water absorption but whose multiple combinations of energies sum up to excite a variety of popular fluorescent sensors, such as channelrhodopsins, halorhodopsins, archearhodopsin, and GCaMPs etc, across the entire visible spectrum. Our laser's power and wavelengths will enable achieving deep tissue (up to ~2mm) imaging. Multiplexing will be performed by detecting fluorescence from all the non- degenerate multiphoton combinations available from our multicolour tunable high energy laser. We will demonstrate the proof-of-concept of multiplexed deep tissue imaging using labelled mouse-brain tissue. This would create an opportunity to image deep structures such as the thalamus and hippocampus (depth>1000 ?m) with minimal tissue damage, which have not been able to be achieved by current in vivo imaging methods. Success in proposed goals would create new avenues for neuroscience research, such as, for example, enabling imaging of large heterogeneous neuronal ensembles of transgenic mouse lines that can genetically label distinct neuronal populations, or facilitating circuit interrogation experiments involving glutamate uncaging that currently require multiple costly ultrafast lasers. Moreover, since the novel laser source is all-fiber in nature, the microscope is readily adaptable for facilitating future endoscopc in vivo imaging.

? DESCRIPTION (provided by applicant): Accumulating evidence suggests that neurogenesis continues in the adult mammalian hippocampus including that of humans, and is relevant for many cognitive behaviors. New neurons generated in the dentate gyrus area of the adult hippocampus mature into dentate granule cells and integrate into existing neural circuits. While adult born dentate granule cells (abDGCs) continue their morphological development for an extended period of time, there seems to be a transient maturation period when immature young abDGCs exhibit heightened membrane excitability and elevated synaptic plasticity. Recent studies through pharmacogenetics and optogenetic down regulation of adult neurogenesis have provided important insights on how a small population of abDGCs may exert specific behavioral influence, from spatial pattern separation to cognitive flexibility, and how different ionic currens may contribute to the unique biophysical properties observed during abDGCs critical maturation periods. However, it is largely unclear how adult neurogenesis influences DG neural network in vivo, and how changes in abDGCs' biophysical and synaptic properties during critical maturation period relate to their behavioral impacts. Recently, we developed a robust optogenetic platform capable of transiently silencing a set of age-defined abDGCs to bias behavior and to influence hippocampal neural network dynamics. We here will use this optogenetic platform to further analyze the neural network impacts of age-defined abDGCs on bilateral hippocampus. In addition, we will use the recently invented expansion microscopy technique to perform super-resolution anatomical characterizations of abDGCs' connectivity patterns relevant for their functional impacts. Upon completion of this study, we hope to provide a detailed, time resolved understanding of changes in the neural network connectivity patterns of abDGCs through maturation, and to advance our understanding of the functional significance of adult neurogenesis in physiology and pathology.

This National Science Foundation Research Traineeship (NRT) award to Boston University will train scientists and engineers in the emerging interdisciplinary field of neurophotonics - the use of light-based tools to study brain function at the cellular scale. Understanding how neural activities and circuits drive human computation, behavior, and psychology is motivated by a critical societal need to address brain diseases that involve disruptions or deterioration of neural circuitry - including Alzheimer's, traumatic brain injury, Parkinson's, cerebral palsy and multiple sclerosis. Recent scientific discoveries and powerful new tools in brain research have inspired broad student interest in career paths focused on understanding brain structure and function, as well as new industrial and academic career opportunities. Neurophotonics is among the most rapidly evolving research frontiers in brain science because it allows researchers to monitor and influence neuron activity and neural circuits at their most fundamental level. A prominent neurophotonic technique is optogenetics, through which communication signals from neurons are precisely monitored, activated, or inhibited using light. This project will support training for eighty (80) PhD students, including twenty (20) funded trainees, across the disciplines of neuroscience, biomedical engineering and photonics.

Trainees will become versed in the biology of neural function and the development of optical instruments, photo-excitable materials, and imaging techniques to sense and affect neural circuits. NRT trainees will graduate having attended a hands-on neurophotonics technology boot camp, participated in multiple laboratory research rotations, completed a four-course core curriculum, conducted challenging doctoral research in a neurophotonics laboratory, and written a neurophotonics-themed dissertation co-mentored by NRT faculty. The traineeship project will emphasize immersive experiential learning activities and peer-to-peer learning, two educational approaches that have been shown to reinforce learning while simultaneously improving outcomes for STEM trainees, especially underrepresented minorities. Interwoven with educational activities will be a professional preparation program that supports trainee career goals, develops communication skills, and builds professional networks. Trainee learning objectives will focus on identifying important research problems in neurophotonics, applying light-based methods to measure and control neural circuits, working on team-oriented projects, and communicating effectively.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.

