Computational Neuroscience Working Group

Working Group Leads: Kanaka Rajan (kanaka.rajan@mssm.edu) & Terry Sanger (terry@sangerlab.net)

 

Goals and Objectives:

The key issue of neuroscience is to understand how different cellular, network and systems neural mechanisms are integrated across multiple levels of organization to produce motor behavior and adapt this behavior to various external and internal conditions. Therefore, multiscale modeling is a tool of critical importance for neuroscience. Quantitative multi-scale models can help us to understand the complex brain mechanisms and processes as well as to assist in generating experimentally testable hypotheses and in selecting informative experiments. The development realistic models of different brain function is a major challenge in the field.

This working group focuses on multiple scale analysis and simulation of neural systems and processes with a special emphasis on the cross-level integration of the intrinsic cellular, network, and systems-level brain mechanisms. Our first goal is to accumulate the available up-to-date information on the modeling tools, novel concepts, and major relevant review papers in the field. Our second goal is to promote new collaborations between experimental neuroscientists and mathematicians and modelers involved in the multiscale modeling of brain mechanisms and processes.

 

For related information, please visit the Theories, Models and Methods (TMM) Working Group page.

 

Directory:

 

2023 Meetings and Activities

Relevant Meetings:

  • July 13-14, 2023 - Allen Institute to host upcoming workshop on software modeling tools. Applications are due by February 15, 2023. More information here.

 

Past Meetings and Activities:

-------------------------------------------------------------------------------------------- 2020 -----------------------------------------------------------------------------------------------------------------------

2020 Meetings and Activities:

During the BRAIN Initiative PI Meeting held virtually from June 1 to June 2, 2020 several topics were discussed in a virtual Networking Lounge. The question formulated in this chat was, What are the roadblocks in generating new theories and integrating competing theories in neuroscience? There was a consensus that there was a need to address experimental design in animal behavior, theory validation and development, and integration of models across scales. Here we present a summary of the discussion. Read more about this conversation from our colleagues Antonio Coronel, Nicolas Buitrago, and Fidel Santamaria in the TMM Working Group.

-------------------------------------------------------------------------------------------- 2017 -----------------------------------------------------------------------------------------------------------------------

MSM 2017 (10th Anniversary) Meeting Discussion Items

  • Appropriate levels of details
  • Difficulties of credibility in an area where "outputs" may be cognitive or otherwise hard to get a handle on
  • Use of common tools vs use of generic programs

March 22, 2017 - 1320 MSM CN WG discussion

  • Model sharing -- model genetic organism; sharing vs publishing
    • Policy and sharing statements -- can balance the two; hold on to things till get the IP or get the submissions and get sufficient yields
    • NIH prefers to see sharing but is not blocking monetization so understands IP/patents
    • Sharing helps with finding sign errors and 6.3deg
    • Cf cancer moonshot - Biden said shouldn't be stovepiping their data -- NEJM: "data vampires"
    • People don't want to have other people find their errors
    • Use of common tools vs use of generic programs -- difficulty archiving very specific programs written on a currently 'standard environment'
    • SBML community has evolved the standards -- standards have to evolve but also need backcompatability
    • Standards or widely used platforms
  • MSM modeling -- hard problems of having levels talking to one another
    • Phenomenological vs mechanistic
    • Going between memory systems -- plug hippocampal model into a larger model
    • MUSIC -- stick together module; MPI-based framework originally designed for spike exchange
    • Ideally people should speak the same language -- gene people will not necessarily speak to fMRI people -- how about some translation to make it adaptable to another framework
    • Getting a common language -- 2 diff languages: as people who are modeling constructing models and exchanging
    • What do the experimentalists record and what do they want
    • different professional models -- physicists vs engineering
  • Molecular pathology vs anatomical pathology -- what are the best markers to segregate patients for treatment
    • Elaborate agent-based bioinformatics (Steven Piper)
    • Appropriate levels of details
  • Uses in the clinic
    • DBS -- how to place the electrodes
    • Epilepsy -- the personalized med of epilepsy surgery
  • Credibility of neural models
    • Drug companies can't replicate experiments
    • Reproducibility and rigor
    • Making 100s of models that captures different variance
      complex system
    • Difficulties of credibility in an area where "outputs" may be cognitive or otherwise hard to get a handle on
    • Authentication of bio-agents
    • Make models that are sufficiently complex -- either go thru them with a fine-tooth comb vs reproducing
    • How much reuse is going on -- always easier to reuse than to rebuild
  • The brain is special organ
    • Resistance to 'medicalization' of the brain from those involved in consciousness/cognition studies
    • What do neurolinguists do? -- why don't we do some of that
    • Brain functions in terms of circuits -- this brain area talks to this area talks to this area
    • You never get a reliable functionality -- everything is stochastic (or hidden components)
    • Saccade is very reliable but none of the cells is reliable -- reduce to the components
    • How to make models that give you that fundamental infrastructure
    • Connectome idea may be misguided -- there is no standard brain
    • Modularity; cf fMRI studies - by the 6th time task is presented don't see any response
  • Standards
    • SBML, cellML, neuroML, sedML, NSDF (neuroscience data format)
    • Allen Brain has a standard (Neo, NineML), wavesurfer
    • Neurodata without borders; spike sorting software is still needed -- been decades

