Open for (neuro)science: Tutorials and symposium

Open for (neuro)science: Symposium Speakers

For almost 20 years, the Allen Institute for Brain Science has accelerated our understanding of how the brain works in health and disease through its unique big, team and open science approach. The public data and resources available at are used by tens of thousands of scientists globally each year. In collaboration with the Allen Institute’s Next Generation Leaders, we bring you a scientific symposium spotlighting our current efforts: to build a “periodic table” of brain cell types, map neural connectivity, and understand and model neuronal activity.

Symposium Speakers

Bing Brunton, Ph.D. | University of Washington

"Go with the FLOW: Visualizing spatiotemporal dynamics in optical widefield calcium imaging"

Bing Wen Brunton is an Associate Professor of Biology and the H. Stewart Parker Faculty Fellow at the University of Washington (UW) in Seattle. She joined the UW in 2014 as part of the Provost’s Initiative in Data-Intensive Discovery to build an interdisciplinary research program at the intersection of biology and data science. She also holds appointments in the Paul G. Allen School of Computer Science & Engineering and the Department of Applied Mathematics. Her training spans biology, biophysics, molecular biology, neuroscience, and applied mathematics (B.S. in Biology from Caltech in 2006, Ph.D. in Neuroscience from Princeton in 2012). The Brunton group develops data-driven analytic methods that are applied to, and are inspired by, neuroscience questions. The common thread in this work is the development of methods that leverage the escalating scale and complexity of neural and behavioral data to find interpretable patterns. She has received the Alfred P. Sloan Research Fellowship in Neuroscience, the UW Innovation Award, and the AFOSR Young Investigator Program award.

Claudia Clopath, Ph.D. | Imperial College London

"Modelling plasticity in network"

Professor Claudia Clopath is based in the Bioengineering Department at Imperial College London. She is heading the Computational Neuroscience Laboratory.
Her research interests are in the field of neuroscience, especially insofar as it addresses the questions of learning and memory. She uses mathematical and computational tools to model synaptic plasticity, and to study its functional implications in artificial neural networks.
Prof. Clopath holds an MSc in Physics from the EPFL and did her PhD in Computer Science under Wulfram Gerstner. Before joining Imperial College, she did postdoctoral fellowships in neuroscience with Nicolas Brunel at Paris Descartes and in the Center for Theoretical Neuroscience at Columbia University. She published highly cited articles in top journals such as Science and Nature, has given dozens of invited talks and keynotes around the world, and received various prizes such as the Google Faculty Award in 2015.

Fenna Krienen, Ph.D. | Harvard Medical School

"Innovations in primate brain cell types"

Fenna Krienen is a postdoctoral fellow in Steve McCarroll's lab in the department of Genetics at Harvard Medical School. She received her B.A. in Cognitive Science from University of California, Berkeley, and did her doctoral work at Harvard University with Randy Buckner using noninvasive neuroimaging in large human cohorts to infer functional connectivity in the cerebral cortex and cerebellum. She was a Brain-Mind Fellow at the Center for Advanced Study of Human Paleobiology at The George Washington University with Chet Sherwood, where she developed an analytic approach for jointly analyzing human neuroimaging and microarray data to reveal transcriptional correlates of large-scale connectivity, before joining the McCarroll lab. Fenna uses single nucleus DNA and RNA sequencing across species (focusing on primates) to understand how brain cell types have evolved, and as a way to build better links between human genetics and animal models. She is a recipient of a Simons Foundation for Autism Research (SFARI) Bridge to Independence Award.

Carolyn Ott, Ph.D. | Janelia Research Campus

"Unprecedented views of visual cortex primary cilia from large TEM volumes provide cell-type specific insights"

Carolyn Ott has been studying how primary cilia form and function for more than 15 years. Her first encounter with the cilium was through live cell imaging as a postdoctoral fellow in the laboratory of Jennifer Lippincott-Schwartz at the National Institutes of Health. Before that she completed her Ph.D. in the laboratory of Vishwanath Lingappa, where she studied how membrane spanning regions of proteins orient and move into the lipid bilayer as they are translated. Following her postdoctoral training she continued to work with Jennifer Lippincott-Schwartz, first as a staff scientist at the NIH and, for the past five years, as a senior scientist at the HHMI Janelia Research Campus in Ashburn, Virginia, where she has been investigating primary cilia in the brain. Little is known about how glial and neuronal cilia differ. By studying both the detailed anatomy of glial and neuronal cilia, as well as the dense meshwork surrounding them, Carolyn is looking for insights into how these antennae-like cellular structures receive information and influence development, learning, and behavior.

