Event Calendar

UPCOMING KCN EVENTS



2019





Lots of upcoming computational neuroscience events in May at the Canadian Neuroscience Meeting (CAN) in Toronto






KCN events will return in Fall 2019 

with 
Stephanie Jones (Brown) 


and more....

PAST KCN EVENTS



2019
 


Support for this KCN event is generously provided by the Fields Institute as part of the 2018-2019 Centre for Mathematical Medicine (CMM) Seminar Series

Date: Thursday, April 11th, 2019

Time: 10:30am
Location: Fields Institute, Stewart Library
Title: Inhibition-based theta resonance in a hippocampal network
Speaker: Horacio Rotstein (Rutgers/NJIT)
ABSTRACT:  A crucial issue in the understanding of neuronal oscillations is to elucidate the microcircuits that are the substrate to these rhythms in the different brain areas. This raises the question of whether rhythmic activity results solely from the properties of the network connectivity (e.g., excitation and inhibition) and topology or it involves the interplay of the latter with the intrinsic properties (e.g., ionic currents) of the participating neurons. In this project we address this issue theoretically in the context of the hippocampal area CA1 microcircuits, which include excitatory (PYR) and inhibitory (INT)  cells. It has been observed that PYR exhibit a preferred subthreshold frequency response to oscillatory inputs at (4 - 10 Hz) frequencies (resonance) 'in vitro'. Contrary to expectation, these cells do not exhibit spiking resonance in response to 'in vivo' direct oscillatory optogenetic activation, but, surprisingly, spiking resonance in PYR occurs when INT are activated. We combine dynamical systems tools, biophysical modeling and numerical simulations to understand the underlying mechanisms of these rather unexpected results. We show that the low-pass filter results form a combination of post-inhibitory rebound (the ability of a cell to spike in response to inhibition) and the intrinsic properties of PYR. The band-pass filter requires additional timing mechanisms that prevent the occurrence of spikes at low frequencies. We discuss various possible, conceptually different scenarios. These results and tools contribute to building  a general theoretical and conceptual framework for the understanding of preferred frequency responses to oscillatory inputs in neuronal networks.

BIO: Horacio G. Rotstein received his PhD from the Technion (Israel Institute of Technology) in Applied Mathematics. He carried out postdoctoral research in chemical oscillations, mathematical and computational neuroscience first at Brandeis University and then at Boston University. After a couple of years as research faculty he moved to the Math Department at NJIT where he became a Professor.  He is currently a Professor in the Federated Department of Biological Sciences at NJIT / Rutgers University and a graduate faculty member in the Behavioral Neurosciences program at Rutgers University.





PROMOTED TALK:
Krembil Seminar Series

Date&Time: Friday, March 8th, 2019 at 1:00 pm

Location: Main Auditorium, West Wing2nd floor, Room 401, Toronto Western Hospital

Title:  Scientific and personal “integrations”: A story of an inhibitory cell and “virtual” networks

Speaker:  Frances Skinner (Krembil)






PROMOTED TALK:
Krembil Seminar Series

Date&Time: Friday, March 1st, 2019 at 1:00 pm

Location: Main Auditorium, West Wing, 2nd floor, Room 401, Toronto Western Hospital

Title: Organization and control of hippocampal circuits.

Speaker:  Ivan Soltesz (Stanford)






Date: Thursday, Feb 21st, 2019
Time: 10:30 am
Location: Room 4KD503, Krembil Discovery Tower
Title: Bridging computational neuroscience and genomics in the era of big data
Speaker: Shreejoy Tripathy (KCNI/CAMH)