September 12-13, 2017 Bernstein conference: Workshop on Multiscale modeling and simulation

  • Goettingen Germany; Organizers: Dura-Bernal, Lytton
  • Tuesday, September 12
    • 13:00 - Bill Lytton, SUNY Downstate, USA Opening remarks
    • 13:40 - Jean Pierre Changeux, Pasteur Institute, France Climbing brain levels of organisation from genes to consciousness
    • 14:20 - Volker Steuber, University of Hertfordshire, UK Multi-scale models of synaptic plasticity and information processing in single neurons and networks
    • 15:30 - Robert McDougal, Yale University, USA Multiscale modeling with NEURON Reaction­Diffusion Module (NRxD)
    • 16:10 - Salvador Dura­-Bernal, SUNY Downstate, USA NetPyNE tool and multiscale model of mouse M1 microcircuits
    • 16:50 - Cliff Kerr, University of Sydney, Australia The forest and the trees: how the dynamical environment influences small­-scale network computations
    • 17:30 - General discussion
  • Wednesday, September 13
    • 9:00 - Szabolcs Kali, Hungary Tools and workflows for reproducible, collaborative computational neuroscience: modeling hippocampal neurons and network in the Human Brain Project
    • 9:50 - Marianne Bezaire, BU Modeling conductance-­specific and cell type­-specific contributions to functional activity in hippocampal microcircuits and networks
    • 11:00 - Daniel Durstewitz, ZI Mannheim, Germany Merging computational modeling with statistics: Towards quantitative, highly data-­driven, predictive models of neural systems
    • 11:40 - Kael Dai, Allen Institute for Brain Science Software Development Kit for Multiscale Modeling of Large-Scale Brain Circuits
    • 12:20 - Organizers: Closing remarks on the workshop 

 

------------------------------------------------------------------------------------------- 2015 -----------------------------------------------------------------------------------------------------------------