Shreejoy Tripathy, Ph.D. | University of Toronto

"Identifying the transcriptomic signatures of cell type-specific electrophysiological heterogeneity using publicly available Patch-seq datasets"

Dr. Shreejoy Tripathy is an Independent Scientist at the Centre for Addiction and Mental Health (CAMH) and Assistant Professor in the Department of Psychiatry at the University of Toronto. The lab aims to develop a multi-scale understanding of brain cell type diversity, bridging genetics and gene expression with cell and circuit physiology. Dr. Tripathy’s long-term goal is to better understand the cellular changes that underlie psychiatric and neurological disorders and to ultimately develop approaches that can help guide tailored treatments for mental health patients.
Before arriving in Toronto, Dr. Tripathy did his Post-Doc with Paul Pavlidis at the University of British Columbia, where he worked on integrating neuron electrophysiology with cell type-specific gene expression. He received his PhD in Neural Computation from Carnegie Mellon University in 2013, working with Nathan Urban. His PhD thesis was on computational and neuroinformatics methods for studying the electrophysiological diversity of neurons throughout the brain.

Nick Turner, Ph.D. Candidate | Princeton University

"EM circuit reconstruction with functional data and segmented organelles"

Nicholas L. Turner is a Ph.D. candidate advised by H. Sebastian Seung in the Computer Science department at Princeton University. His work has helped to improve neural circuit reconstruction from electron microscopy (EM) volumes, and includes careful study of the resulting large scale reconstructions. His software has also been a key component towards producing some of the largest EM circuit reconstructions to date. Before his graduate career, he received his bachelor’s degree from Stanford University in Psychology, and completed an Intramural Research Training Award Fellowship at the NIH.



Yaniv Ziv, Ph.D. | Weizmann Institute of Science

"Representational drift in the mouse visual cortex"

Dr. Ziv is an Assistant Professor at the Department of Neurobiology at the Weizmann Institute of Science. Dr. Ziv lab’s main goal is to understand how memories are acquired, processed, and stored in the brain over the long term. Dr. Ziv is specifically interested in long-term memory of places and events — the type of memory that depends on the hippocampus and related cortical circuits. In Dr. Ziv's research combines novel in-vivo optical imaging techniques for longitudinal recordings of neuronal activity in freely behaving rodents, genetic tools for manipulating neuronal activity in specific cell types, and computational approaches they develop for longitudinal analysis if neuronal activity data.

Joel Zylberberg, Ph.D. | York University

"Learning from unexpected events in the neocortical microcircuit"

Joel Zylberberg is Associate Fellow of Learning in Machines and Brains at CIFAR, Faculty Affiliate at the Vector Institute for AI, and Canada Research Chair in Computational Neuroscience at York University. Zylberberg’s research lies at the intersection of machine learning and neuroscience, and his excellence in these areas has been recognized by multiple awards including the Google Faculty Research Award in Computational Neuroscience, Sloan Foundation Research Fellowship in Neuroscience, and the CIFAR Azrieli Global Scholar Award for Learning in Machines and Brains. Zylberberg received his Ph.D. in Physics from U.C. Berkeley in 2012, was Acting Assistant Professor of Applied Mathematics at U. Washington from 2012-2015, and was Assistant Professor of Physiology and Biophysics at the U. Colorado School of Medicine from 2015-2018. In 2019, Zylberberg moved his laboratory to York University in Toronto, Canada.

Allen Institute Speakers

Agnes L. Bodor, Ph.D. | Scientist II

"Recognizing neuronal cell types in electron microscopy (em) datasets"

Agnes L. Bodor joined the Allen Institute in 2013 with over 10 years of experience in laboratory research. She is currently working to reconstruct the mouse visual cortex as a part of the neural coding group. Prior to joining the Allen Institute, Bodor was a scientist at the University of Washington where she used classical anatomical methods such as light and electron microscopy to examine the structure and connectivity of the songbird brain. Her current research interests include the use of cortical cell labels and electron microscopic serial sections to reconstruct the connectivity of the mouse visual cortex. This will help us to understand structure and connectivity in relation to function in the mammalian neocortex. Bodor received a baccalaureate degree in structural and functional neurobiology from Eötvös Loránd University in Budapest and a Ph.D. in neurobiology from Semmelweis University in Budapest, where she studied the ultrastructure of inhibitory synaptic innervation of the mammalian thalamus.

