Timothy Dunn, Ph.D., Assistant Professor, Department of Biomedical Engineering, Duke University
Multi-scale Three Dimensional Behavioral Quantification in Individuals and Social Groups
Current methods of measuring movement of freely behaving animals have limitations: Highly detailed observations of small movements of an animal (a single digit, for example) require restricted ranges of motion. Studying freely moving behavior in 3D space often means limiting resolution, perhaps only tracking overall position, or relying on an observer’s description. Automatic video tracking in animals typically requires an unnatural, simple environment, and body parts not visible to cameras aren’t tracked accurately. High-resolution Artificial Intelligence (AI) predictions over large three-dimensional spaces using volumetric spatial representation, a technique recently developed to overcome these issues, require massive computing power. Adding multiple animals for social observations introduces additional issues.
As a result, there is poor availability of the most desired data: High-resolution, automatic tracking of animals in 3D space performing natural behaviors, alone or in groups, and quantification of that motion in a standardized format. Dr. Dunn is working on a new approach that aims to bring that ideal closer. Building on learnings from a 3D geometric machine-learning algorithm his team used to greatly improve the accuracy of predictions, Dr. Dunn and his team are now working on adaptive recurrent image sampling (ARIS) that combines images from multiple cameras to build a model that can measure and predict body position on many scales, even when a part (such as an arm or foot) isn’t directly visible.
ARIS selectively improves the resolution of fine-scale body features, and uses predictive modelling based on what it knows of its subject (arrangement and length of limbs, how they are connect, how they move, etc.) – learned first by parsing enormous amounts of training data from freely-behaving rats and then fine-tuned using training data in other species – to focus on the portion of space where the body part is likely to be. This uses far less computational power than previous 3D volumetric tools. In his research, Dr. Dunn will implement ARIS and record data at multiple scales, from overall position and posture down to the movement of fine features of the hands, feet, and face. Further research will explore its effectiveness with multiple animals interacting. This ability to measure behavior in a new, more precise way has broad implications for the study of neurological disorders that affect movement, linking brain activity to behavior, and studying social interactions.
Jeffrey Kieft, Ph.D., Professor, Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine
A New Technology to Control the Transcriptome
Messenger RNA, or mRNA, is recognized as a vital player in the life and health of cells. These RNA molecules are the templates to make protein, and are created within cells to carry instructions to the protein-making machinery, then are destroyed by enzymes. The totality of mRNA an organism expresses is called its “transcriptome.”
Deficiencies in mRNA and non-coding RNA (ncRNA) are linked to certain neurodegenerative and neurodevelopmental disorders. If there is too little of a specific mRNA or ncRNA in the transcriptome, certain cellular functions may be degraded or disabled. Dr. Kieft is exploring a novel way to manage the transcriptome by slowing the decay of mRNA and ncRNA. Knowing that some enzymes that destroy the RNAs essentially “chew” it from one end to the other, Dr. Kieft used his understanding of how RNA molecules are structured and fold on themselves to create an engineered piece of exoribonuclease-resistant RNA (xrRNA) that, when introduced to compatible mRNA or ncRNA, combines and folds to form a “blocking” structure, literally changing the shape of the RNA by inserting a protrusion that stops the enzymes in their tracks.
By slowing the decay of the target mRNA and ncRNA, Dr. Kieft sees the opportunity to manage their abundance within the transcriptome. Engineered xrRNAs could recognize just specific targets, link up with them, and create the protection, so researchers can increase the proportion of the target without changing how much is created. The approach has the advantage of being less disruptive to the host cell than unnaturally boosting mRNA, and the precision with which xrRNA can be engineered offers the potential to target multiple RNAs at once, and possibly even allow fine-tuning by precisely managing the rate of decay. Dr. Kieft sees this application, born of basic science studying RNA, as a potentially powerful research tool for neuroscientists, and perhaps even the foundation for therapies in the more distant future.
Suhasa Kodandaramaiah, Ph.D., Benjamin Mayhugh Assistant Professor, Department of Mechanical Engineering, University of Minnesota Twin Cities
Robot Assisted Brain-Wide Recordings in Freely Behaving Mice
Neuroscientists studying brain activity during behaviors usually have to make a trade-off: They use miniaturized head-mounted neural sensors that are light enough to allow a subject animal to behave freely, but are lower resolution or can’t monitor the whole brain. Or they use more powerful tools, which are far too heavy for subject animals and require other solutions, like immobilization while letting animals move on a treadmill, or even using virtual reality experiences that nonetheless limit the behavior of a subject.
Dr. Kodandaramaiah is tackling the challenge with a robotic cranial exoskeleton that carries the weight of neural recording and monitoring hardware while still allowing the subject (in this case a mouse) to rotate its head in all three degrees: a full 360 degree turn in the yaw (horizontal rotation) axis, and about 50 degrees of motion in the pitch and roll axes, while moving around in an arena. The robot has three jointed arms arranged in a triangular configuration, suspended over the subject and meeting at the point of mounting on the head. Sensors in the mount will detect what motion the mouse is making and direct the robot to enable the motion with as little resistive force as possible, allowing the mouse to turn and move within an arena typically used for neuroscience experiments with all the necessary sensory equipment and wires from the implants supported by the robot.
Taking out the need for miniaturization allows researchers to use whatever state-of-the art hardware is available, meaning a robot can theoretically be upgraded to use the latest technology soon after its introduction. To get to that point, Dr. Kodandaramaiah’s team will go through several steps – engineering the exoskeleton; engineering the head-stage with its needed sensors plus high-density electrodes and cameras for external observation of eyes, whiskers and more; performing benchtop testing; tuning the robot to the inputs a mouse can deliver; determining how to introduce probes; and finally making live recording. With this mechanical underpinning, Dr. Kodandaramaiah hopes to help researchers get closer to the state where they can make detailed brain-wide neural recordings of freely behaving subjects over long timescales.
Eva Dyer, Ph.D., Assistant Professor, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University
“Comparing Large-Scale Neural Datasets Across Time, Space, and Behavior”
The ability to observe and record neural data over large parts of the brain has resulted in enormous amounts of data, making it possible to find patterns in the data that can explain how many neurons work together to encode information about the world. Even with new advances in finding low-dimensional patterns in datasets, it is still challenging to compare multiple large-scale recordings, whether it be over long periods of time, or across different individuals solving the same or similar tasks, or across disease states. Dr. Dyer’s experience using machine learning (ML) to decode brain activity has led her to a novel solution to identify patterns in multiple large neural datasets.
Dr. Dyer’s work involves creating machine learning algorithms to extract meaningful information from neural datasets, which are labelled to identify whether the animal was asleep, awake, foraging, or engaging in various motions or behaviors. New cryptography-inspired mathematical rules guide the algorithms to identify similar patterns in separate data sets, looking specifically to match the neural activity generated by different brain states as a starting point for bringing the data into alignment. Aligning neural activity can show how neural patterns are related to the behavior and state of the subject as well as prevent corruption by noise, and provides a critical stepping-stone for more powerful analysis techniques.