2015 Meeting Breakout

  • Accomplishments
    • White paper for US BRAIN Initiative 
    • Set of white papers coming out on MSM applications to clinic  (Annals of BME, Tom Yankeelov)
    • Workshop on MSM organized by Bill Lytton at Computational Neuroscience (CNS'15) meeting
    • BRAIN Initiative Session organized by Raj Vadigepalli at American Institute of Chemical Engineers Annual Meeting http://www.aiche.org/conferences/aiche-annual-meeting/2015/events/unders...
  • Possible Meeting and Paper Plans
    • Apply for an SFN Symposium on MSM; NB Cell/Neuron organizes satellite symposium
    • Consider a cosine workshop focused on implications of modeling for behavior -- drug abuse issues and/or schizophrenia
    • Set of white papers coming out on MSM applications to clinic  (Annals of BME, Tom Yankeelov)
    • Statistical and applied maths Institute (NSF MBI) organized by Mark Kramer and others - virtual working group how statistics and mathematics can be applied to multiscale Neuroscience data
    • Expand Current BRAIN white paper - use as starting point to expand and deepen; populate with examples, papers, ways of attacking
  • Challenges
    • Stochastic modeling and non-stationarity (hypothesis: get one shot at the data; most neurons not related to stimulus investigated)
    • Social challenge - leadership of the field focused largely on the network with little focus on biological details down to cellular or molecular scale; would like to refocus on biological issues instead of current simplifying paradigms; reconceptualize/redefine what we do to fit 
  • Need to define what we are, what makes us different; what do we offer that defines what this group is?
    • Compared to traditional neuroscience: we should provide solutions for a category of problems in Neuroscience (multiscale)
    • Compared to rest of MSM we have to deal with information representations, cognitive and memory processes, behavior (cf control theory, information theory)
    • Need tools to share multiscale knowledge with different communities/audiences (eg. psychologists) 
    • Rather than tools, we can provide specific questions and then have tools for each question (matlab package, math eqns,..)
    • Define language, principles, methodology, approximations, empirical rules - develop standardized methods for each problem
    • Ebola example integrates data and model: cyber-infrastructure that is queryable - produces feasible answer
    • Gigantic models (cf HBP in EU) vs specific model forms focused on specific questions -- middleware to support this
    • Importance of archiving data that could be be accessed in the context of genomes -- cf proteome, genome data related to neural dynamics or to behavior
    • Linking modelers and experimentalists - how to explain what we do?; we claim we can build bridges between molecular, cellular, network -- but need clear examples of how this has been done; eg. explain behavior at different scales/levels
    • Include tools for HPC multiscale simulations (similar to NSG portal)
    • MSM is about making non-trivial prediction in a different area of investigation
  • How to get people to collaborate from different fields?
    • Models/data that can make predictions for different level (eg. biology to psychology)
    • Explain same question at different levels; hypothesis sharing, scientific affordances, can lead to collaborations 
    • Can help decide what questions to work on
    • Difficult to get working group to work same problem (eg. on addiction) with bottom up participation and no funding
    • Centralization vs distributed/independent research (eg. Human Brain Project, NEURON)
  • 2016 Plans
    • Share computer models of primary motor cortex (M1) neurons (pyramidal, interneuron) at varying levels of complexity (point-neuron, multicompartmental with full dendritic geometry) on ModelDB, and the open-source brain (OSB) websites.
    • Share hybrid network models of M1 microcircuit on ModelDB and OSB. These hybrid models will consist of point-neurons interconnected with detailed multicompartmental models.
    • Share custom Python/NEURON scripts for fitting single neuron models on ModelDB and OSB. Scripts will use genetic algorithms and the PRAXIS algorithm, and will include multiple custom-designed fitness functions and cell models, along with somatic whole-cell recorded data from M1.
    • Share microglial cytokine regulatory network model (Vadigepalli).
  • 2015 Accomplishments
    • Shared primary motor cortex (M1) microcircuit data (Top-down laminar organization of the excitatory network in motor cortex, Weiler et al, Nature Neurosci. 2008) on the new NeuroscidataDB Senselab database, that was designed in collaboration between experimentalists and modelers (https://senselab.med.yale.edu/_siteNET/eavData.aspx?db=18&cl=154&o=147217). The model was also previously made available here: https://senselab.med.yale.edu/ModelDB/ShowModel.cshtml?model=114655 .
    • Devised new formats for multiscale model specifications that range from subcellular synaptic to cellular to network levels. This new format was designed for later incorporation into the NeuroML standard together with our UCL collaborators (Padraig Gleeson).
    • Translation of the Weiler 2008 dataset into the OSB format, and uploaded to the OSB site (URL: http://www.opensourcebrain.org/projects/weileretal08-laminarcortex)
    • Translation of the Izhikevich point-neuron model (of cortical neurons) to the OSB format and shared on the OSB website (URL: http://www.opensourcebrain.org/projects/izhikevichmodel).
    • Sharing of a model that integrates Angiotensin II signaling and electrophysiology in brainstem neurons (Makadia et al., Biophys J 2015 http://dx.doi.org/10.1016/j.bpj.2014.11.1851). Shared on Senselab ModelDB. URL: http://senselab.med.yale.edu/modelDB/ShowModel.cshtml?model=156830
    • Organized (Bill Lytton, Wim van Drongelen) workshop on multiscale modeling (Beyond the canon: temporal and spatial multiscale organization in cortex) at the annual organization for computational neurosciences meeting (7/23/15; Prague, CZ).
    • Multiscale Computational Modeling for the US BRAIN initiative White Paper: computationalmodelingforusbraininitiative_2.pdf
      • How will we understand the brain?  To start, we must observe the brain's dynamic activity, which consists of rich patterns propagating across the brain’s spatial and temporal scales, within the context of the brain's complex anatomy.  A fundamental component of the BRAIN Initiative is the development of new technologies. Here we present suggestions for new technologies in simulation and mathematical modeling – spanning spatial scales from molecules to large neuronal populations – leveraging the strengths of the Multiscale Modeling (MSM) community.