JoAnn Buchanan, Ph.D. Candidate | Sr. Research Associate

"How a large scale EM dataset led to novel discovery about glia"

JoAnn joined the Neural Coding - Electron Microscopy team in 2014. With more than 30 years of experience in electron microscopy, she works to push forward the field of connectomics. JoAnn spent 25 years at Stanford University doing research and teaching. Prior to that, she worked at Harvard, Yale and Boston University Medical Schools. She has also participated as a faculty member in the Neurobiology course at the Marine Biological Laboratory in Woods Hole, MA for many summers. She has worked on a large variety of organisms including fruit fly, leech, mouse, rat, squid, sea slug, mosquito, firefly and human. JoAnn received her Cell Biology from Northeastern University and is currently pursuing a Ph.D. in Biology at the same institution.

Michael Buice, Ph.D. | Associate Investigator

"Functional Computation in the Mouse Visual Cortex"

Michael Buice is a member of the modeling, analysis, and theory team at the Allen Institute, where he explores the implications of theories of neural processing and contributes to mathematical and data analysis. Before arriving at the Allen Institute, Buice worked in the lab of Ila Fiete at the University of Texas at Austin, where he helped derive a system size expansion for the Fisher Information for sensory and working memory systems, and developed analytic expressions for the fluctuations in attractor network models of neural networks. He held a postdoctoral research position in Carson Chow's group at the Laboratory of Biological Modeling at the National Institutes of Health (NIH). There, Buice applied kinetic theory and density functional theory to oscillator models of neural networks, answering open questions regarding the stability of asynchronous firing states in networks of finite size, a dynamical phenomenon related to the information present in the network. In addition, Buice helped construct a method for deriving equivalent reduced stochastic equations for systems with "incomplete information", such as an interacting network of neurons in which only a few neurons are actually recorded. Buice earned a Ph.D. in physics from the University of Chicago working with Jack Cowan to adapt techniques from the analysis of reaction-diffusion systems in physics to the statistics of simple models of neural networks.

Forrest Collman, Ph.D. | Assistant Investigator

"Introduction to the MICrONS Explorer"

Forrest Collman is an assistant investigator working at the Allen Institute within the Human Cell Types group with Stephen Smith. He received his undergraduate training in physics from Princeton University, where he did his senior thesis with John Hopfield on computational models of olfaction using synchrony. He then did a Ph.D., also at Princeton, but within the Molecular Biology department where he worked with David Tank, helping developing methods for two-photon microscopy in awake behaving mice, as well as the design and construction of a virtual reality behavioral environment for head-fixed mice. Before joining the Allen Institute, he was a postdoc, also with Stephen Smith, at Stanford University, where he worked on the development of conjugate IF/SEM array tomography and its application to neural plasticity.

Saskia de Vries, Ph.D | Associate Investigator

"Introduction to the Allen Brain Observatory" and Allen Brain Observatory Tutorial

Saskia de Vries joined the Allen Institute in 2012 as a scientist in the neural coding team. With a background in systems neuroscience, she has studied visual processing in both vertebrate and invertebrate systems using a combination of physiological, computational, behavioral and molecular tools to parse how neural circuits process visual information and use that information to select appropriate behavior. Prior to joining the Allen Institute, de Vries was a postdoctoral scholar in the department of neurobiology at Stanford University, where she identified loom sensitive neurons in the optic lobe of the fruit fly and directly linked them to the fly's escape behavior. De Vries received a B.S. from Yale University in molecular biophysics and biochemistry and a Ph.D. in neurobiology from Harvard University.

Leila Elabaddy, Ph.D. Candidate

MICrONS Explorer Tutorial

Leila currently works as part of the Institute’s Synapse Biology team, concentrating in the Imaging and Processing subgroups. The team is working towards reconstructing synaptic networks in large volumes of the brain using Array Tomography. Leila's role within this workflow involves preparing, staining, and imaging the tissue samples. Once the data is collected, Leila is involved in the image processing, 3D volume reconstruction, and alignment. Prior to the Institute she worked in the Gobes Lab at Wellesley College where she earned a B.S. in Neuroscience. While focused on synaptic changes associated with birdsong learning in Zebra Finches, Leila spent time in the Hahnloser Lab at ETH Zurich investigating the inhibitory/excitatory balance of single and multiple synapse boutons. Overall, her interests encompass both synaptic network research as well as data science applications to global health issues.

Rohan Gala, Ph.D. | Scientist II

"Consistent cross-modal identification of cortical neurons with coupled autoencoders"

Rohan Gala joined Allen Institute as a Scientist I in 2018. His research is aimed at analyzing multimodal observations of brain cells to understand neuronal identity. He obtained his PhD in Physics from Northeastern University where he studied statistical models of associative learning, and designed computational tools to analyze neuron connectivity and morphology. Rohan completed his undergraduate studies in Engineering Physics from IIT Bombay (Mumbai, India).