Abstract: With each day we are learning more and more about which genes and gene variants are associated with increased risk for disorders such as epilepsy, autism, and depression. However, genetics alone provides little clue about how genes contribute to altered functioning of neurons and circuits. In this talk, I will share my ongoing efforts to understand how genetics and gene expression give rise to neuronal electrophysiology and morphology. One aspect of this work is Patch-Seq, a novel method for sampling gene expression, electrophysiology, and morphology from the same cell. In addition, I will describe recent collaborative work with the Valiante Lab that correlates patient-specific demographics with the electrophysiological features of human pyramidal cells. I will end the talk by illustrating my vision for how multi-scale modeling of patient-specific genetics and brain circuits can help contribute to novel therapeutics for neuropsychiatry.
Bio: Dr. Shreejoy Tripathy leads the Laboratory for Computational Genomics (https://triplab.org) at the Krembil Centre for Neuroinformatics. He is an Independent Scientist at the Centre for Addiction and Mental Health and is an Assistant Professor in the Department of Psychiatry at the University of Toronto. He did his Post-Doc in Bioinformatics at the University of British Columbia and received his PhD in Computational Neuroscience from Carnegie Mellon University.




Date: Thursday, Jan 24th, 2019
Time: 10:30 am
Location: Room 4KD503, Krembil Discovery Tower
Title: Modelling the mechanisms of visual maps formation and alignment in the midbrain
Speaker: Michael Reber (Krembil)

Abstract: The Superior Colliculus (SC), a conserved structure located in the midbrain, receives visual, auditory and somatosensory inputs and is involved in the control of attention. Visual information in the SC is provided by retinal and V1 cortical projections that must be aligned and in register. Our lab characterized and modelled the molecular mechanisms controlling mapping in the SC. These mechanisms are composed of sequential steps involving gradients of tyrosine kinase receptors Eph and their ligands ephrins, transport of ephrin ligands and correlated neuronal activity. Altogether, these mechanisms allow the topographic mapping of the retinal projections in the SC and subsequent alignment of the V1 projections.


Bio: Trained as a geneticist (PhD) at University Denis Diderot in Paris, I moved to the Salk Institute in Dr. G. Lemke’s lab as a research associate in 2000. Assistant/associate professor at CNRS – Institute for Cellular & Integrative Neurosciences in Strasbourg, FR from 2005-2018. Senior scientist at Donald K. Johnson Eye Institute, Krembil since April 2018.

Publications related to this talk: Savier E. et al, 2017; Hjorth J.J. et al., 2015; Bevins N. et al., 2011; Reber M. et al., 2004.







2018



Date: Thursday, Nov 22nd, 2018
Time: 10:30 am
Location: Room 4KD503, Krembil Discovery Tower
Title: An Introduction to Bayesian-based Estimation and Tracking Techniques, Application to Multi-Scale Brain Modeling 
Speaker: Milad Lankarany (Krembil)


ABSTRACT: Bayesian-based estimation techniques are powerful tools for nonlinear filtering, i.e., the process of estimating and tracking the state of a non-linear stochastic system from non-Gaussian noisy observation data. Bayesian-based estimation techniques require integration over probability density functions of the (hidden) states, e.g., dynamics of ionic currents in a single neuron, and the observation, e.g., recorded membrane potential. In the most practical scenarios, this integration cannot be calculated in closed form, so approximations are required. In this talk, first, we present the development of a general Bayesian approach to filtering stochastic systems. Second, we introduce different Bayesian-based techniques to approximate probability density functions underlying these systems. Finally, we apply well-known Kalman filtering approach to estimate the parameters and track the states (hidden) of two toy models, namely, (1) Hodgkin-Huxley model of a single neuron, and (2) Jansen-Rit model of population of neurons.

BIO: Milad Lankarany is a principal investigator (PI) at the Krembil Research Institute – University Health Network (UHN). Milad completed his PhD in Electrical and Computer Engineering at Concordia University, Montreal, QC (2010 – 2013) and continued his postdoctoral training (2014-2017) in Theoretical and Experimental Neuroscience at The Hospital for Sick Children (SickKids). In addition, he spent a year at a Neuro-technology company developing circuits to record electrical activity in different parts of the body, as well as the methods to analyze these complex recordings. 
The main focus of Dr. Lankarany’s lab is to uncover information processing mechanisms of neural systems. Dr. Lankarany uses advanced methods in computational neuroscience and engineering, as well as cutting-edge Neuro-technology to uncover information processing mechanisms of neural systems, in order to treat neurological disorders and to advance biologically-inspired computational frameworks.