Webinar: Microconnectomics of primary motor cortex: a multiscale computer model

  • Webinar Date: Monday  Mar 2, 2015 15:00-16:00 
  • Presenters: 
    • William W. Lytton MD SUNY Downstate
    • Gordon MG Shepherd MD PhD Northwestern University
  • The dual-output hypothesis, based on analysis of wiring patterns in M1, describes neocortex as organized around Layer-5 corticostriatal pyramidal cells (STRs) which project to other cortical areas (as well as to striatum) and Layer-5  corticospinal pyramidal cells (SPIs), which project out of cerebrum to brainstem and spinal cord.  We propose the dual-output hypothesis as a replacement for the old canonical-circuit model of Douglas and Martin.  The canonical-circuit was a major contribution in 1989, and remains today a touchstone for thinking about neocortex.  Although basic concepts from that model are valid, this model is insufficient for multiscale modeling since it implicitly uses point neurons and thereby neglects the key multiscale feature of cortex -- the large L5 pyramidal cells that span circuit layers at a higher scale.

 

​----------------------------------------------------------------------------------------- 2014 ------------------------------------------------------------------------------------------------------------------------

2014 Meeting

Organized BRAIN Theme Discussion of modeling/simulation opportunities associated with the Presidential BRAIN (Brain Research through Advancing Innovative Neurotechnologies) initiative

Discussion of plans and activities in 2014

  • WG re-organization, lead rotation
  • Integration with the BRAIN Initiative
  • Several IMAG/MSM webinars on multi-scale modeling in neuroscience
  • Workshop: Multi-Scale Modeling in Computational Neuroscience at CNS*2014, July 13-18, Quebec, Canada
  • Funding issues

 

​-------------------------------------------------------------------------------------------- 2013 -------------------------------------------------------------------------------------------------------------------

2013 IMAG/MSM Meeting: The BRAIN Initiative and its links to MSM 

  • October 2, 2013. 
  • Keynote by Terry Sejnowski, Advisory Board to the NIH Director 
  • Organizers: Bill Lytton, Raj Vadigepalli