Rebecca Hodge, Ph.D. | Assistant Investigator

“Cell type diversity in human cerebral cortex revealed by single nucleus RNA-seq” and Allen Cell Types Database Tutorial

Rebecca Hodge joined the Allen Institute as a Scientist II in the Human Cell Types program in March of 2014. Prior to joining the Institute, she conducted research in the laboratory of Dr. Robert Hevner at the University of Washington and the Center for Integrative Brain Research at Seattle Children’s Research Institute. There, she studied the actions of transcription factors during the process of neurogenesis (the generation of neurons) in both the developing and adult brain. She completed herundergraduate training at Simon Fraser University in Burnaby, British Columbia where she received a Bachelor’s degree (B.Sc.) in animal physiology. Her graduate training was completed in the Department of Pathology and Laboratory Medicine at the University of British Columbia (UBC) in Vancouver, BC. Her Ph.D. work at UBC focused on the role of growth factors in regulating neural stem cell development and the generation of neurons during early development of the mammalian cerebral cortex.

Xiaoxuan Jia, Ph.D. | Senior Scientist

"Tracking information flow in mouse visual areas"

Dr. Xiaoxuan Jia received her B.S. in Biological Sciences and Biotechnology from Tsinghua University in 2005. Dr. Jia then obtained her Ph.D. in Systems Neuroscience from Albert Einstein College of Medicine, where she studied brain oscillations and visual processing in early visual areas of non-human primates in Dr. Adam Kohn’s lab. Her Ph.D. work won the Julius Marmur Research Award for outstanding graduate research. Dr. Jia pursued postdoc training in Dr. James DiCarlo’s lab at MIT to investigate the neural mechanisms underlying tolerant object recognition behavior from the aspect of unsupervised learning (uninstructed learning). After postdoc, Dr. Jia joined Allen Institute for Brain Science in 2016, where she led various projects to investigate visual sensory processing in behaving mice with multi-area, large-scale electrophysiology recordings. Dr. Xiaoxuan Jia’s long term interest is to understand the fundamental principles of visual information representation and propagation, and how they shape perception and behavior.

Nik Jorstad, Ph.D. | Scientist I

“Single-nucleus RNA-seq profiling of middle temporal gyrus across the great apes and monkeys”

Nik joined the at the Allen Institute in May 2019 as a Scientist working on the Human Cell Types team. His research is focused on developing analytical tools and drawing biological insight to characterize all the cells that make up the human brain.
Nik received his BA in Biochemistry from the University of Washington in June 2012. After graduating, Nik began his career as a research scientist in the labs of Drs. Thomas Montine and C. Dirk Keene at the University of Washington studying Alzheimer’s, Parkinson’s, and other neurodegenerative disorders. During these 3 years, Nik developed skills in automated image analyses, electrophysiology, surgical techniques, and various molecular biological assays, as well as microscopy expertise. He was also an autopsy technician for 5 years and performed over 100 human brain removals and dissections in support of the ADRC, ACT, and PANUC studies, among others.
Following his research scientist position, Nik joined the Molecular Medicine and Mechanisms of Disease PhD program in the Department of Pathology at the University of Washington. His dissertation work was performed in the lab of Dr. Thomas Reh studying mammalian retinal regeneration. During his PhD, Nik gained expertise in various molecular biological techniques, including epigenetic assays, single-cell RNA-sequencing, and advanced confocal and electron microscopy. He earned his PhD in May 2019 and was the first to show that adult mice can regenerate functional retinal neurons from Muller glial cells. 

Peter Ledochowitsch, Ph.D., Dipl.-Phys. | Senior Scientist

“A tale of two methods: can we reconcile two-photon calcium imaging with extracellular electrophysiology?”

Peter Ledochowitsch is currently a Scientist II in the Department of Modeling, Analysis, and Theory (MAT), working with Michael Buice. Prior to that, Peter has been developing instrumentation as a Research Engineer III in the Department of Research Engineering under Peter Saggau. Peter originally joined the Allen Institute in 2014 as a Scientist I working with Timothy J. Blanche in the Department of Neural Coding.
Peter earned a Joint Ph.D. in bioengineering from the University of California, Berkeley and from the University of California, San Francisco, where he was co-advised by Dr. Michel M. Maharbiz and Dr. Jose M. Carmena.  Peter’s Ph.D. work focused on the development of electrocorticographic microelectrode arrays, and on their application to functional brain mapping and brain-machine interfaces. He also earned a Management of Technology certificate from Haas Business School, and co-founded the medical device start up Cortera Neurotechnologies, Inc.
Peter holds a Dipl.-Phys. in physics with a minor in chemistry from the Georg August University in Göttingen (Germany). His thesis research on organic field effect transistors, was completed externally under the supervision of Dr. Alan J. Heeger at the University of California, Santa Barbara.