PROMOTED TALK:
Krembil Seminar Series

Date&Time: Friday, November 9, 2018 at 1:00 pm

Location: Main Auditorium, West Wing2nd floor, Room 401, Toronto Western Hospital

Title: Computational Modelling of Brain Rhythms and Brain Stimulation at the Meso-scale: Overview and Applications in Neurology and Neuropsychiatry

Speaker:  John Griffiths (Krembil)



Support for this KCN event is generously provided by the Fields Institute as part of the 2018-2019 Centre for Mathematical Medicine (CMM) Seminar Series

Date: Wednesday, Oct 24th, 2018

Time: 2pm
Location: Toronto Western Hospital Main Auditorium, West Wing, 2nd floor, Room 401
Title: Applications of techniques in mathematics and statistics to study human seizures
Speaker: Mark Kramer (Boston)

ABSTRACT: Epilepsy - the propensity toward recurrent, unprovoked seizure - is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. In this talk, we will examine some aspects of this challenge through the analysis and modeling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We will focus on two proposals: (1) that human seizure terminate in a critical transition, and (2) that rapidly propagating waves of activity sweep across the cortex during seizure. In each case, we will describe a corresponding computational model to propose specific mechanisms that support the observed spatiotemporal dynamics.

BIO:  Following graduate and postdoctoral training in physics, dynamical systems, and neuroscience, Professor Kramer joined the Department of Mathematics and Statistics at Boston University. His research focuses on interdisciplinary topics in computational neuroscience with particular emphasis on mathematical models of neural activity and data analysis techniques. He is currently interested in medical applications and networks in neuroscience



PROMOTED TALK:

Date: Tuesday, June 26th, 2018
Time: 3pm
Location: Room 4KD503, Krembil Discovery Tower
Title:  Transcriptomic profile, connectivity and role in memory encoding of long-range VIP GABAergic neurons
Speaker:  Lisa Topolnik (Laval)

Dr. Topolnik is a researcher at the Centre de recherche du CHU de Québec and professor at the Department of Biochemistry, Microbiology and Bio-informatics of Laval University’s Faculty of Science and Engineering.  Dr. Topolnik is a recipient of the University Faculty Award for Women in Science and Engineering from the Natural Science and Engineering Council of Canada (NSERC) and a “Professor-Star Award” from Laval University’s Faculty of Science and Engineering.

Dr. Topolnik’s research program focuses on the cellular and synaptic mechanisms involved in the coordination and processing of information by the cortical circuits. Her team explores how sensory information is integrated and modified by the GABAergic inhibitory interneurons, and how these processes are altered in neurological and neurodegenerative disorders, in particular, epilepsy, Alzheimer’s disease, and amyotrophic lateral sclerosis.



PROMOTED TALK:
Krembil Seminar Series

Date: Friday, June 15th, 2018
Time: 1pm
Location: Toronto Western Hospital Main Auditorium, West Wing, 2nd floor, Room 401
Title: The multisensory scaffold of perception and rehabilitation
Speaker: Micah M Murray (Lausanne)

BIO: Micah Murray is a cognitive neuroscientist. He obtained his BA from The Johns Hopkins University and his MS and PhD in neuroscience from the Albert Einstein College of Medicine. Dr Murray is also the director of The LINE (Laboratory for Investigative Neurophysiology) and the EEG Brain Mapping Core of the Centre for Biomedical Imaging (CIBM). He is also an adjunct professor at the University Hospital Center & University of Lausanne, Switzerland. He is Editor-in-Chief of Brain Topography, section editor at Neuropsychologia, and handling editor at Neuroimage. He also serves on the editorial board of Current Biology.




PROMOTED TALK:

Nancy Kopell, PhD
William Fairfield Warren Distinguished Professor, Mathematics & Statistics, Boston University
Director, Cognitive Rhythms Collaborative, and Co-Director, CompNet

Rhythms, routing, resonance and rule-based decisions—Distinguished Seminar IBBME

May 7, 2018 @ 5:00 pm – 6:00 pm

Fields Institute for Research in Mathematical Sciences, 

Room 222 College St

This talk is co-hosted with the Fields Institute for Research in Mathematical Sciences.