In everyday social situations, normal hearing humans are able to listen to a speaker in the midst of other people talking and other sound sources. This is an example of a general problem termed auditory scene analysis. The understanding of auditory scene analysis remains a challenging problem in a diverse range of fields such as neuroscience, computer science, speech recognition and engineering, after more than 50 years of research. Although a difficult problem for machines and hearing impaired listeners, humans with normal hearing solve it with relative ease. This suggests the existence of a solution to this problem in the brain, but this solution remains unknown. This project will investigate how the brain solves this problem. By revealing circuits in the brain that contribute to the solution, this project will ultimately improve quality of life through applications in medical devices, e.g., hearing aids and cochlear implants; benefit society through applications in technology, e.g., applications for speech recognition; and create an educational platform to train students to integrate knowledge from a variety of disciplines to address challenging and important societal problems.

The spatial location of different sound sources is an important component of auditory scene analysis. The auditory cortex, with its unique spatial sound processing ability, is thought to play an important role in auditory scene analysis, although the underlying neural network mechanisms remain largely unknown. This project will investigate cortical circuits for auditory scene analysis in the primary auditory cortex of the mouse, employing powerful optogenetic tools to investigate both bottom-up and top-down mechanisms. First, the investigators will examine the influence of behavioral states on cortical spatial representations of sound mixtures across different cortical layers and test the hypotheses that such spatial representations vary across cortical layers and behavioral states of the animal. Second, the investigators will examine the causal role of parvalbumin positive (PV) inhibitory interneurons versus somatostatin positive (SOM) inhibitory interneurons in the primary auditory cortex, using optogenetic manipulations, and test the hypothesis that PV interneurons are critical in mediating bottom-up signaling, whereas SOM interneurons are selectively engaged during active behavioral states. Finally, the investigators will construct a computational model of the primary auditory cortex including excitatory, PV and SOM neurons to explain the experimental results and make predictions for future experiments.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The field of neuroscience is undergoing a rapid transformation, and within the next decade, it may become possible to capture data from millions of individual neurons at the same time. Such a technological advancement would allow scientists to record and analyze a significant fraction of the brain's neural network at unprecedented spatial and time resolutions. The goal of this research project is to advance our understanding of brain activity through the integration of bioengineering, systems neuroscience and data science and their application to the study of networks of neurons. The research team will engineer new sensors designed to image the activity of individual neurons within a large network and then apply this method to the study of functioning neural systems. The team will also develop computational methods to extract information from the resulting, extremely large datasets. This research will have broader impact through training STEM students in a convergent science area and through deepening our understanding of the science underlying neurological disease and thereby improving mental health treatment.

This research project aims to create novel protein sensors to acquire single-neuron-resolution imaging data. This methodology could serve as the basis for ultra-large-scale neural network imaging. The researchers will establish the architectural principles and fundamental limits for fluorescence imaging systems and inference algorithms that extract underlying neural activity. They will then develop machine learning techniques to extract network-level phenomena from high-dimensional neural data. Finally, the researchers will study large networks of neurons during behavior and learning via carefully-designed experiments and machine learning techniques. The technologies developed in this work, to acquire and to analyze, single-neuron-resolution imaging data, will facilitate the understanding of brain's neural network computation at an ultra-large scale, directly confronting challenging societal problems related to the human brain. The project participants will also educate the next generation of engineers and scientists in the convergent area of neuroscience with data science.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The ability of our auditory systems to recognize target sounds in a mixture of other sounds is fundamental to normal healthy function and communication. For example, during the course of a normal day we must communicate with a conversation partner in the presence of other sounds, e.g., other people talking, music, sound of cars etc. Like humans, many animals are capable of listening to a single sound source in a mixture of sources. Thus, neural circuits for solving the CPP also likely exist in animals. This proposal, will investigate how the auditory cortex contributes to solving this problem by unraveling cortical circuitry that underlies the processing of complex sound mixtures, using powerful experimental tools available in mice. By providing new insights into cortical mechanisms that help solve this problem in the normal brain, this proposal may impact the development of novel therapeutic strategies for the hearing impaired, who have great difficulty solving this problem, and improve hearing assistive devices, e.g., hearing aids and cochlear implants.