Dr. Dyer’s second aim will help researchers refocus on single neurons to understand how they contribute to the overall changes in neural activity, and whether they can be used to predict specific brain states. The research will further explore whether differences in behaviors can be traced back to specific cell types, and how the differences seen across datasets can be used to characterize variation across individual animals. The ability to decode and compare large neural datasets will prove invaluable in neurological research by indicating how neurodegenerative disease affects the brain’s processing of information.
Rikky Muller, Ph.D., Assistant Professor of Electrical Engineering and Computer Sciences, University of California – Berkeley
“A High-Speed Holographic Device for Optogenetic Control of Thousands of Neurons”
Optogenetics – genetically modifying neurons to be light-sensitive so researchers can activate or silence them at will – has revolutionized neuroscience research. Paired with spatial light modulators that shape light into 3D holograms, researchers can individually control many neurons distributed throughout a three-dimensional region of a brain in vivo. But until now, there has not been a holographic projector able to control neurons at the speeds found in the brain naturally.
Dr. Muller is designing and building a holographic projector to solve this issue. Her device will stream holographic light images at rates of 10,000 frames per second (Hz). Many current-generation TVs refresh 60 frames per second, for comparison, and the fastest commercially available holographic tools top out at 500 Hz. This high refresh rate is necessary to replicate natural neural signaling, which involves action potential times of about 1/1,000th of a second (equivalent to 1,000 Hz when considering refresh rates.) Additionally, Muller aims to target thousands of neurons with pinpoint accuracy, and just as higher rates in TVs result in sharper images, a 10,000 Hz hologram will offer greater precision.
Dr. Muller, an electrical engineer who focuses on neurotechnology, regularly consults with neuroscientists as she designs, tests, and builds the device to ensure it serves their needs. The device will use a micromirror array, which will sculpt 3D patterns of light to specific locations and depths through the electrical actuation of miniature mirrors; the light is then relayed through a series of lenses. The project will first design and fabricate two arrays – a smaller array for testing and proof of concept, and a larger format array, along with the associated drivers and controls that will be used for measurement and calibration. Finally, Dr. Muller’s team will produce a full-featured spatial light modulator. It is hoped that this tool will give researchers unprecedented ability to control and test neural connectivity.
Kai Zinn, Ph.D., Howard and Gwen Laurie Smits Professor of Biology, California Institute of Technology
“Modular Enzymatic Barcoding”
Many neuroscience experiments involve the analysis of antibody and receptor binding to cell surfaces. Also, an understanding of neural development and function requires knowledge about in vivo interactions among cell surface proteins. High-throughput experiments involving proteins are usually time-consuming and complex since every protein has different biochemical properties. To help open new opportunities for neuroscience research, Dr. Zinn and his team are developing a modular way to “barcode” different proteins, providing researchers with a flexible toolkit.
Barcoding in its simplest form involves inserting a genetic marker into molecules and then seeking out those markers after the experiment to determine which molecules are localized together. It has been used with nucleic acids with great success. Proteins are more complex, however, and there was no way to barcode the thousands of proteins of interest to researchers without resorting to chemical crosslinking, which often alters protein function. Dr. Zinn is overcoming this challenge with the use of fusion proteins containing high-affinity protein binding modules attached to “HUH-domain” enzymes, which can covalently couple themselves to barcode oligonucleotides. The binding modules allow the barcodes to be attached to antibodies, biotinylated proteins, and proteins with covalent binding tags. This provides access to most of the proteins of interest to neuroscientists. The project also involves building nanoparticle scaffolds with 60 binding points that can be simultaneously attached to barcodes and to proteins of interest. These scaffolds will enhance the observability of interactions – weak interactions are made stronger when multiple proteins on each structure interact.
Dr. Zinn’s project will entail developing the protocols and processes involved in conducting several types of high-throughput single-cell sequencing experiments that will provide information on proteins. These include experiments using barcoded antibodies to observe the expression of specific surface receptors on a cell, to observe changes to cells when exposed to certain proteins, to visualize large numbers of antigens in brain tissue, to screen interactions of large numbers of proteins, and to identify receptors for “orphan” proteins. Thanks to its modularity, simplicity, and the ability to allow multiple proteins to interact at once, Dr. Zinn expects his barcoding system will enable and accelerate these and many other types of neuroscience experiments.
Gilad Evrony, M.D., Ph.D., Assistant Professor, Center for Human Genetics and Genomics, Depts. of Pediatrics and Neuroscience & Physiology, New York University Langone Health
“TAPESTRY: A Single-cell Multi-omics Technology for High-resolution Lineage Tracing of the Human Brain”
It is common knowledge that every human being starts as a single cell with a single set of dna “instructions”, but details of how that one cell becomes trillions – including the tens of billions of cells in the brain – are still largely unknown. Dr. Evrony’s research is aimed at developing a technology called TAPESTRY, which may illuminate this process by building a “family tree” of brain cells, showing which progenitor cells give rise to the hundreds of types of mature cells in the human brain.
The technology may solve some of the key issues facing researchers studying human brain development. The key method for studying development by tracing lineages (introducing markers into cells of immature animals and then studying how those markers are transmitted to their progeny) is impossible in humans because it is invasive. Dr. Evrony’s prior work along with colleagues has shown that naturally-occurring mutations can be used to trace lineages in the human brain. TAPESTRY aims to advance and scale this approach by solving several limitations of current methods. First, lineage tracing requires more reliable isolation and amplification of the tiny amounts of DNA of single cells. Second, a detailed understanding of human brain development needs to be cost-effective to allow profiling of thousands or tens of thousands of individual cells. Finally, it needs to also map phenotypes of cells – not just seeing how closely cells are related, but also what types of cells they are. TAPESTRY seeks to solve these challenges.
Dr. Evrony’s approach is applicable to all human cells, but is of special interest in brain disorders. Once healthy brain lineages are mapped, they can be used as a baseline to see how brain development differs in individuals with various disorders that likely arise in development, such as autism and schizophrenia.
Iaroslav ‘Alex’ Savtchouk, Ph.D., Assistant Professor, Department of Biomedical Sciences, Marquette University
“Fast Panoptical Imaging of Brain Volumes via Time-tagged Quadrangular Stereoscopy”
Modern optical brain imaging techniques allow observation of a thin layer of the brain, but imaging lots of brain activity in 3-dimensional space – such as a volume of brain – has proven daunting. Dr. Savtchouk has developed an approach that allows researchers to see what is happening not just on the surface of a brain, but deep within and in much higher spatio-temporal resolution than ever before.
