The Distinguished Seminar Series features presentations by outstanding thinkers and scientists, sponsored by the Allen Institute for Brain Science. Distinguished speakers are selected based on the impact of their interdisciplinary research to the neuroscience community. Speakers spend a full day visiting with research staff, are nominated by members of the Allen Institute, and selected by a committee of peers.
We welcome members of the broader community to join us for these open seminars. See below for a schedule of upcoming speakers and view video presentations from past speakers. Register for the upcoming seminars below.
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Liqun Luo | May 20, 2021
Wiring specificity of neural circuits
Developing brains utilize a limited number of molecules to specify connection specificity of a much larger number of neurons and synapses. How is this feat achieved? In this talk, I will first discuss our work using the Drosophila olfactory circuit as a model to address this question. I will then discuss analogous functions of some of the wiring molecules we identified in the fly olfactory circuits also in determining wiring specificity of complex circuits in the mammalian brain, focusing on the hippocampal network.
Dr. Luo is currently the Ann and Bill Swindells Professor in the School of Humanities and Sciences, Professor of Biology, and Professor of Neurobiology by courtesy at Stanford University, and a Howard Hughes Medical Institute Investigator. He earned his bachelor's degree in molecular biology from the University of Science and Technology of China. After obtaining his PhD in Brandeis University, and postdoctoral training at the University of California, San Francisco, Dr. Luo started his own lab in the Department of Biology, Stanford University in December 1996. Together with his postdoctoral fellows and graduate students, Dr. Luo studies how neural circuits are organized to perform specific functions in adults, and how they are assembled during development.
Lin Tian | July 22, 2021
Talk title TBA
Lin Tian is Associate Professor of Biochemistry & Molecular Medicine at the School of Medicine of the University of California, Davis, and the Director of the AggieLight Initiative. After graduating from University of Science and Technology of China, she joined an interdisciplinary PhD program at Northwestern University, where she studied the mechanisms of protein processing via ubiquitin-proteasome pathway in Dr. Andreas Matouschek’s lab. She then moved to HHMI Janelia Farm as a postdoc. The goal of her research is to invent new molecular tools for analyzing and engineering functional neural circuits. We also leverage these tools, combined with optical imaging techniques, to study molecular mechanisms of neurological disorders at system level and to empower searching for novel therapeutic treatments. More information is available at her lab website.
Timothy Lillicrap | January 2022
Backpropagation in the brain?
Recent advances in machine learning have been made possible by employing the backpropagation-of-error algorithm. Backpropagation enables the delivery of detailed error feedback across multiple layers of representation to adjust synaptic weights, allowing us to effectively train even very large networks. Whether or not the brain employs similar deep learning algorithms remains contentious; how it might do so remains a mystery. In particular, backpropagation uses the weights in the forward pass of the network to precisely compute error feedback in the backward pass. This way of computing errors across multiple layers is fundamentally at odds with what we know about the local computations of brains. We will describe new proposals for biologically motivated learning algorithms that are as effective as backpropagation, and outline new empirical approaches to understanding learning in the brain.
Timothy Lillicrap is a Staff Research Scientist at Google DeepMind and Adjunct Professor at the Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX) at University College London. He received his Hon. B.Sc. from the University of Toronto and Ph.D. in Systems Neuroscience from Queen’s University in Canada. He moved to the University of Oxford where he worked as a Postdoctoral Research Fellow before joining Google DeepMind as a Research Scientist. His research focuses on machine learning for optimal control and decision making, as well as using these mathematical frameworks to understand how the brain learns. He has developed new algorithms for exploiting deep neural networks in the context of reinforcement learning, and new recurrent memory architectures for one-shot learning problems. His recent projects have included applications of deep learning to robotics and solving games such as Go.
Bence Ölveczky | March 31, 2021
Neural circuits underlying motor skill learning and execution
This talk will introduce a motor skill learning paradigm that trains stereotyped complex motor sequences in rodents. By recording and manipulating neural activity in the basal ganglia, motor cortex and thalamus, we delineate the logic by which these circuits work together to promote the acquisition and control of task-specific motor sequences. I will also talk about recent work we have done to probe how the brain controls naturalistic movements across behavioral contexts.
Bence Ölveczky is a Professor of Organismic and Evolutionary Biology at Harvard University. More information is available on his lab website.