IMAG/MSM Webinar: Multi-scale seizure dynamics 

  • December, 2013
  • Presenter: Mark Kramer

Thursday, December 5, 2013: Multi-scale seizure dynamics

  • Presenter Mark Kramer
  • Abstract: Epilepsy - the condition of recurrent, unprovoked seizures - is a common brain disease, affecting 1% of the world’s population. Seizures are typically identified as abnormal patterns in brain voltage activity. Many open questions surround epilepsy and seizures, and identifying the associated answers promises new insights for treatment and prevention. In this talk, we will consider brain voltage activity during seizure as observed at multiple spatial scales. We will show how techniques from mathematics and statistics can be used to characterize these data, identify common features, and connect observed brain activity to mechanisms. We will first examine how brain electrical activity couples and decouples during the the course of a seizure. We will then focus on a specific, open question in epileptology: why do seizures spontaneously terminate? Through analysis of human brain electrical activity at various spatial scales, we will propose that seizures self-terminate via a common dynamical mechanisms: a discontinuous critical transition or bifurcation. In contrast, prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. To support these results, we will also consider a computational model to demonstrate that alternative stable attractors, representing the seizure and post-seizure states, emulate the observed brain dynamics. These results suggest that self-terminating seizures end through a common dynamical mechanism. This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature.

Tuesday April 30, 2013: MSM Webinar of Computational Neuroscience WG: Multiscale Modeling of Neural Control of Breathing

  • Presenter: Dr. Yaroslav Molkov, Math Dept., Indiana and Purdue Universities
  • Abstract: Neural circuits involved in generation of the respiratory rhythm and control of breathing is one of the most studied systems in the mammalian brain. Yet the more experimental data become available the more heated become the debates concerning the neural mechanisms involved. The main reason of the controversy is that particular oscillatory regimes observed result from interactions of mechanisms and processes operating on significantly different temporal and spatial scales. In this talk, I will address a number of experimental observations leading to seemingly contradicting hypotheses about mechanisms of respiratory rhythm generation, and analyze them from the single theoretical perspective which includes a spectrum of time and spatial scales from the sub-cellular and cellular levels (voltage-dependent ionic channels, ionic concentrations, pumps, etc.) to the network and system levels of operation. I will demonstrate the conditions in which interventions on smaller scales may or may not lead to significant perturbations on the higher hierarchical level and/or on longer time scales.

 

​--------------------------------------------------------------------------------------------------------------- 2012 -------------------------------------------------------------------------------------------------------

Workshop: Multi-scale Modeling in Computational Neuroscience

  • April 30 - May 5, 2012 
  • University of Lübeck, Germany 
  • Organizer: James M. Bower

Workshop: Multi-Scale Modeling in Computational Neuroscience II: Challenges and Opportunities 

  • July 25, 2012
  • At CNS 2012, Atlanta/Decatur
  • Organizers: James M. Bower and Ilya A. Rybak

IMAG/MSM Webinar: Modeling Neurons as Model Building Devices for Systems Medicine 

  • October 10, 2012
  • Presenter: James S. Schwaber

IMAG/MSM Webinar: Multiscale Modeling of Neural Control of Breathing 

  • April 30, 2012
  • Presenter: Yaroslav I. Molkov

Tuesday, October 22; Meeting of Computational Neuroscience WG during 2012 MSM Consortium Meeting

  • Participants
    • Ilya A. Rybak (Drexel Univ., lead)
    • Carl Berdahl (American Airlines)
    • Thomas Dick (CWRU)
    • Mounya Elhilali (Johns Hopkins Univ.)
    • William W. Lytton (SUNY, Downstate)
    • Grace C. Y. Peng (NIBIB/NIH)
    • James S. Schwaber and Rajanikanth Vadigepalli (Thomas Jefferson Univ.)
    • Susan Volman (NIDA/NIH)
  • Discussion topics
    • Perspectives in multiscale modeling in neuroscience (Rybak, Dick, Elhilali, Litton, Schwaber, Vadigepalli, Volman). Suggested important directions to focus in the future: (1) Modeling of systems biology with computational neuroscience (Schwaber, Vadigepalli) (2) Neural code involving cell selection not population firing rate (Litton) (3) Neuron-glia interactions (Dick)
    • MSM funding for neuroscience (Peng, Volman). We hope that NINDS and NIMH will return to participation in the MSM Consortium. Otherwise the potential future support of neuroscience-related proposals in the framework of MSM Program would be problematic.
    • WG reorganization. We decided to have in this WG two additional leads in the group: Carl Berdahl (American Airlines) and Rajanikanth Vadigepalli (Thomas Jefferson Univ.).