The core process – two-photon microscopy – picks up brain activity by looking for fluorescence in the genetically modified brain cells of laboratory animals. With a single laser, depth information is recorded very slowly. With two laser beams, researchers essentially get binocular vision – they can see what is closer and further away, but there still are visual “shadows” where nothing can be seen (for example, when a person looks at a chess board edge, some pieces may be blocked by nearer pieces.) Dr. Savtchouk is solving this issue with the addition of two additional laser beams, which gives quad-vision and greatly reduces blind spots. He is also sequencing the timing of the lasers – which pulse rapidly – so researchers know which laser saw which activity, critical to building a time-accurate three-dimensional model.
Dr. Savtchouk’s project first involves designing the system in computer simulations, then proving its application with mouse models. His goal is to develop ways to update existing two-photon microscopes both through the addition of laser beams and through upgrades to hardware and software, allowing labs to benefit from the technology without paying for a whole new system.
Nanthia Suthana, Ph.D., Associate Professor, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles
“Wireless and Programmable Recording and Stimulation of Deep Brain Activity in Freely Moving Humans Immersed in Virtual (or Augmented) Reality”
Studying human neurological phenomena presents many challenges – human brains cannot be studied directly like animal brains, and it is hard to recreate (and record the outcomes of) the phenomena in a laboratory setting. Dr. Suthana proposes developing a system that uses virtual and augmented reality to create realistic test scenarios for her subjects. She uses data recorded by implantable brain devices used in the treatment of epilepsy.
Hundreds of thousands of people have these devices implanted, and many of the implanted devices allow for wireless programming and data recovery. Dr. Suthana’s approach takes advantage of the latter – these devices record all kinds of deep brain activity, and she can tap into data recorded while subjects are interacting in VR or AR-based experiments. Importantly, the subjects can move freely since they carry the brain activity monitor and recording device with them. Motion capture and biometric measurements can be made simultaneously, assembling a complete picture of responses.
Dr. Suthana is working with a multidisciplinary team to make the system work; this team includes electrical engineers, physicists, and computer scientists. Basic facts like signal latency need to be established so data can be synchronized and measured accurately. Ultimately, she believes that freely-behaving humans interacting with the most realistic simulations possible will allow researchers to understand more accurately how the brain works. In addition to basic neurological questions – like what brain activity and physical responses accompany specific actions or reactions to stimuli – the system shows promise for research into post-traumatic stress disorder and other conditions where environmental triggers can be simulated in a controlled virtual environment.
Michale S. Fee, Ph.D., Glen V. and Phyllis F. Dorflinger Professor of Computational and Systems Neuroscience, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology; and Investigator, McGovern Institute for Brain Research
“New technologies for imaging and analyzing neural state-space trajectories in freely-behaving small animals”
Studying neural activity in the brains of animals is a long-standing challenge for researchers. Current approaches are imperfect: the current size of microscopes require animals to be restricted in their activity, and these microscopes offer a limited field of view of neurons. By making breakthroughs in microscope miniaturization, Dr. Fee and his lab are developing the tools needed to see what’s going on in an animal’s brain while the animal is free to perform natural behaviors.
The head-mounted microscope allows Dr. Fee to observe changes in the brains of juvenile birds as they learn to sing their songs. As they listen, repeat, and learn, Dr. Fee documents the neural circuits that develop as part of this complex learning process. These circuits are related to human circuits that form during complex learning of motor sequences, such as learning to ride a bike, and are disrupted in certain conditions including Parkinson’s disease. Given his aim to document a natural learning process, it’s of vital importance to be able to record neural activity during natural behaviors.
In addition to miniaturization, the new microscope will have the ability to record an order of magnitude more neurons than other techniques used on freely-behaving animals and will be paired with new data analysis that will allow researchers to make observations in real time and adjust their experiments, speeding the research process. It will have immediate and broad applications for researchers exploring all kinds of brain behaviors in small animals.
Marco Gallio, Ph.D., Assistant Professor, Department of Neurobiology, Northwestern University
“Re-wiring connections in the living brain”
This research aims to expand our understanding of how brains work by allowing scientists to selectively prune synaptic connections and to encourage new connections between neurons. This re-wiring of the brain will allow researchers to understand more precisely which connections play a role in specific subsets of neurological effects.
Each neuron within a brain circuit connects to multiple targets. Each target may have a unique function, and therefore process the same incoming information in a completely different way. For example, some specific neurons in the fruit fly brain carry information about the external environment which is used to quickly get away from imminent threats (an innate behavior), but also to produce long-lasting associations through learning.
The proposed technology will allow researchers to pinpoint the connections that are critical to each process by selectively removing synapses to the learning centers while leaving all other connections intact. The project aims to use genetic engineering to produce designer proteins that will mediate either repulsion or attraction/adhesion between genetically defined synaptic partners in the intact brain of living animals. In addition to proving that this kind of rewiring of brains is possible, the research will result in new fruit fly strains with unique genetics that can immediately be shared with other researchers. By design, these tools can be easily modified for use in any animal model or applied to different parts of the brain, enabling a whole new class of neurological studies with profound implications for our understanding of how human brains work.
Sam Sober, Ph.D. , Associate Professor, Department of Biology, Emory University
Muhannad Bakir, Ph.D., Professor, School of Electrical and Computer Engineering and Associate Director, Interconnect and Packaging Center, Georgia Institute of Technology
“Flexible electrode arrays for large-scale recordings of spikes from muscle fibers in freely behaving mice and songbirds”
Our understanding of how the brain coordinates muscle activity during skilled behavior has been limited by the technology used to record such activity – typically, wires inserted into muscles that can only detect the summed activity of many individual signals that the nervous system uses to control muscles. Drs. Sober and Bakir are developing what is in essence a “high definition” sensor array (a collection of many small sensors) that resolves many of these issues by allowing researchers to detect and record very precise electrical signals from individual muscle fibers.
The proposed sensor has many detectors that record from a muscle without damaging it. (Prior approaches relied on wires that could damage muscles when inserted, especially small muscles used in fine motor skills.) The arrays are fabricated from flexible materials that fit the shape of a muscle and change shape as the animal moves. Furthermore, because the arrays collect exponentially more data than prior devices, they have built-in circuits to collect and package data before transmitting the signals to the researcher’s computer.
A prototype version of the array has already revealed new insights: previously, it was believed that the nervous system controls muscle activity by regulating only the total number of electrical spikes sent to a muscle. But precise detection revealed that millisecond-level variations in multi-spike timing patterns change how muscles control behavior. The new arrays will be designed for use in mice and songbirds and will help us understand the neural control of many different skilled behaviors and potentially provide new insights into neurological disorders that affect motor control.