Surya Ganguli, Stanford University | January 19, 2021
Theoretical and computational approaches to neuroscience with complex models in high dimensions across multiple timescales: from perception to motor control and learning
Remarkable advances in experimental neuroscience now enable us to simultaneously observe the activity of many neurons, thereby providing an opportunity to understand how the moment by moment collective dynamics of the brain instantiates learning and cognition. However, efficiently extracting such a conceptual understanding from large, high dimensional neural datasets requires concomitant advances in theoretically driven experimental design, data analysis, and neural circuit modeling. We will discuss how the modern frameworks of high dimensional statistics and deep learning can aid us in this process. In particular we will discuss: (1) how unsupervised tensor component analysis and time warping can extract unbiased and interpretable descriptions of how rapid single trial circuit dynamics change slowly over many trials to mediate learning;(2) how to tradeoff very different experimental resources, like numbers of recorded neurons and trials to accurately discover the structure of collective dynamics and information in the brain, even without spike sorting; (3) deep learning models that accurately capture the retina’s response to natural scenes as well as its internal structure and function; (4) algorithmic approaches for simplifying deep network models of perception; (5) optimality approaches to explain cell-type diversity in the first steps of vision in the retina.
Surya Ganguli is an Associate Professor of Applied Physics at Stanford University. More information is available on his lab website.
Aman Saleem, University College London | December 2, 2020
Vision in Action: Visual processing in active behaviours
Aman Saleem is a Sir Henry Dale Fellow and Associate Professor and at University College London. The Saleem Lab focuses on understanding the visual system during active behaviours, particularly naturalistic behaviours such as locomotion and navigation. More information is available at his lab website.
Much of our everyday visual experience is based on our movements through the world, when we navigate between different places - from within a room, to between cities. Is visual function the same during navigation? We asked this using a virtual reality environment, where we presented identical visual stimuli in different locations and asked if spatial position modulates activity in the visual system. We found that activity in the primary visual cortex (V1) is strongly modulated by spatial position, and this modulation persists across higher visual areas in the cortex. However, this modulation is not present in the inputs to the visual cortex from the lateral geniculate nucleus. Furthermore, the spatial modulation of visual responses is stronger when animals actively navigate, rather than passively view the environment. Our results suggest that the spatial modulation of visual information arises in V1 with active navigation. We have also been investigating feedback inputs to V1, and visual responses to optic flow stimuli. The Saleem Lab has also developed an open-source software paradigm, BonVision, that can both present both 2D and 3D stimuli in a common framework, while maintaining the precision and replicability of standardised visual experiments.
Anatol Kreitzer, the Gladstone Institute of Neurological Disease and the University of California, San Francisco | October 1, 2020
Mapping the functional connectivity of motor thalamus
Classical models of basal ganglia propose bidirectional regulation of thalamocortical motor circuitry, yet the principles of motor thalamus function are not well understood. We developed methods to record from basal ganglia-recipient thalamic neurons in awake behaving mice and assess their functional connectivity with the cortex. Using forelimb position during locomotion as a primary behavioral readout, we identified robust modulation of thalamic firing during locomotor stride, which varied depending on cortical projection target. Thalamic neurons projecting to anterior cortex (M2) showed less stride modulation, whereas thalamic neurons projecting more caudally (S1/M1) were more strongly stride modulated. Stride modulation of cortical units followed a similar pattern, and stride modulation in basal ganglia-recipient thalamus was largely dependent on cortical input. Together, our data argue for multiple, segregated loops between basal ganglia recipient motor thalamus and cortex, which are driven largely by cortical activity.
Anatol Kreitzer is a Senior Investigator at the Gladstone Institute of Neurological Disease and a Professor of Physiology and Neurology at the University of California, San Francisco. More information is available at his lab website.
Bang Wong, Broad Institute | February 20, 2020
Visual approaches to exploring and explaining data
Data drive scientific discovery – but only if they make sense. As the pace at which we generate data increases, there is a need to find new and innovative ways to handle the volume and complexity of the information. Visual representation has proven to be an effective tool for exploring data and explaining research results. While each goal entails different approaches to data presentation, design decisions that take advantage of our innate physiological wiring to improve perception of data will be important to both. I will present work from the Pattern Design Group at Broad Institute and our strategy for making data more accessible, comprehensible, and useful.
Bang Wong is the creative director and staff scientist at the Broad Institute of MIT and Harvard. His work focuses on developing data visualization methods and techniques to understand biomedical research data. He has written over 35 articles published by Nature Methods on the fundamental aspects of visual representation. Bang is a National Academy of Sciences Kavli Fellow and a faculty member in the Department of Art as Applied to Medicine at the Johns Hopkins University School of Medicine. More information is available at his website.