Abstract: Brain rhythms are thought (by some) to be essential for many kinds of cognitive activity, especially communication among different areas of the brain.  In this talk, I will discuss mechanisms of resonance to input frequencies and a role of resonance in filtering and routing of signals, especially when the target network has strong inhibitory feedback. The ideas are discussed in the context of dynamics in the dorsolateral prefrontal cortex and rule-based decisions, with inputs from the anterior cingulate cortex.  I will also talk about how top-down signals to the striatum can bias activity between go and no-go pathways depending on the frequency of the signals.








































Date: Thursday, April 19th, 2018
Time: 10:30am
Location: Toronto Western Hospital Main Auditorium, West Wing, 2nd floor, Room 401
Title: Building an intellectual prosthesis - avoiding paralysis of analysis
Speaker: Igor Jurisica (Krembil)

ABSTRACT: To fathom complex disease development processes, we need to systematically integrate diverse types of information and link them using relevant annotations and relationships, leading to meaningful modeling. Application of graph theory, data mining, machine learning and advanced visualization enables data-driven, precision medicine. This process also supports focused, faster and more economical experiments.

BIO: Igor Jurisica is a Senior Scientist at Krembil Research Institute, Professor at U Toronto and Visiting Scientist at IBM CAS. He is also an Adjunct Professor at the School of Computing, Pathology and Molecular Medicine at Queen's U, Computer Science at York U, an adjunct scientist at the Institute of Neuroimmunology, Slovak Academy of Sciences and an Honorary Professor at Shanghai Jiao Tong University. Since 2015, he has also served as Chief Scientist at the Creative Destruction Lab, Rotman School of Management. He has published extensively on data mining, visualization and cancer informatics, including multiple papers in Science, Nature, Nature Medicine, Nature Methods, J Clinical Oncology, and has over 11,336 since 2013, including 558 highly influential citations (SemanticScholar). He has been included in Thomson Reuters 2016, 2015 & 2014 list of Highly Cited Researchers, and The World's Most Influential Scientific Minds: 2015 & 2014 Reports.




PROMOTED TALK:
Center for Mathematical Medicine Seminar Series

Wednesday, April 25th, 2018
11:00 to 12:00
Frances Skinner, Krembil Research Institute, University Health Network
Location:Fields Institute, Room 230
Speaker: 
Frances Skinner, Krembil Research Institute, University Health Network

 

Abstract: Although we have long known that our brains produce oscillations, we do not have a clear understanding of how they are generated. One of the main reasons for this stems from the multi-scale and multi-temporal nature of our brains. This makes it highly challenging to be able to obtain explanations for how oscillatory activities are produced. However, we need to address this challenge as it is becoming clear that oscillatory activities underlie brain function and they change during disease. In this talk I will describe how we are tackling this challenge by tightly linking models and experiments so that mathematical model development and usage can help lead to explanations. Our present focus is on a prominent rhythm involved in memory processing – theta rhythms in the hippocampus.




PROMOTED TALK:
Center for Mathematical Medicine Seminar Series

Wednesday, March 14th, 2018
11:00 to 12:00
Jesse Gillis (Cold Spring Harbor Lab)
Location:Fields Institute, Room 230
Speaker:  Jesse Gillis (Cold Spring Harbor Lab)
 

Abstract: Research in my lab involves two interwoven elements: improving the interpretability of network analysis and characterizing transcriptional data in the brain. These topics form a naturally complementary unit because the complexity of the brain as a system means that it is essential that the methods for analyzing it yield clear and precise signals. A dominant interest within computational biology is the analysis of gene networks to provide insight into diverse levels of functional activity, typically starting with regulatory interactions and moving up to more diffuse associations important for understanding systemic dynamics. Gene associations (of various sorts) are believed to encode functional interaction, and this interaction is frequently shown to be able to substantially predict gene function. In this talk, I will demonstrate the power of gene networks determined from shared expression profiles to understand phenotype. I will focus on an a number of unusually well-defined cases, including individual neurons, rare diseases, (outbred) genetic replicates, and largescale populations. In each case, using the observed co-expression of genes to filter complex data for its most important functional properties will yield clear signals that precisely characterize phenotype.