Jose M. Carmena, Ph.D., Professor, Department of Electrical Engineering and Computer Sciences, and the Helen Wills Neuroscience Institute, University of California Berkeley
Michel M. Maharbiz, Ph.D., Professor, Department of Electrical Engineering and Computer Sciences, University of California Berkeley
Neural Dust: an ultrasonic, low power, extreme miniature technology for completely wireless and untethered neural recordings in the brain
Drs. Carmena and Maharbiz are collaborating to create the next generation of brain-machine interface (BMI) using so-called “neural dust”—implantable, mote-sized, ultrasonic sensors that could eliminate the need for wires that go through the skull, and allow for untethered, real-time wireless cortical recording. While researchers in their labs as well as other colleagues at the University of California Berkeley’s Department of Electrical Engineering and Computer Sciences and the Helen Wills Neuroscience Institute are studying the potential of neural dust technology as applied to muscles and the peripheral nervous system, funding from McKnight will allow researchers to apply the concept to the central nervous system, a method they believe could revolutionize neurology in the same way the pacemaker revolutionized cardiology. Through closed-loop operation of neural dust technology, Carmena and Maharbiz envision a future in which the brain could be trained or treated to restore normal functionality following injury or the onset of neuropsychological illness.
Ali Gholipour, Ph.D., Assistant Professor in Radiology, Harvard Medical School; Director of Radiology Translational Research, and staff scientist at the Computational Radiology Laboratory, at Boston Children’s Hospital
Motion-robust imaging technology for quantitative analysis of early brain development
The motion of fetuses, newborns, and toddlers poses a special challenge for researchers focused on advanced imaging to analyze early brain development and identify possible disruptions. Dr. Gholipour’s research group in the Computational Radiology Laboratory at Boston Children’s Hospital is working to develop, evaluate, and disseminate new, motion-robust magnetic resonance imaging (MRI) technology and software that will allow researchers to study and characterize in-utero, perinatal, and early childhood brain function and structure. New imaging and image analysis tools can lead to dramatic improvements in the neuroscience community’s ability to collect and analyze big data to improve understanding of early brain development and establish a clearer link to disorders that may originate from the earliest stages of life.
Alexander Schier, Ph.D., Leo Erikson Life Sciences Professor of Molecular and Cellular Biology, Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University
Recording the history of neuronal activity through genome editing
Dr. Schier’s lab is pursuing a novel technology to test whether genomic editing technologies can record the history of neuronal activity. The proposed approach, called GESTARNA (for genome editing of synthetic target arrays for recording neuronal activity), has the long-term potential to record neuronal activity of millions of neurons over extended periods. Using zebrafish as the model system, the tools and concepts generated by Dr. Schier and his team could eventually be applied to other neuronal systems in which genome editing and next-generation sequencing is possible. A past recipient of McKnight Foundation support, Schier earned early career recognition as a McKnight Scholar (1999-2002), and was a recipient of the Brain Disorders Award (2006-2008).
Kwanghun Chung, Ph.D., Massachusetts Institute of Technology
Multi-scale proteomic reconstruction of cells and their brainwide connectivity
Dr. Chung and his lab are developing new technologies to generate a comprehensive, high-resolution brain map. He will combine new tissue processing technologies with genetic labeling techniques. Current brain mapping is relatively low resolution and incomplete; Chung’s research will allow neuroscientists to interrogate many molecules, cell types, and circuits in single tissues. Dr. Chung hopes that this high resolution, comprehensive brain mapping will accelerate the pace of discovery in a broad range of neuroscience applications and enable scientists to characterize animal disease models in a fast and unbiased way.
Narayanan (Bobby) Kasthuri, Ph.D., MD, University of Chicago and Argonne National Labs
Brain-X: Nanoscale maps of entire brains using synchrotron-based high-energy x-rays
Dr. Kasthuri’s lab is using high energy X-rays to create complete and comprehensive maps of the brain. The stacks of images generated result in staggering amounts of data that can be segmented to identify the location of every neuron, blood vessel, and component of the brain. By generating maps of healthy mice and human brains, scientists can compare them to pathological samples to better understand cellular and ultimately synaptic differences in diseased brains affected by autism, diabetes and stroke, among other diseases.
Stephen Miller, Ph.D., University of Massachusetts Medical School
Overcoming barriers to imaging in the brain
Imaging in the brain is difficult, as many molecular probes are unable to cross the blood-brain barrier (BBB). Dr. Miller and his lab have found ways to improve imaging in the deep tissue of the brain by tapping the bioluminescent properties of the firefly. Miller’s team has modified the natural firefly luciferin substrate to increase its ability to access the brains of live animals. The glow of the brain can be used to detect gene expression, enzyme activity, monitor disease progression, or gauge the effectiveness of new drugs.
Long Cai, Ph.D., California Institute of Technology
Deciphering molecular basis of cell identity in the brain by sequencing FISH
Cai’s lab has developed a high-powered imaging method based on “single molecule fluorescence in situ hybridization,” or smFISH, which makes it possible to look at genetic information (e.g. RNA) within cells. He now seeks to adapt this method to profile gene expression directly in brains at the same high resolution using sequential FISH (seqFISH).
Cynthia Chestek, Ph.D., University of Michigan
High-density 90μmpitch carbon microthread array to record every neuron in layer 5
The Chestek lab is developing a way to record and visualize healthy, interconnected, active neurons over a span of time at greater density than ever before. Using minuscule carbon thread electrodes, she plans to record neurons in a rat brain from an array of channels and then to slice the brain to visualize the entire circuit. The goal is to achieve a 64-channel array that can be observed at a high density using a conventional neuroscience connector.
Spencer Smith, Ph.D., University of North Carolina at Chapel Hill
Multiphoton imaging for large brain volumes
Single neurons act together in complex ways to shape thoughts and behaviors. Multiphoton imaging, which can resolve individual neurons from millimeters away, appears to offer an innovative way to study this process. Drawing on previous research with two-photon microscopy, Spencer’s lab is seeking to build a custom optical system to gain access to 1 million neurons while retaining the ability to observe neurons individually.
Juan Carlos Izpisua Belmonte, Ph.D., The Salk Institute for Biological Studies
Derivation, characterization and gene modification of common marmoset primordial germ cell lines under a novel condition
The Izpisua Belmonte lab is working to shorten the time needed to develop non-human primate animal models—specifically, marmosets. Belmonte has developed a strategy to facilitate generation of transgenic marmoset models using primordial germ cells (PGCs). The research has the potential to offer unlimited cell resources to study primate germ cell development in a dish and, combined with genome editing tools, the approach can help create novel animal models for human diseases.
Sotiris Masmanidis, Ph.D., University of California, Los Angeles
Silicon microprobes for monitoring mesoscale brain dynamics
The Masmanidis lab is developing micromachined silicon-based devices, or microprobes, that can be made widely available through mass production and can record many neurons at one time at millisecond resolution. The microprobes will enable Masmanidis to study how multiple brain cells interact during behavior and learning. In addition, his lab will pioneer techniques to precisely label recording locations, improving the accuracy of mapping brain activity.