Erich D. Jarvis, Howard Hughes Medical Institute and The Rockefeller University | January 17, 2020
Molecular convergence in brain regions for song learning in birds and spoken language in humans
Dr. Jarvis seeks to know how the brain generates, perceives, and learns behavior. He and his colleagues use vocal communication as a model behavior. Emphasis is placed on the molecular pathways involved in the perception and production of learned vocalizations. Dr. Jarvis uses an integrative approach that combines behavioral, anatomical, electrophysiological, and molecular biological techniques. The main focus of study is songbirds, representing one of the few vertebrate groups that evolved the ability to learn vocalizations. The overall goal of the research is to advance knowledge of the neural mechanisms for vocal learning and basic mechanisms of brain function.
Erich D. Jarvis is an Investigator of the Howard Hughes Medical Institute and Professor at The Rockefeller University. More information is available at his lab website. His research using the Allen Brain Map was recently profiled here.
Carlos Brody, Princeton University | December 11, 2019
Collicular circuits for executive control
Carlos Brody's research concentrates on collicular contributions to decision-making and developing computational models of the circuit. How do we control routing of information within our brains? Brody's lab has studied this by adapting a well-studied primate rule-learning task to rodents requiring the subject to orient to a cue. They have found that, during the delay period, deep layer neurons of the superior colliculus (SC) encode the task rule, and after the cue is presented, they encode the side of the animal’s upcoming orienting choice. However, optogenetic inactivation of the SC during the choice formation period had no effect on choices. His lab uses computational models to ask whether dynamics in a network of SC neurons could account for all these data together. By repeatedly fitting model parameters, starting from many different initial conditions, they found a diverse set of models that were consistent with the data. These electrophysiological, optogenetic, and computational modeling data strongly constrain the collicular circuit motifs that underlie the SC’s contribution to executive control.
Carlos Brody is an Investigator of the Howard Hughes Medical Institute and is the Wilbur H. Gantz III '59 Professor in Neuroscience at Princeton University. His lab has been pushing the envelope on the complexity of cognitive tasks that rodents can perform, and has been using these tasks, together with computational and experimental approaches, to study the neural mechanisms underlying cognition.
Alcino Silva, University of California, Los Angeles | November 21, 2019
Molecular, cellular, and circuit mechanisms that open and close the window for memory linking across time
Studies of the molecular, cellular and circuit mechanisms of learning and memory have focused almost exclusively on how single memories are acquired, stored and edited. By comparison, very little is known about the mechanisms that integrate and link memories across time. Recently, we have used state of the art in vivo imaging methods, chemogenetic and optogenetic approaches in the hippocampus and retrosplinial cortex, to uncover mechanisms that open and close the window for memory linking across time. Interestingly, we showed that aging disrupts these mechanisms and that this results in age dependent decline in memory linking. Importantly, studies in our laboratory have also identified strategies to rescue these deficits.
Alcino J. Silva is director of the UCLA Integrative Center for Learning and Memory and Distinguished Professor in the Departments of Neurobiology, Psychiatry, and Psychology at the University of California, Los Angeles. He is a pioneer in the field of Molecular and Cellular Cognition. In 2002, he founded and became the first President of the Molecular and Cellular Cognition Society. In 2006/2007 he served as Scientific Director of the Intramural Program of the National Institute of Mental Health.
Danielle Bassett, University of Pennsylvania | October 30, 2019
Perturbation and Control for Human Brain Network Dynamics
The human brain is a complex organ characterized by heterogeneous patterns of interconnections. New non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports our thought processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics. This talk covers an approach for understanding how perturbations to brain dynamics propagate through complex wiring patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – Dr. Bassett covers control points in brain networks, trajectories of brain activity states following perturbation to those points, and proposes a mechanism for how network control evolves in our brains as we grow from children into adults.
Danielle S Bassett is the J Peter Skirkanich Professor at the University of Pennsylvania, with affiliations in the Departments of Bioengineering, Physics & Astronomy, Electrical & Systems Engineering, Neurology, and Psychiatry. She is also an External Professor at the Santa Fe Institute.