Wednesday October 10, 2012 - Modeling neurons as model building devices for systems medicine

  • Presenter: Jim Schwaber
  • Abstract: What is the function of the extensive variability observed in individual members of a homogenous cell phenotype? This question is particularly relevant to the highly differentiated organization of the brain. High throughput gene expression data from several hundred single neurons from a brainstem homeostatic regulatory nucleus were collected and analyzed in terms of synaptic input type. The results, defined by inputs, showed that the variability in the data contains a surprising structure as a continuum of neuronal gene expression sub-phenotypes. This structured variability is manifest as a gradient of co-regulated gene expression modules at baseline and following hypertensive challenge. This observation indicates that analog tuning of underlying regulatory networks by inputs could shape a state-dependent response of autonomic control networks to physiological challenges. These principles of input-structured phenotype may extend to other neuronal systems where inconsistent, variable responses are common, and where the role of large populations of neurons is uncertain. Analyses of this type could also be extended outside the brain to other environments where cells clearly vary and receive different inputs. Finally, reduction of variability of the transcriptional identity and response of these cells may make identification of specific gene network topologies possible. This may illuminate a molecular physiology interacting with the biophysics, synaptic organization, and connectivity of many different kinds of neurons.

 Workshop: Multi-scale Modeling in Computational Neuroscience

  • April 30 - May 5, 2012
  • University of Lübeck, Lübeck, Germany
  • Organized by James M. Bower, University of Texas Health Science Center, San Antonio, TX.
  • Through simulation projects, participants will have the opportunity to create realistic neural models from sub-cellular to network levels. This will provide an excellent opportunity for those with previous experience in neural simulation to learn new techniques and strategies for multi-scale modeling. Although participants can use the simulator of their choosing, this workshop will also introduce GENESIS 3 (G-3), a modular reimplementation of the GENESIS neural simulator that has capabilities uniquely suited for multi-scale modeling.
  • The international faculty includes:
  • Dr. James M. Bower (University of Texas System) who has been involved in the development of software tools for multi-scale modeling for 30 years.
  • Dr. David Beeman (University of Colorado) who has supported multi-scale modeling both as an instructor in numerous international courses in computational biology as well as in his role as director of the GENESIS users group.
  • Dr. Avrama Blackwell (George Mason University) who’s modeling and experimental expertise involves the investigation of molecular synaptic mechanisms.
  • Dr. Hugo Cornelis (Lead GENESIS developer) with expertise both in the design and construction of multi-scale simulation systems as well as modeling at single cell and network levels.
  • Dr. Volker Steuber (University of Hertfordshire) with expertise in biochemical, single cell, network and systems level modeling and analysis.
  • Mr. Armando Rodriguez (University of Texas San Antonio) an expert in interface design and interoperability in simulations systems.
  • Application deadline is April 10.
  • Applications and inquiries should be sent to: gen3@gradschool.uni-luebeck.de

Workshop: Multi-Scale Modeling in Computational Neuroscience II: Challenges and Opportunities”

  • July 25, 2012
  • Computational Neuroscience Conference (CNS 2012) in Atlanta/Decatur Organizers: 
    • James M. Bower, University of Texas Health Science Center, San Antonio, TX (bower@uthscsa.edu)
    • Ilya A. Rybak, Drexel University College of Medicine, Philadelphia, PA (rybak@drexel.edu).
  • http://www.cnsorg.org/assets/CNS_Meetings/CNS2012/Workshops2012/bower_workshop_at_cns2012-final.pdf
  • Following last year’s highly successful CNS 2011 workshop, we will once again consider and discuss challenges and issues in multi-scale modeling as they apply to understanding nervous systems. The workshop is being organized by the co-chairs of the Computational Neuroscience Working Group of IMAG, a multi-federal agency consortium based at the National Institutes of Health, tasked with exploring and developing multi-scale modeling in biology. including the U.S. National Institutes of Health, the U.S. National Science Foundation. (http://www.imagwiki.nibib.nih.gov/). The results of this discussion will be added to the IMAG wiki and will be presented to the Multi-scale Modeling Consortium at NIH. This workshop therefore represents an opportunity for the CNS community to influence the direction of future funding formodeling in general and multi-scale modeling efforts in particular.