Kate O’Connor-Giles, Ph.D., University of Wisconsin, Madison
A CRISPR/Cas9 toolkit for comprehensive neural circuit analysis
O’Connor-Giles seeks to develop modular toolkits to molecularly identify and gain genetic control of neuronal subtypes. These toolkits will provide critical resources for characterizing the functional contributions of genes to neuronal identity and neuronal subtypes to behavior. The O’Connor-Giles lab will employ these same technologies to understand how neurons wire together during development. The work builds on the lab’s recent success adapting CRISPR/Cas9 genome engineering technology in fruit flies.
Thomas R. Clandinin, Ph.D., Stanford University
A genetic method for mapping neuronal networks defined by electrical synapses
Most of the research on brain circuitry has focused on chemical synapses, which are easier to study than electrical synapses. But this incomplete picture of brain wiring hinders efforts to understand changes in brain activity. Clandinin proposes to develop a generalizable,genetic method to determine which neurons connect electrically to others. By the end of the two-year grant period, he expects to have a working set of tool sin fruit flies as well as a survey of specific electrical connections in the fly brain, and analogous tools ready for testing in the mouse.
Optical tools to manipulate synapses and circuits
Optogeneticsis a relatively new field that involves controlling neuronal function with light. Kennedy and Tucker hope to broaden the field by engineering new tools that will allow users to use light to control processes downstream from neuronal firing, with a focus on signaling molecules important for synapse formation, elimination and plasticity. They also plan to develop tools that allow users to manipulate the fundamental molecular signaling pathways responsible for learning and memory in the brain.
Zachary A. Knight, Ph.D., University of California – San Francisco
Sequencing neuromodulation with engineered ribosomes
The mammalian brain contains hundreds of neural cell types, each with distinct patterns of gene expression. Knight’s lab is building tools for mapping biochemical events in the mouse brain onto this molecular diversity of cells. He will develop methods for RNA capture that can help determine the molecular identity of the underlying cells. These tools will allow neuroscientists to identify the specific neurons that are modulated during changes in behavior, physiology or disease. These identified cells can then be manipulated genetically to understand their function.
Don B. Arnold, Ph.D., Associate Professor of Molecular & Computational Biology, University of Southern California
Ablating Intrabodies—Tools for Direct Ablation of Endogenous Proteins
Proteins are continually made and degraded in the brain. Dr. Arnold is working on tools to enable scientists to manipulate the process of protein degradation for biomedical research. These tools, known as ablating intrabodies, can mediate the fast, efficient and specific degradation of proteins. A protein might be degraded to test its function in normal cells or investigate the harmful effects of a particular pathological protein—in a neurodegenerative disease, for instance. Currently, scientists can only cause protein ablation indirectly, by deleting either the gene, or the RNA, that encodes the protein. Ablating intrabodies cause the direct degradation of target proteins and thus work much more quickly. They can also target proteins in particular conformations or ones with specific post-translational modifications. Dr. Arnold will test the use of ablating intrabodies by manipulating the protein content of postsynaptic sites to study synaptic function, homeostasis and plasticity within the brain. The research, if it succeeds, could have wide application in the biomedical sciences.
TIVA-tag Enables True Neuronal Systems Genomics
While it has been possible for several years to study gene expression in individual cells in laboratory cultures, continuing progress in neurobiology requires the ability to examine genetic function and regulation at the systems level, in intact tissues or living organisms. Drs. Eberwine and Dmochowski are working on a method to isolate RNA from live cells through an approach they have pioneered, called TIVA-tag (for Transcriptome In Vivo Analysis). During the grant period, they plan to tailor the chemistry of TIVA-tag compounds to collect RNA from cells with greater specificity, efficiency and less tissue damage than previously possible. By the end of the grant period they intend to have established the TIVA-tag approach as a viable methodology for systems-level genomics.
Doris Tsao, Ph.D., Assistant Professor of Biology, California Institute of Technology, and William J. Tyler, Ph.D., Assistant Professor at Virginia Tech Carilion Research Institute, School of Biomedical Engineering and Sciences
Functional Modulation of Intact Primate Brain Circuits using Pulsed Ultrasound
Neuroscience is missing a tool for noninvasively stimulating specific 3D loci anywhere in the human brain. Previous work by Dr. Tyler showed that ultrasonic neuromodulation can noninvasively stimulate neurons in the living mouse brain. The next step is to characterize how ultrasound affects a non-human primate, the macaque, whose brain is larger and more complex than that of the mouse. The researchers plan to observe neuronal responses, cerebral blood flow, and animal behavior during focused ultrasonic neuromodulation. Ultimately, Drs. Tsao and Tyler aim to develop a way to use ultrasound to stimulate specific areas of the human brain, which will provide a powerful new tool for understanding brain circuitry in humans, and provide novel strategies for treating pervasive neurological and psychiatric diseases.
Samuel S.-H. Wang, Ph.D., Associate Professor of Molecular Biology, Princeton University
Transcending the Dynamic Limits of Genetically Encodable Calcium Indicators
Fluorescent proteins that change their brightness when brain cells are active are useful in observing the neural activity underlying perception, memory, and other cognitive processes. Current versions of these proteins respond only sluggishly, on time scales of a second or longer. Dr. Wang’s lab is redesigning these proteins to respond more quickly and for a wider range of activity. Combined with advanced optical methods, such advances will allow small parts of brain tissue to be tracked in the way that fMRI imaging tracks the whole brain—with the advantage that the new method will enable researchers to see single cells and changes occurring over milliseconds. This research is part of a larger effort by neuroscientists to develop technologies to study brain networks while an animal learns, or to see what goes wrong in animals with neurological defects.
Sandra Bajjalieh, Ph.D., Professor of Pharmacology, University of Washington
Developing Biosensors for Signaling Lipids
Changes in membrane lipids play a role in neuronal signaling, but researchers cannot yet reliably track signaling lipid production. Bajjalieh plans to generate sensors to track the generation of signaling lipids in cells in real time. She will engineer proteins that bind to two signaling lipids in the absence of other signals and use them to develop fluorescent probes to track the location of these lipids. This information will make it possible to extend the approach to other lipids.
Guoping Feng, Ph.D., Professor of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology
Developing a Molecular, in vivo Tool for Genetic Manipulation of Behaviorally Defined Neuronal Microcircuits Using Coincidence Detection of Activity and Light
To study more closely how the brain processes information, Feng is developing a tool to capture specific neuronal populations activated by animal behaviors within a brief period defined by pulses of light, and select brain cells for genetic alteration based on that activity. These cells can then be tested to assess their involvement in the behavior. If successful, the tool will enable neuroscientists to genetically modify any group of neurons activated by a specific behavior in a precisely defined period.