The Krembil Computational Neuroscience (KCN) Winter Series
This Winter Series of 5 KCN events consisted of selected lectures from a seminar-style graduate course in Computational Neuroscience 

Day (same): Thursdays
Time: 1:30pm (note different time from previous KCN events!)
Location (same): Room 4KD503, Krembil Discovery Tower, 60 Leonard Ave., Toronto


January 25, 2018
Topic: Mean field/firing rate models
Speaker: Sue Ann Campbell (Waterloo)
Bio: Sue Ann Campbell is a Professor of Applied Mathematics, with a cross-appointment to the Department of Biology, at the University of Waterloo. She received her BMath (Applied Mathematics) from the University of Waterloo and her PhD (Theoretical and Applied Mechanics) from Cornell University.  She currently serves on the Editorial Boards for SIAM Journal on Applied Mathematics, Journal of Nonlinear Science and Journal of Mathematical Neuroscience. Her research interests include dynamical systems, especially delay differential equations, with applications in neuroscience especially the generation of rhythms.


February 8, 2018
Topic: Dynamical analysis of neuronal excitability
Speaker: Steve Prescott (Sickkids)
Bio: Steve Prescott is a Senior Scientist at SickKids and an Associate Professor in Physiology and Biomedical Engineering at the University of Toronto. He obtained his MD and PhD in pharmacology from McGill University before pursuing postdoctoral training in computational neuroscience at the Salk Institute. He relocated to Toronto in 2012 after establishing his own lab at the University of Pittsburgh. His lab combines computational modeling with neurophysiological experiments that seek to uncover the neural basis for information processing. He is particularly interested in understanding how somatosensory information is processed, and how pathological disruption of that processing contributes to neuropathic pain. 

 

March 1, 2018
Topic: Reinforcement learning in sensorimotor networks
Speaker: Doug Tweed (Toronto)
Bio:  Douglas Tweed is a Professor in the Department of Physiology at the University of Toronto. He got an MD from the University of Manitoba and a PhD in physiology and an Honours diploma in mathematics from the University of Western Ontario, and did his postdoctoral work at Tübingen University. He studies the computational principles of control and learning in sensorimotor systems.
https://sites.google.com/site/krembilcompneuro/event-calendar/LRSc-103.JPG


March 15, 2018
Topic: The probabilistic brain: A (hopefully) gentle introduction to population coding and related questions
Speaker: Jeremie Lefebvre (Krembil)
Bio: Jeremie Lefebvre is a Scientist at the Krembil Research Institute and an Assistant Professor of Mathematics and Biomedical Engineering at the University of Toronto. He obtained a PhD in Physics at the Center for Neural Dynamics of the University of Ottawa in 2010 under the supervision of André Longtin and Victor LeBlanc. He then left Canada to pursue postdoctoral research in Geneva and Lausanne, where he worked on probabilistic population coding and the dynamics of perception. His lab develops analysis tools to investigate neural circuits and their dynamics, in order to understand the correlation between brain activity, neural coding and cognitive processes. Using a combination of experimental data, simulations, and dynamical systems approaches, Prof Lefebvre investigates how noise and non-linearity shape the complexity of brain functions. Notably, his team interfaces models and experimental data to learn how to use brain stimulation to route information in the brain, control neural synchronization and ultimately manipulate cognition.


March 29, 2018
Topic: Biological variability and model databases
Speaker: Frances Skinner (Krembil)
Bio: Frances Skinner is a Senior Scientist at the Krembil Research Institute and a Professor at the University of Toronto. She graduated from the University of Waterloo (B.Math.) and Toronto (M.A.Sc., Ph.D.) and did 4 years of postdoctoral work in Boston and California. She enjoys collaborative work and is interested in determining cellular-based mechanisms underlying the dynamic output of neuronal networks in normal and pathological states.  She is particularly interested in advancing our understanding by creating win-win scenarios with the plethora of data and theoretical and experimental approaches available today.