Maitham Naeemi | Data Analyst II

CCF Tutorial

Lydia Ng, Ph.D. | Investigator

"The Allen Mouse Brain Common Coordinate Framework: A 3D reference atlas enabling data integration" and CCF Tutorial

Lydia Ng joined the Allen Institute in 2004 and has been a technical leader in the full spectrum of product development, delivering innovative and impactful neuroscience data, tools and knowledge to our user community. Ng is also involved in community efforts to standardize and integrate neuroscience data. She is currently the Senior Director of Architecture for Allen Institute for Brain Science products covering ontologies, taxonomies, data access, workflows and user interface. Her research background includes image processing and analysis, image registration, data analysis and mining. Ng received a B.E. in electrical engineering and a B.Sc. in computer science from the University of New South Wales (Sydney, Australia) and a Ph.D. in electronics at Macquarie University (Sydney, Australia).

Casey Schneider-Mizell, Ph.D. | Scientist II

MICrONS Explorer Tutorial

Casey is a Scientist II in the Neural Coding group of the Institute for Brain Science, working with Clay Reid and Nuno da Costa to understand the structure of cortex at synaptic resolution. He did his postdoctoral work in the lab of Albert Cardona, first at the Institute for Neuroinformatics in Zürich and then at HHMI Janelia Research Campus outside of Washington, DC. Within a tight collaboration between the Cardona lab and Marta Zlatic’s group, also at Janelia, he worked on combining large scale electron microscopy, functional experiments, and computational analysis and modeling to understand the neural basis of behavior in the compact nervous system of Drosophila larva.
Before developing a focus on questions in neuroscience, he received his BS in physics and mathematics at the University of Washington in Seattle and continued to a Ph.D. in physics at the University of Michigan, Ann Arbor. Casey's graduate research with Len Sander spanned diverse topics in physics and complex systems, including stochastic processes on networks, adult neurogenesis, and cancer cell motility. 

Sharmi Seshamani, Ph.D. | Scientist II

MICrONS Explorer Tutorial

At the Allen Institute for Brain Science, Sharmishtaa Seshamani is working in the Human Cell Types group. Her current research focuses on building a data processing pipeline to facilitate the imaging of neurons in the brains of mouse and human brain samples in order to reveal important details about the morphology and connectivity of neural circuits. She received her Ph.D. in Computer Science from Johns Hopkins University where she focused on developing meta registration and mosaicking techniques for endoscopic imaging. Prior to joining the Allen Institute for Brain Science, she was a Senior Fellow at the Biomedical Image Computing Group in the University of Washington. There, she was working on a pipeline for fetal fMRI analysis which included algorithms for MRI artifact correction (bias and spin history), motion estimation and reconstruction.

Josh Siegle, Ph.D. | Assistant Investigator

"Introduction to the Allen Brain Observatory" and Allen Brain Observatory Tutorial

Josh Siegle joined the Allen Institute in 2014 as part of the Neural Coding research program. He received his PhD in Neuroscience from MIT, where he studied hippocampal circuits with Dr. Matthew Wilson and cortical and thalamic circuits with Dr. Christopher Moore. In both labs, he combined optogenetics and extracellular electrophysiology in order to investigate the impact of neural oscillations on behavior. In addition to his scientific work, Josh has been heavily involved in the design and distribution of open-source tools for electrophysiology. He co-founded Open Ephys in order to centralize some of the development efforts occurring across the community. Josh has also carried out research at the Max Planck Institute for Biological Cybernetics and Brown University, where he earned an Sc.B. in Neuroscience.

Bosiljka Tasic, Ph.D. | Director, Molecular Genetics

"Introduction to the Allen Cell Types Database"

Bosiljka Tasic joined the Allen Institute in 2011 as one of the founding members of the Mouse Cell Types program to establish methods for studying cell-type specific neuronal connectivity. She currently leads an effort toward comprehensive molecular analysis of neuronal identity in the mouse visual system. Before joining the Allen Institute, Bosiljka completed her postdoctoral training with Liqun Luo at Stanford University, where she developed molecular genetic techniques for labeling and manipulation of specific neuronal populations or single neurons in Drosophila and mice, and a new method for site-specific transgenesis in mice. Bosiljka received a Bachelor's degree in biochemistry from the University of Belgrade (once Yugoslavia, now Serbia), and a Ph.D. in biochemistry and molecular biology with Tom Maniatis at Harvard University, where she studied mechanisms of vertebrate-specific protocadherin gene expression in the nervous system and their role in neuronal identity.