Nelson Spruston, HHMI Janelia Research Campus | September 12, 2019
Deciphering the function of specific cell types in memory circuits
A major goal of biology is to understand complex physiological systems in terms of their cell types. What are the cell types? How do their properties and interrelationships allow the system to function? Our progress toward understanding hippocampus-dependent spatial memory in the mouse includes our efforts to provide unified descriptions of hippocampal cell types based on gene expression, morphology, circuit integration, and cellular function. This approach has allowed us to make new discoveries about hippocampal cell types and begin to explore cell-type-specific contributions to spatial memory, and we continue to develop a better understanding of the cellular and circuit basis of spatial memory.
Nelson Spruston is the Senior Director of Scientific Programs at the Janelia Research Campus, where he leads the Science and Training team. The group coordinates a number of science-related operations at Janelia. Spruston also oversees the Gene-Targeting and Transgenics resource. Spruston's lab explores the role of the hippocampus in learning and memory with an emphasis on the properties of a diverse collection of cell types.
Karen Rommelfanger, Emory University | July 18, 2019
No longer unthinkable: Neuroethics questions for the 21st century neuroscientist
Some have dubbed our current moment as the “Golden Era of Brain Science” wherein the revolution in neuroscience has prompted scientists to ask questions that were once unthinkable. Advances in neuroscience proffer new insights into fundamental and precious features of human existence such as memories, desires, emotion, and even demarcations of life and death. Such scientific promise is not just a matter of knowledge and health, but also of commerce and national pride. Our ever-expanding global neuroscience landscape requires that we, as a society and as scientists, consider the underlying values and ethics that drive brain research across culture and continents.
Karen Rommelfanger is the Program Director of Emory University’s Neuroethics Program at the Center for Ethics and Assistant Professor in the Department of Neurology and Department of Psychiatry at Emory University.
Ivan Soltesz, Stanford University | April 24, 2019
Organization and Control of Hippocampal Circuits
Ivan Soltesz Ph.D. is the James R. Doty Professor of Neurosurgery and Neurosciences at Stanford University School of Medicine. He received his doctorate in Budapest, and conducted postdoctoral research at Oxford, London, Stanford and Dallas. He established his laboratory at UC Irvine in 1995, where he served as department Chair from 2006 until his return to Stanford in 2015. His lab is interested in the nature of inhibition in the CNS, focusing on the synaptic and cellular organization of GABAergic microcircuits in the hippocampus under normal conditions and in temporal lobe epilepsy. Dr. Soltesz’ lab employs a combination of closely integrated experimental and theoretical techniques, including closed-loop optogenetics, in vivo electrophysiology and 2P calcium imaging, AI-aided segmentation of behavior, and large-scale computational modeling methods using supercomputers. He wrote an acclaimed book on GABAergic microcircuits “Diversity in the Neuronal Machine”, and he is the recipient of several awards, including the Javits Neuroscience award from NINDS, the international Michael Prize for basic epilepsy research, and the American Epilepsy Society’s Research Recognition Award.
Sebastian Seung, Princeton University | January 10, 2019
Models of cortical learning are constrained by functional connectomics
Sebastian Seung is Anthony B. Evnin Professor in the Neuroscience Institute and Computer Science Department at Princeton University, and Chief Research Scientist at Samsung Electronics. Seung has done influential research in both computer science and neuroscience. Over the past decade, he helped pioneer the new field of connectomics, applying deep learning and crowdsourcing to reconstruct neural circuits from electron microscopic images. His lab created EyeWire.org, a site that has recruited over 250,000 players from 150 countries to a game to map neural connections. His book Connectome: How the Brain's Wiring Makes Us Who We Are was chosen by the Wall Street Journal as Top Ten Nonfiction of 2012. Before joining the Princeton faculty in 2014, Seung studied at Harvard University, worked at Bell Laboratories, and taught at the Massachusetts Institute of Technology. He is External Member of the Max Planck Society, and winner of the 2008 Ho-Am Prize in Engineering.
Yang Dan, University of California, Berkeley | November 16, 2018
Neural Circuits Controlling Sleep
Yang Dan is Paul Licht Distinguished Professor in the Department of Molecular and Cell Biology and an investigator of the Howard Hughes Medical Institute at the University of California, Berkeley. She studied physics as an undergraduate student at Peking University and received her Ph.D. training in Biological Sciences at Columbia University, where she worked on cellular mechanisms of neurotransmitter secretion and synaptic plasticity. She did her postdoctoral research on information coding in the visual system at Rockefeller University and Harvard Medical School. Using a combination of electrophysiology, imaging, and computational methods, Dan’s lab has made important contributions to understanding the microcircuits underlying cortical computation, cellular mechanisms for functional plasticity, and neuromodulation of sensory processing.