2017

Date: Thursday November 23rd, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower, 60 Leonard Ave., Toronto
Title: 
Blue Brain Nexus: A knowledge graph for data-driven science
Speaker: Sean Hill (CAMH)

ABSTRACT: Blue Brain Nexus is a domain-agnostic data and knowledge management platform that enables the registration, tracking, search, discovery and integration of heterogeneous datasets. Users can register new data models in the platform and extend existing ones. Models are expressed in the Shapes Constraint Language (SHACL) from the W3C, which enables validation of Resource Description Framework (RDF) data models. By supporting full provenance tracking for all entities, Nexus also allows rich contextual descriptions of datasets and models that are essential for discoverability, reproducibility, reuse, quality assessment and attribution. Nexus is built on modern, open, scalable web technologies and standards (REST, W3C PROV, SHACL, ElasticSearch, BlazeGraph) and will be released under an open source license. While Nexus is designed to be domain agnostic, we have developed domain specific metadata schemas to support neuroscience datasets including electrophysiology, morphology and brain atlases. These schemas can reuse or extend community defined schemas (e.g. schema.org or bioschema.org) and ontologies (e.g. brain parcellation schemes, cell types, taxonomy). Nexus validates all submissions according to these schema and their related ontologies.  This enables neuroscientists and modelers to discover data, models and literature according to metadata properties such as specimen, protocol, brain region, data type, cell type. It makes it possible to discover datasets via semantic relationships (data produced using similar protocols, common brain regions, similar types of data or models, related cell types). Datasets can also be discovered via provenance relationships (which datasets originated from the same animal, from the same cell, from the same laboratory, or which models were built from specific data). The provenance metadata supports reproducibility by capturing aspects of the experimental design and the protocols, solutions, software, etc that were used to generate the dataset or model. Importantly in the context of team science, Nexus also enables rapid summary of the full attribution of datasets (including institution, PI, postdocs, technicians, students, analysts, curators). Future steps include enabling spatial search and discovery and integration with KnowledgeSpace– a collaborative community-based encyclopaedia linking brain research concepts to the latest data, models and literature.

BIO: Dr. Sean Hill is the inaugural Director of the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH). Prior to this, he was co-Director of Blue Brain, a Swiss brain initiative, where he led the Neuroinformatics division, based at the Campus Biotech in Geneva, Switzerland. Dr. Hill has served as Executive Director and Scientific Director of the International Neuroinformatics Coordinating Facility (INCF) at the Karolinska Institutet in Stockholm, Sweden. Dr. Hill has extensive experience in building and simulating large-scale models of brain circuitry and currently supervises and leads research efforts exploring the principles underlying the structure and dynamics of neocortical and thalamocortical microcircuitry. He also serves in management and advisory roles on several large-scale clinical informatics initiatives around the world. After completing his Ph.D. in computational neuroscience at the Université de Lausanne, Switzerland, Dr. Hill held postdoctoral positions at The Neurosciences Institute in La Jolla, California and the University of Wisconsin, Madison, then joined the IBM T.J. Watson Research Center and served as the Project Manager for Computational Neuroscience in the Blue Brain Project until his appointment at the EPFL.



Date:
Thursday October 19th, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower, 60 Leonard Ave., Toronto
Title: Embracing Variability: Ensemble Modeling in Neuroscience
Speaker: Astrid Prinz (Emory)