Project Summary Ultrasound has been explored as a modality to modulate nerves and muscles back in the 1920s. A number of recent studies have demonstrated the feasibility of using ultrasound to stimulate peripheral nerves, spinal cord, and brain. Yet, it has been difficult to determine whether ultrasound stimulation is via direct modulation of the membrane voltage or via indirect synaptic or network pathways. In order to unveil the mechanisms of ultrasound modulation, we formed a team of complementary expertise (Xue Han: neuroscience and technology; Ji-Xin Cheng: imaging and opto-acoustic technology; Edward Boyden: neurotechnology). Specifically, we will deploy and integrate three novel technologies that have been established in the co-PI's labs recently. First, we will use a miniature fiber optoacoustic converter (FOC) (0.4 mm in dia.) that can be positioned inside the brain to deliver localized ultrasound with an unprecedented sub-millimeter spatial resolution. Second, we will use cutting-edge genetically encoded voltage sensors to quantify the effects of ultrasound stimulation on individual cells in the brain at a temporal resolution of 1 millisecond that is beyond commonly used Ca2+ imaging. Third, we will deploy submicron spatial resolution stimulated Raman scattering microscopy to map membrane voltage at threshold and sub-threshold level to monitor membrane response to ultrasound at different regions of a single neuron. Integrating these novel technologies with a large-scale imaging platform that allows simultaneous intracranial local drug delivery, recently developed in the Han lab, we will perform a systematic analysis of the cellular and the biophysical mechanisms of ultrasound stimulation at sub-cellular level in cultured primary neurons, and in different brain regions of awake mice. Specifically, we will (1) examine the spatial response profile of individual neurons in awake brains by FOC-based neurostimulation and large-scale Ca2+ imaging in vivo; (2) examine the temporal response profile of individual neurons in awake brains by FOC-based neurostimulation and in vivo voltage imaging with genetically encoded voltage sensors; and (3) examine the involvement of membrane deformation and mechanosensitive channel activation in ultrasound neuromodulation. Our proposed studies will deliver a systematic understanding of the spatiotemporal profiles of ultrasound neuromodulation in the brain, and identify the causal role of membrane deformation and mechanosensitive channels. These new knowledge will build a new foundation for rational design of ultrasound neuro-stimulators and for basic neuroscience research as well as treatment of neurological disorders.

In recent years there has been much excitement about genetically encoded fluorescent indicators of neural activity, with new molecules such as the genetically encoded calcium indicator GCaMP6 being used to image the activity of many neurons at once in living brains. However, such indicators are slow, raising the question of whether voltage indicators will become useful enough to be widespread in neuroscience. Furthermore, imaging of axons and dendrites remains difficult, especially in densely expressing tissues. For example, when neurons express such reporters densely, axons and dendrites within the diffraction limit of light will have their signals mixed, so that the signals of individual neural processes cannot be resolved. How can we push the spatiotemporal performance of neural activity imaging to the specifications desired by neuroscientists ? down to the millisecond timescale, and down to the sub-micron scale axonal and dendritic parts of neurons? We here propose to address this problem through molecular engineering, guided by in vivo imaging constraints. To address the spatial dimension: if neural activity indicators could be safely clustered into discrete, bright puncta that, even when expressed in all the cells of a neural circuit, are separated from one another by a distance greater than the diffraction limit of the imaging system, then these puncta could cleanly be imaged, and used to sample activity along axons and dendrites of the neurons in a circuit. In this grant, we will (Aim 1) create and validate this strategy, which we call stochastic arrangement of reagents in clusters (STARC). In this way, we will effectively point the way towards circuit-wide neural activity imaging that allows for the investigation of axonal signaling and dendritic processing, and not only cell body imaging. To address the temporal dimension: we will create optimized fluorescent voltage indicators (Aim 2). Pioneering efforts have resulted in fluorescent voltage indicators, but their performance is often poor when utilized in the brain, because of poor trafficking and membrane localization that manifests in vivo, since neurons in vivo are different from the cultured cells used to screen for the voltage sensors. We will conduct an in situ screen to directly identify fluorescent voltage indicators that work well in neurons in intact mouse brain circuits, by virally expressing members of a library of mutant voltage indicators directly in the mouse brain, imaging the responses with single cell resolution in mouse brain slices, and then directly reading out the mutations that yielded the voltage indicators that best perform in actual brain circuits, validating the resultant indicators in the mouse brain. We will also create (Aim 3) STARC forms of voltage sensors, since the proximity issues discussed in Aim 1 are even more severe when a neural activity reporter is on a neural membrane that is in close proximity to other membranes. We will close the loop by testing all such indicators in vivo and then iterating on the molecular engineering, delivering to the neuroscience community a powerful, simple-to-use toolbox that can be rapidly deployed for ultraprecise ? across both space (via STARC) and time (via in situ optimized voltage indicators) -- neural activity imaging.