Feng Zhang, Ph.D., Investigator, McGovern Institute for Brain Research; Core Member, Broad Institute of MIT and Harvard; Assistant Professor of Brain and Cognitive Sciences, Massachusetts Institute of Technology
Precise Genome Engineering Using Designer TAL Effectors Recombinases
Genetic expression is commonly used to identify a neuron’s type, but conventional genetic manipulation is inefficient and is limited largely to the mouse. Zhang is working on a way to modify the genome of neurons using reporter genes that can be introduced into specific cells and brain circuits. This technology would allow human mutations to be introduced into animal models to determine whether genetic mutations cause a disease. The technology will also shorten the time it takes to generate an animal model.
Michael Berry II, Ph.D., Associate Professor of Molecular Biology, Princeton University
Microfabricated patch clamp micropipette
Berry’s lab will develop a microfabricated patch micropipette that will allow novel experiments not possible with conventional glass patch micropipettes, such as the ability to readily control the chemical environment of neurons by rapid dialysis. The device will also be more reliable and simpler to use than existing micropipettes, saving significant time and effort.
Robert Kennedy, Ph.D., Hobart H. Willard Professor of Chemistry & Professor of Pharmacology, University of Michigan
In vivo monitoring of neurotransmitters at high spatial and temporal resolution
To measure neurotransmitters in vivo at high spatial and temporal resolution, Kennedy’s lab is developing a miniaturized probe that can reach into any brain region of the mouse to generate small samples for analysis at frequent intervals. This technology offers a potential breakthrough for neuroscience, because so much genetic work and many disease models are based on the mouse.
Timothy Ryan, Ph.D., Professor of Biochemistry, Weill Cornell Medical College
Development of a synaptic ATP reporter
Ryan’s lab is developing a more accurate way to measure the concentration of ATP in specific neuronal compartments and to obtain dynamic information for monitoring ATP levels during ongoing synaptic communication. This should help determine if fundamental energy imbalances are manifest in various diseases and how ATP supplies are normally regulated at synapses.
W. Daniel Tracey, Ph.D., Professor of Anesthesiology, Cell Biology and Neurobiology, Duke University Medical Center
Genetically encoded rhabdoviruses for functioning mapping of neuronal connectivity
Tracey’s lab is developing a viral gene expression system to explore neural circuits in the fruit fly. The goal is to use it to genetically manipulate nerve cells, trace their connections and manipulate the activity of interconnected neurons. If this is successful with fruit flies, Tracey hopes the same techniques will be useful for studies of mammalian brains.
Joseph Fetcho, Ph.D., Professor of Neurobiology and Behavior, Cornell University
Mapping patterns of synaptic connections in vivo
There is no easy way to reveal all of the nerve cells that connect to another cell while those cells are alive. Working with zebrafish, Fetcho proposes to use optical methods, whereby all of the neurons connected to a particular nerve cell would turn color, to map the pattern of wiring in the intact living nervous system. Ultimately, such an approach could help reveal the patterns of wiring that underlie movement and other behavior.
Pavel Osten, M.D., Ph.D., Associate Professor of Neuroscience, Cold Spring Harbor Laboratory
Automated high-throughput anatomy for fluorescent mouse brain
Osten’s project seeks to help bridge the gap between the study of molecular and cellular brain functions and the study of the whole brain. Using a novel imaging technology, he is focusing on mapping changes in neural circuits in mice that carry genetic mutations linked to autism and schizophrenia. He hopes the technology will provide a fast, accurate way to study many genetic mouse models to better understand a range of human psychiatric diseases.
Thomas Otis, Ph.D., Professor of Neurobiology, Geffen School of Medicine, University of California, Los Angeles
Development of optical methods for monitoring voltage in groups of neuroanatomically defined neurons
Otis and his colleagues, including co-principal investigator Julio Vergara, have developed a sensor technology that allows nerve impulses to be measured with high fidelity using novel optical methods. The purpose of the grant is to perfect their optical method so that it can track neural activity in many neurons simultaneously.
Larry J. Young, Ph.D., William P. Timmie Professor of Psychiatric and Behavioral Science and Division Chief, Center for Behavioral Neuroscience, Yerkes National Primate Research Center
Development of transgenic technologies in prairie voles for dissecting the genetics and neural circuitry of social bonding
The study of complex social behaviors, such as maternal nurturing and social bonding, is limited by the difficulty of manipulating gene expression to learn how specific genes regulate social behavior. Young aims to generate transgenic prairie voles, which are highly social, and identify the genes responsible for individual variations in social behavior. The research will have particular relevance to such disorders as autism and schizophrenia.
Ion Channels for Neuronal Engineering
Lester will use ion channels and receptors to gain insight into how neurons are connected within circuits and how such circuits control behavior. He will engineer new receptor channels that respond only to a drug, ivermectin, that can be delivered in an animal’s diet. Once these receptors are developed, it will be possible to study how activating or inhibiting selected neurons influences behavior.
Charles M. Lieber, Ph.D., Harvard University
Nanoelectronic Device Arrays for Electrical and Chemical Mapping of Neural Networks
Lieber plans to develop and demonstrate new nanotechnology-enabled electrophysiology tools to measure electrical and biochemical signaling at the scale of natural synapses, using samples ranging from cultured neural networks to brain tissue. In the long term, these tools may be used as powerful new interfaces between the brain and neural prosthetic devices in biomedical research and, ultimately, treatment.
Fernando Nottebohm Ph.D., Rockefeller University
Development of a Technique for Making Transgenic Songbirds
The study of vocal learning in songbirds provides an excellent way to explore how memories are stored in a complex brain and how damage to the central nervous system can be repaired by neuronal replacement. Nottebohm seeks to develop a protocol for efficient production of transgenic songbirds in order to test the involvement that individual genes might have in learning and brain repair.
Development of Fluorescent False Neurotransmitters: Novel Probes for Direct Visualization of Neurotransmitter Release from Individual Presynaptic Terminals
Sames and Sulzer have developed Fluorescent False Neurotransmitters (FFN) that act as optical tracers of dopamine and enable the first means to optically image neurotransmission at individual synapses. Applying FFNs, Sames and Sulzer will develop new optical methods to examine the synaptic changes associated with learning as well as pathological processes relevant to neurological and psychiatric disorders such as Parkinson’s disease and schizophrenia.
Paul Brehm, Ph.D., Oregon Health & Science University
A novel green fluorescent protein from echinoderms provides a long-term record of neuronal network activity
Brehm is exploring a new way to image cellular activity in healthy and diseased tissue. He proposes an alternative to the jellyfish green fluorescent protein—the bioluminescent brittlestar Ophiopsila, whose long-lasting fluorescence in nerve cells can provide a long-term history of their cellular activity.
Timothy Holy, Ph.D., Washington University School of Medicine
High-speed three-dimensional optical imaging of neural activity in intact tissue
Holy is developing optical methods for recording simultaneously from very large populations of neurons by using thin sheets of light that quickly scan brain tissue in three dimensions. If successful, the study may help scientists observe pattern recognition and learning at the cellular level.