ABSTRACT: Computational modeling is an increasingly widespread complement to experimental neuroscience that can, when used in a beneficial feedback loop between experimentation and modeling, add insights into the mechanisms of neuronal circuit operation not accessible by experimentation alone. Traditionally, computational models of neuronal systems were constructed and hand-tuned to achieve a single model version that reproduced experimentally observed behavior and then was progressively refined as new experimental data became available. In recent years, the growing computational power has enabled an alternative to hand-tuning small numbers of model versions – ensemble modeling of large numbers (often millions) of model versions that differ in their parameter settings and produce a variety of outputs. Such model ensembles can be thought of as the in silico equivalent of a biological neuron or circuit type or population and exhibit parameter and output variability analogous to that of living neurons and networks. I will review different approaches to ensemble modeling, including evolutionary algorithms, brute-force computational exploration of high-dimensional model parameter spaces, and the construction, visualization, and analysis of model databases. Applications of these ensemble modeling methods in different neuronal systems have revealed that similar and functional network output can be achieved on the basis of disparate underlying cellular and synaptic parameter combinations, and that neuronal systems often constrain and navigate in their high-dimensional solution spaces by implementing pairwise or higher correlations between specific parameter sets. This suggests that a particular neuron or circuit type is defined by parameter correlation rules rather than by narrowly constrained individual parameter values. The variability in cellular and synaptic properties observed in living neuronal systems may thus be not a bug, but an adaptive feature.
Supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and by R01 NS054911 from NIH/NINDS.

BIO:  Astrid Prinz is an Associate Professor of Biology at Emory University and is currently the President of the Organization for Computational Neuroscience.   She has degrees in Physics and Biophysics from the University of Ulm and Munich Technical University in Germany respectively, and did postdoctoral studies at Brandeis University with Eve Marder.  She has received several honors including a Sloan Research Fellowship and the Winship Distinguished Research Fellowship.



Date: Thursday September 28th, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower, 60 Leonard Ave., Toronto
Title: Optimized coding of natural stimuli in sensory systems
Speaker: Maurice Chacron (Ottawa)

ABSTRACT: Understanding how the brain processes sensory input in order to give rise to perception and behavior remains a central problem in systems neuroscience. Growing evidence shows that the general strategies employed are strongly dependent on the statistics of sensory input as encountered in the environment that the organism evolves in (i.e., the “natural” environment). In this talk, I will summarize our recent progress towards understanding how the electrosensory system of weakly electric fish and the vestibular system of non-human primates encode sensory input encountered in the animal’s natural environment. While, at first glance, these two systems could not be any more different from one another, I will illustrate that the guiding principles by which they process sensory input are similar. In particular, I will focus on the following three questions: 1) Are coding strategies optimized to process natural sensory input? 2) What are the underlying mechanisms? 3) What are the functional roles of correlations in population coding? Throughout, I will emphasize how a combination of electrophysiological recordings together with computational data analysis, mathematical modelling, and behavioral approaches across multiple species has allowed us to make significant progress towards uncovering general applicable principles by which natural sensory stimuli are processed as well as the underlying mechanisms.

BIO: Dr. Maurice J. Chacron received his PhD in Physics from the University of Ottawa in 2003. After a post-doctoral fellowship at the University of Oklahoma, he joined McGill University's physiology department in 2006 where he is now an associate professor. His research interests focus on how sensory information is processed by the brain in order to lead to perception and behavior. For this, he uses a combination of electrophysiological recordings from awake behaving animals, mathematical modeling, and behavioral approaches. To date, he has published over 74 papers and 4 book chapters. His contributions have focused on a wide range of topics and help us better understand the general principles by which the brain processes sensory input.





Date: Thursday June 8th, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower, 
60 Leonard Ave., Toronto
Title: Burst ensemble multiplexing relates active dendrites with cortical microcircuits
Speaker:  Richard Naud (Ottawa)

ABSTRACT : Cracking the neural code is to attribute proper meaning to temporal sequences of action potentials. While the neural code is typically understood as a set of rules to translate features of the external world into trains of action potentials, anatomical connections show that external input is often combined with internal signals from higher order areas. A popular view poses that this top-down input merely modulates the encoding of bottom-up information, a signal fusion that leads to an information loss with respect to the two individual signals. Based on the known properties of cortical neurons and circuits, we suggest that, instead, both signals are represented simultaneously, in the form of a multiplexed population code consisting of spikes and bursts. We use a computational model of thick-tufted pyramidal neurons that is constrained by data to understand how bottom-up and top-down signals are represented in the spiking activity of a population. We show that top-down signals arriving in distal dendrites are represented by the relative prevalence of bursts, while bottom-up information arriving perisomatically is encoded in the sum of single spikes and bursts. Using a coherence-based information-theoretical analysis, we show that the code can more than double the rate of information transfer, even for rapidly changing signals. We then show that both bottom-up and top-down signals can also be decoded by biologically plausible mechanisms, namely by combining inhibitory microcircuits with short-term plasticity. These results suggest a novel functional role of both active dendrites and the stereotypical patterns with which inhibitory cell types interconnect in the neocortex. Burst ensemble multiplexing, we suggest, is a general code used by the nervous system to flexibly combine two distinct streams of information.