Jessica Cardin, Yale University | October 9, 2018
State-dependent cortical circuits
Dr. Cardin is an associate professor of neuroscience at the Yale University School of Medicine, where her lab studies the flexible function of cortical circuits in health and developmental disease. Her lab at Yale uses a multilevel electrophysiological and optical approach to explore the dynamic interactions between inhibitory and excitatory neurons that underlie the flexible encoding of visual information in cortical circuits, and how cortical circuit function varies with behavioral state and learning. The Cardin lab also studies how developmental dysregulation of cortical circuits leads to compromised perceptual and cognitive function in models of autism and schizophrenia.
Li-Huei Tsai, Massachusetts Institute of Technology | September 20, 2018
Transcriptomic analysis of Alzheimer's disease at the single cell resolution
Professor Li-Huei Tsai is Director of the Picower Institute for Learning and Memory at the Massachusetts Institute of Technology, a Picower Professor of Neuroscience, and an Associate Member of the Broad Institute. Tsai is also a Fellow of the American Association for the Advancement of Science, a member of the National Academy of Medicine, and an Academician of the Academia Sinica in Taiwan.
Tsai is interested in elucidating the pathogenic mechanisms underlying neurological disorders that impact learning and memory. She takes a multidisciplinary approach to investigate the molecular, systems, and circuit basis of neurodegenerative disorders. Recent contributions include the identification of chromatin remodeling as a means to regulate memory gene expression and enhance cognitive function during neurodegeneration. Her lab also conducts epigenomic analysis of mouse and human Alzheimer’s disease (AD) brain samples and has identified important contributions of dysregulated immune response genes in AD. Currently, the Tsai lab uses induced pluripotent stem cells (iPSCs) derived from human subjects to model AD and large scale imaging, optogenetics, and in vivo electrophysiology to study the brain circuitry affected by AD. Recently, she and her colleagues invented a non-‐invasive sensory stimulation technology that proved effective in reducing AD pathology on animal models.
Kenneth Harris, University College London | April 27, 2018
Brain-wide patterns of neural activity underlying a visual decision task
Professor Harris studied mathematics at Cambridge University, obtained his PhD in robotics at University College London, then moved to Rutgers University in the United States for postdoctoral work in neuroscience. Before returning to UCL in 2012, he was Associate Professor of Neuroscience at Rutgers, and Professor of Neurotechnology at Imperial College London. Together with Matteo Carandini, he directs the Functional Neuromics Lab at UCL, which aims to understand how the brain processes sensory signals, and integrates them with internal signals to guide decision and action. The lab investigates these questions with a combination of experiment and computational analysis.
Hillel Adesnik, University of California, Berkeley | March 2, 2018
Optically probing the neural basis of perception
Dr. Adesnik is an assistant professor of neurobiology at UC Berkeley, where his labs studies the neural basis of sensory perception. He obtained a PhD from UCSF in synaptic physiology with Roger Nicoll, and did his postdoctoral fellowhsip at UCSD with Massimo Scanziani where he studied the structure and function of cortical inhibitory circuits. His lab at Berkeley develops and leverages novel optical tools to manipulate neural activity in the brains of behaving animals to understand the synaptic and circuit basis of neural computation in the sensory cortex.
Hilton Lewis, W. M. Keck Observatory | February 9, 2018
Sociology of the Astronomy Community - Organization and Challenges
As Director, Lewis is responsible for the operation and performance of the observatory with its twin 10-meter optical/infrared telescopes, and for the development of new capabilities. Lewis works closely with the staff, partner institutions and scientists to ensure the continued success of the Keck Observatory and foster the development of its scientific capabilities and overall productivity.
Lewis was recruited in 1986 to lead the design and development of the software that controls the Keck Observatory’s twin, 10-meter telescopes. He has held many leadership roles throughout the history of the Observatory, ranging from leading software development to overseeing the full range of technical activities at the observatory.
Lewis holds a B.S. in Electrical Engineering from the University of Cape Town and earned his MBA from the University of Hawai’i at Manoa. His professional interests include leadership and motivation of high tech teams, strategic planning, multiple-year plan design, and effective project planning and execution.
Lewis has dedicated his career to building, operating and updating the most sophisticated ground- based optical/infrared telescopes in the world, a commitment that has contributed to the unprecedented astronomical innovation and forefront science of the W. M. Keck Observatory.