Krishna Shenoy, Ph.D., Stanford University
HermesC: A continuous neural recording system for freely behaving primates
Shenoy’s lab is trying to learn more about how neurons act by developing a miniature, head-mounted, high-quality recording system for use on monkeys going about their everyday activities. If successful, this work will create a recording device that can track individual neurons in behaving monkeys for days and weeks.
Gina Turrigiano, Ph.D., Brandeis University
Mapping the position of synaptic proteins using super-resolution fluorescence cryo-microscopy
Turrigiano and her collaborator, David DeRosier, Ph.D., will develop tools to map the way synaptic proteins are arranged into molecular machines that can generate memories and cognitive functions. If this proves successful, they will eventually be able to determine how synapses become disorganized in disease states.
Pamela M. England, Ph.D.,University of California at San Francisco
Monitoring AMPA Receptor Trafficking in Real Time
The England lab will develop a novel set of molecular tools, based on synthetic derivatives of philanthotoxin, that could be used to study the cell surface trafficking of the AMPA subtype of glutamate receptor. The goal is to produce a set of toxin derivatives that will inactivate AMPA receptors with specific subunit compositions, thus enabling pharmacological investigation of the role of these different classes of AMPA receptors in living neurons.
Alan Jasanoff, Ph.D., Massachusetts Institute of Technology
Cellular-Level Functional MRI with Calcium Imaging Agents
Jasanoff will explore a novel method of functional Magnetic Resonance Imaging (fMRI), developed in his lab, based on iron oxide nanoparticles that produce image contrast when they aggregate. If successful, the new method will be a more direct measure of neural activity, with the potential for improved spatial and temporal resolution in fMRI.
Using Viral Vectors to Probe Sensory-Motor Circuits in Behaving Non-human Primates
Krauzlis and Callaway will develop a method to inactivate specific subpopulations of neurons in localized regions of the monkey cerebral cortex. If successful, their method will provide a means to assess how specific subpopulations of neurons in different brain regions function in circuits to enable higher brain functions, such as perception, memory and sensory-motor control.
Markus Meister, Ph.D., Cal Tech
Wireless recording of multi-neuronal spike trains in freely moving animals
Meister and his collaborators, Alan Litke of the University of California, Santa Cruz, and Athanassios Siapas of Caltech, will engineer a wireless microelectrode system that will allow the recording of neural electrical signals from freely moving animals without wires attached. Combining technologies for miniaturization and lightweight materials, this system should facilitate the measurement of neural dynamics during truly natural behaviors, such as burrowing, climbing or flying.
Karl Deisseroth, M.D., Ph.D., Stanford University
Noninvasive, High Temporal Resolution Control of Neuronal Activity Using a Light-Sensitive Ion Channel from the Alga C. Reinhardtii
Deisseroth’s lab, including postdoctoral fellow collaborator Edward Boyden, will develop a new tool, based on a genetically encoded light sensitive ion channel from algae, to stimulate electrical activity in specific sets of neurons with light. Their goal is to stimulate individual action potentials with millisecond time precision and to control what neurons are stimulated using genetic methods to target channel protein expression.
Samie R. Jaffrey, M.D., Ph.D., Weill Medical College, Cornell University
Real-time Imaging of RNA in Living Neurons Using Conditionally Fluorescent Small Molecules
Jaffrey’s lab will further develop a system to enable visualization of RNA using live-cell fluorescence microscopy. His technique is based on the construction of short RNA sequences that bind to a fluorophore and greatly increase its light emission. The fluorophore is derived from that used in Green Fluorescent Protein (GFP). The goal is to revolutionize the study of RNA in the same way that GFP technology has revolutionized protein visualization.
Development of an Automatic Tape-collecting Lathe-Ultramicrotome for Large-scale Brain Reconstruction
Hayworth and Lichtman are developing a tool to slice and automatically collect thousands of tissue sections for imaging via transmission electron microscopy (TEM). TEM serial section reconstruction is the only technology proven capable of mapping out, at the finest level of resolution, the exact synaptic connectivity of all the neurons within a volume of brain tissue. But application is limited because the ultrathin sections have to be collected manually. This tool would automate the process, making serial sectioning accessible to many labs and useful on larger tissue volumes.
Alice Y. Ting, Ph.D., Massachusetts Institute of Technology
Imaging Neuronal Protein Trafficking by Optical and Electron Microscopy Using Biotin Ligase Labeling
Ting proposes an improved technology to visualize and quantify membrane protein trafficking. She has developed a highly selective enzyme-based labeling technique by which to distinguish molecules existing on neuron surfaces before a stimulus from those appearing after the stimulus. The spatial distribution of labeled molecules can then be observed with optical imaging and, with some modifications, can also be seen in higher resolution with electron microscopy.
Probing the Retina
Chichilnisky, a neurobiologist, and Litke, an experimental physicist, are collaborating on technology to record and stimulate electrical activity in hundreds of neurons at a time on a fine spatial and temporal scale. This will enable them to study how large populations of neurons process and encode information to control perception and behavior. They first plan to study the retina, and, in turn, other neural systems.
Daniel T. Chiu, Ph.D., University of Washington
Spatially and Temporally Resolved Delivery of Stimuli to Single Neuronal Cells
Nanocapsules are extraordinarily small “shells” that can contain something as minute as a molecule and deliver it to a selected target. Chiu is developing and perfecting new types of nanocapsules and refining existing ones to study how a single neuronal cell processes the arrival of a signal at its membrane surface. Nanocapsules will be useful in mapping cell surface proteins and probing how receptors send signals and trigger synaptic transmission.
Susan L. Lindquist, Ph.D., Whitehead Institute for Biomedical Research
Development and Use of Yeast Model Systems for Neurodegenerative Diseases and High Throughput Screening
Lindquist proposes to examine neurodegenerative diseases by studying the genes in baker’s yeast. Because of the great success her lab has had using yeast as a model system to study Parkinson’s disease, she plans to extend the model to two more classes of disease-the tauopathies (including Alzheimer’s) and spinocerebeller ataxia-3.
Daniel L. Minor, Jr., Ph.D., University of California, San Francisco
Directed Evolution of Ion Channel Modulators from Natural and Designed Libraries
Minor is working on a new approach to identify molecules that block or open ion channels, the proteins that are the key to electrical signaling in the brain. He will study natural peptides from venomous creatures and will make venom-like molecules for testing. Creating molecules that mimic those in nature and making them widely available will accelerate the search for drugs that may act upon specific ion channels.