BIORichard Naud is currently an assistant professor at the University of Ottawa. He received his B.Sc. and M.Sc. degrees in Physics from McGill University. During his doctoral studies at EPFL, he designed statistical methods for the automatic characterization of neuronal dynamics. In parallel, he co-organized a Spike-Timing Prediction Challenge for the comparison and benchmarking of mathematical neuron models. After obtaining his Ph. D. in 2011, he developed quasi-renewal theory, which allows to decode neural responses in the presence of adaptation. He then obtained a post-doctoral scholarship of the FRQNT to work with André Longtin, identifying computational roles of active dendrites and inhibition in sensory systems.  Before moving back to Canada, he was hired as a research assistant at the Teschnische Universität in Berlin, where he established computational roles of active dendrites and inhibition in the neocortex.

Richard Naud




Date: Thursday May 11th, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower,
60 Leonard Ave., Toronto
Title: Models of homeostatic regulation in neurons and networks
Speaker:  Eve Marder (Brandeis)


BIO: Eve Marder is the Victor and Gwendolyn Beinfield Professor of Neuroscience in the Biology Department of Brandeis University. Marder was President of the Society for Neuroscience in 2008, and served on the NINDS Council, numerous Study Sections, and a variety of Advisory Boards for institutions in the USA and abroad. Marder is a member of the National Academy of Sciences, the National Academy of Medicine, the American Academy of Arts and Sciences, a Fellow of the Biophysical Society, a Fellow of the American Physiological Society, and a Fellow of the American Association for the Advancement of Science. She received the Miriam Salpeter Memorial Award for Women in Neuroscience, the W.F. Gerard Prize from the Society for Neuroscience, the George A. Miller Award from the Cognitive Neuroscience Society, the Karl Spencer Lashley Prize from the American Philosophical Society, an Honorary Doctorate from Bowdoin College, the Gruber Award in Neuroscience, and the Education Award from the Society for Neuroscience. Marder served on the NIH working group for the Obama BRAIN Initiative. Most recently, she shared the 2016 Kavli Award in Neuroscience.

Marder studies the dynamics of small neuronal networks, and her work was instrumental in demonstrating that neuronal circuits are not “hard-wired” but can be reconfigured by neuromodulatory neurons and substances to produce a variety of outputs. For the past 25 years Marder’s lab has combined experimental work with insights from modeling and theoretical studies. Together with Larry Abbott, her lab developed the programmable dynamic clamp, now used widely in laboratories around the world. Her lab pioneered studies of homeostatic regulation of intrinsic membrane properties, and stimulated work on the mechanisms by which brains remain stable while allowing for change during development and learning. Marder is now studying the extent to which similar network performance can arise from different sets of underlying network parameters, opening up rigorous studies of the variations in the individual brains of normal healthy animals.



Date:
Thursday April 13th, 2017
Time: 10:30am
Location: Room 4KD503, Krembil Discovery Tower
60 Leonard Ave., Toronto
Topic: Large scale brain simulations
Title:
 
Modelling brain dynamics at rest - practical tools and theoretical perspectives
Speaker:  John Griffiths (Baycrest)

BIO: Dr. John Griffiths is a postdoctoral fellow in the McIntosh Lab at the Rotman Research Institute. He has degrees in psychology and cognitive neuroscience from Universities of Cambridge, Warwick, and York, UK, and is an honorary associate of the University of Sydney Center for Complex Systems. His current work focuses on studying brain changes in ageing and neurological disease using a combination of neuroimaging, computational modelling, and theoretical neurobiology.