Cognitive and motor behavior in the brain is controlled by networks of highly interconnected neurons. Neurons communicate via signals called spikes, which are generated by complex biological mechanisms. These mechanisms crucially depend on the subthreshold membrane potential activity, which is controlled by the complex interaction of ionic currents among other factors. Although the spiking patterns of the individual neurons are typically not regular, certain neuronal networks produce periodic oscillatory patterns. Important among them is the theta rhythm (4-10 Hz), which has been recorded in various brain areas by global activity measures, such as electroencephalography (EEG) or extracellular local field potentials (LFPs). Theta oscillations have been observed during motor activity and REM sleep, and are thought to play important roles in navigation, episodic memory and learning. Theta oscillations have also been observed at the subthreshold membrane potential level in brain slice preparations, and in behaving animals in the hippocampal CA1 area. However, how the oscillatory activity at the network level is linked to the biophysical properties of individual neurons remains largely unknown. In this project, the investigators will address this question using a combined experimental/theoretical approach. The Boston University team will perform experiments in behaving animals in CA1, and the NJIT team will carry out detailed computational modeling. This research is expected to generate a framework for describing and understanding how high-level neuronal oscillations depend on the oscillatory activity of individual neurons through complex network interactions. The PIs will also work to disseminate their imaging technology to the scientific community. This project will contribute to the cross-disciplinary training of students and postdoctoral trainees in both experimental and computational neuroscience.

The central hypothesis of this project is that theta oscillations in the hippocampus are generated by resonant mechanisms involving the intrinsic properties of individual neurons, and circuit interactions that are tuned to amplify theta frequency inputs from the medial septum and possibly other external sources. We will address this hypothesis from an interdisciplinary perspective involving in vivo experiments, computational modeling, and dynamical systems analysis. We aim to understand the cellular and circuit mechanisms of hippocampal theta oscillations in vivo, and to create a theoretical framework to describe the biophysical and dynamic links between the oscillatory properties of individual neurons and network oscillations. The Boston University team will deploy a novel voltage imaging technique to measure subthreshold voltage dynamics and spiking activity from individual hippocampal neurons of defined cell types, including pyramidal cells and local interneurons (e.g. parvalbumim (PV)- and somatostatin (SOM)- positive ones) during behavioral states with varying levels of LFP theta oscillations. Additionally, to test the causal role of these interneurons in supporting theta oscillations, precision optogenetic activation and silencing will be used. The NJIT team will build biophysical models of the hippocampal network that include the intrinsic subthreshold oscillatory properties of the participating neurons and inputs from other areas (e.g., medial septum) to produce theta LFP oscillations. The results of the proposed research will provide mechanistic insights on the formation of hippocampal CA1 network oscillations with implications to learning, memory and other cognitive functions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Title: Voltage imaging analysis of striatal network dynamics related to movement, Parkinson?s disease and deep brain stimulation Summary Deep brain stimulation (DBS) delivers high frequency electrical current stimulation through chronically implanted electrodes. DBS has been FDA approved for managing several brain disorders, including Parkinson?s disease (PD), epilepsy, essential tremor, and obsessive compulsive disorders. However, the therapeutic mechanisms of DBS remain largely unknown. There are many intriguing hypothesis, but experimental evidence has been limited. The increasing use of DBS for PD over the past 20 years has offered a unique opportunity to record from various basal ganglia brain structures in patients, and accumulating evidence suggests that exaggerated pathological local field potential (LFP) beta oscillations (~10-30Hz) in the cortical-basal ganglia circuit are a signature of PD. Using exaggerated LFP beta oscillations recorded in STN as a target feature, a recent study showed that closed-loop DBS could be more effective in alleviating akinesia in primate PD models, highlighting the potential of using pathological beta oscillations as a biomarker for PD. PD is characterized by degeneration of SNpc dopamine neurons that project to the striatum. The fact that DBS is effective at managing motor pathologies highlights that PD involves neural circuit deficits that can be altered by electrical stimulation to achieve therapeutic effects. The central goal of this proposal is to study the neural circuit dynamics related to PD, and the therapeutic mechanisms of DBS, using a novel single cell voltage imaging technique that was recently developed in Dr. Han?s lab. Specifically, we will examine how individual striatal neurons? subthreshold membrane voltage and spiking patterns relate to bulk striatal LFP oscillations during voluntary movement in healthy and dopamine-depleted PD conditions, and how DBS alters these interactions. Such understanding will provide important insights into the relationship between individual neurons subthreshold membrane voltage dynamics (a measure of synaptic inputs) and spiking outputs, and provide direct experimental evidence linking pathological LFP oscillations with single neuron biophysics, and how DBS affects these relationships. We believe that such insights will help establish oscillation based biomarkers for brain disorders, and facilitate future DBS designs.