Stephen J. Smith, Ph.D., Stanford University School of Medicine
Methods for the Delineation of Brain Circuitry by Serial-Sectioning Scanning Electron Microscopy
Smith is designing tools to enable neuroscience to benefit from what he calls the microscope of the 21st century, invented by his collaborator, Winfried Denk, Ph.D., a biophysicist at the Max Planck Institute. They are developing automated Serial-Sectioning Scanning Electron Microscopy (S3EM) methods that, for the first time, will provide the capacity to analyze complete brain circuits in minute detail. Smith is developing ways to stain brain tissues for analysis with this microscope, and computational tools to analyze the immense volume of information the new techniques will yield.
Stuart Firestein, Ph.D., Columbia University
A Genetically Encoded Optical Sensor of Membrane Voltage
Firestein and his collaborator, Josef Lazar, Ph.D., propose to test a new type of voltage-sensing protein that may be able to detect very small electrical events and to visualize voltage changes in a large number of cells simultaneously. This would promote a level of investigation into information processing in the brain that is currently beyond reach.
David Heeger, Ph.D., New York University
Heeger and his collaborator, Souheil Inati, Ph.D., along with Stanford University scientists John Pauly and David Ress, plan to take a new approach to improving spatial resolution of functional magnetic resonance imaging (fMRI) to enable it too routinely acquire fMRI data at extremely high resolution. The team aims to help solve some of the fundamental problems with conventional MRI.
Paul Slesinger, Ph.D., Mount Sinai/Icahn School of Medicine
G Protein Receptor Energy Transfer (GRET) System for Monitoring Signal Transduction in Neurons
Modulation of nerve cell communication occurs when chemical neurotransmitters bind to specific types of G protein-coupled neurotransmitter receptors (GPCR) that, in turn, activate G proteins. To study dynamic changes in G protein activity during nerve cell communication, Slesinger proposes to develop a protein-based, fluorescent detector for G proteins that is based on the property of fluorescence resonance energy transfer (FRET).
Bernardo Sabatini, M.D., Ph.D., Harvard Medical School
Optical Tools for the Analysis of Protein Translation in Extrasomatic Neuronal Compartments
To explore how neurons establish communication channels and how the brain stores and recalls information, Sabatini is developing molecules that emit light when neurons make proteins, and a microscope to view the process deep within the living brain.
Karel Svoboda, Ph.D., Cold Spring Harbor Laboratory
Regulation of Synaptic Transmission in vivo with High Spatial and Temporal Specificity
Svoboda is developing molecular tools to further the understanding of how synapses organize brain circuitry.
Liqun Luo, Ph.D., Stanford University
Single Neuron Labeling and Genetic Manipulation in Mice
Luo is working on a genetic method to manipulate and trace single neurons in mice to learn how neural networks are assembled during development and later modified by experience.
Wireless Recording of Neural Ensembles in Awake, Behaving Rats
The collaborators-a neuroscientist, an electrical engineer, and a mechanical engineer-are developing a wireless method of recording neuronal spike trains from awake, behaving rats to enhance understanding of learning and behavior.
Helen M. Blau, Ph.D., Stanford University
Minimally Invasive, Regulated Gene Delivery to the Central Nervous System
Blau’s lab is investigating a novel means of delivering therapeutic genes to the central nervous system, using bone marrow cells engineered with genes capable of targeting disease.
Graham C.R. Ellis-Davies, Ph.D., MCP Hahnemann University
Functional Imaging of Neuroreceptors in Living Brain Slices by Two-photon Uncaging of Neurotransmitters
Ellis-Davies is developing innovative methods to make images of aspects of brain function that have not been seen before, devising a form of neurotransmitters that remain biologically inert until activated by an intense flash of focused light.
Dwayne Godwin, Ph.D., Wake Forest University School of Medicine
Unveiling Chains of Functional Connectivity with Viral DNA
By injecting cells with viral DNA, chemically marking the virus, and tracing its spread to connected cells, Godwin is exploring new ways to reveal how nerve cells in the brain send and receive messages.
Seong-Gi Kim, Ph.D., University of Minnesota Medical School
Development of In Vivo Perfusion-based Columnar-resolution fMRI
Kim is working to increase the power of functional magnetic resonance imaging to study brain activity in greater detail.
Stephen Lippard, Ph.D., Massachusetts Institute of Technology
Synthetic Chemistry to Develop Zinc Sensors to Probe Neurochemical Signaling
Lippard is synthesizing novel fluorescent sensors that will detect zinc ions and nitric oxide in living cells and reveal their spatial pattern.
Partha Mitra, Ph.D., and Richard Andersen, Ph.D., California Institute of Technology
Developing Techniques to Record and Read-out Population Codes in Real Time from the Parietal Reach Region
Mitra and Andersen use mathematical techniques to analyze the activity of ensembles of neurons, hoping ultimately to decode the relationship between neural activity and behavior.
William Newsome, Ph.D., and Mark Schnitzer, Ph.D., Stanford University School of Medicine
In Vivo Brain Dynamics Studied with Fiber Optics and Optical Coherence Tomography
Schnitzer and Newsome (who received a special, $50,000 award) are studying brain dynamics by localizing recording sites, mapping the distribution of molecular markers, and monitoring patterns of brain activity by the precise use of light.
Timothy Ryan, Ph.D., Weill Medical College of Cornell University, and Gero Miesenböck, Ph.D., Memorial Sloan Kettering Cancer Center
Design and Application of pH-based Optical Sensing of Synaptic Activity
The scientists are developing novel fluorescent indicators of synaptic activity based on sensitivity to changes in acidity.
Daniel Turnbull, Ph.D., New York University School of Medicine
In Vivo µMR Imaging of Neuronal Migration in the Mouse Brain
Turnbull is working on a new imaging method to visualize the migration of neurons in the developing mouse brain, labeling new neurons and following them in intact animals over several days with magnetic resonance microimaging.
Michael E. Greenberg, Ph.D., and Ricardo E. Dolmetsch, Ph.D., Boston Children’s Hospital
New Technologies for Studying the Temporal and Spatial Control of Transcription and Translation in Intact Neurons
The scientists are developing a method to visualize gene activity in living nerve cells, using molecular amplifiers and fluorescence detection, to see how genes affect one another.
Paul W. Glimcher, Ph.D., New York University
Glimcher’s research explores diagnostic ultrasound to make possible the precise placement of recording electrodes in the brains of awake, active primates.
Leslie C. Griffith, M.D., Ph.D., and Jeffrey C. Hall, Ph.D., Brandeis University
Real-time Signal Transduction Sensors
Griffith and Hall are developing genetic sensors that can be introduced into individual nerve cells of living fruit flies, in an effort to determine when a cell is recruited to perform its behavioral role.
Warren S. Warren, Ph.D., Princeton University
Zero Quantum Functional Magnetic Resonance Imaging
Warren’s bold initiative seeks to make fMRI more powerful, increasing its resolution more than 100 times, allowing it to reveal active areas of the brain in far greater detail and with better contrast.