Workshop: Multi-Scale Modeling in the Nervous System

  • August 28th, 2012
  • 34th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2012) (www.embc2012.embs.org) held at the Bayfront Hilton Hotel, San Diego
  • Organized and chaired by Vasilis Z. Marmarelis Professor of Biomedical & Electrical Engineering, University of Southern California (USC).
  • This Workshop brought together experts on the subject of “Multi-Scale Modeling in the Nervous System”, which is attracting increasing attention worldwide because of its fundamental importance in understanding the hierarchical functional organization of the nervous system. The Workshop speakers presented their summary thoughts and recent work that pertain to the fundamental issues of multi-scale modeling of the nervous system (neuronal interconnectivity, emerging properties of neuronal ensembles etc.).
  • The list of speakers (in alphabetical order):
    • Theodore Berger (USC) 
    • Kwabena Boahen (Stanford University) 
    • Sam Deadwyler (Wake-Forest University) 
    • Mounya Elhilali (Johns Hopkins University) 
    • Jack Gallant (UC, Berkeley) 
    • Bill Lytton (SUNY Downstate) 
    • Vasilis Marmarelis (USC) 
    • Mayank Mehta (UCLA) 
    • Terry Sanger (USC) 
    • Christoph Schreiner & Craig Atencio (UCSF) 
    • James Schwaber (Jefferson Univ.) 
    • Terry Sejnowski (Salk Institute)
  • Current State of the Art:NineML - A new simulation tool for multiscale modeling in neuroscience

 

------------------------------------------------------------------------------------------------ 2011 ------------------------------------------------------------------------------------------------------------------------

Workshop

 

------------------------------------------------------------------------------------------- 2010 -------------------------------------------------------------------------------------------------------------------------

Three multiscale projects in the field of neuroscience were awarded in 2010:

1. PD/PI – Terence D. Sanger, Ph.D., University of Southern California

  • R01 NS069214 (02/01/2010-12/31/2013)
  • High-speed simulation of developmental motor disorders
  • Abstract: When the brain is injured during development, there is an effect not only on immediate brain function but also on the future ability to learn and acquire skills. We propose to create and simulate multi-scale computational models of the effect of early structural injury on future motor function of the cortex and spinal cord. We will use programmable chips (FPGA's) and the new mathematical theory of "Likelihood Calculus" to build simulations of 300,000 neurons that run 500 times faster than real-time. The model will be fitted to electromyographic and kinematic data from children at two visits spaced one year apart, and predictions will be tested by comparison to a third visit one year later. High speed simulation of the effect of early injury has the potential to revolutionize the treatment of developmental neurological deficits because it can, in one week, simulate 10 years of future change. In doing so, it allows prediction of disease progression, prediction of the future effects of treatments, and detailed understanding of the interaction between brain injury and resulting disorders of movement, perception, and behavior. Because of these predictions, we can intervene much earlier with treatments customized to each patient's disease profile. With early intervention, it may be possible to attenuate or block the natural progression of their disease. With over 750,000 US children and adults affected by developmental brain disorders, early acquired brain injury, or childhood progressive brain disease, the applicability and potential impact of an early intervention and disease prediction technique are significant.

2. PD/PI – Mounya Elhilali, Ph.D., Johns Hopkins University

  • R01 AG036424 (06/01/2010-05/31/2015)
  • Overcoming the Cocktail Party problem: A multi-scale perspective on the neurobio
  • Abstract: Despite the enormous advances in computing technology over the last decades, there are stills many tasks that are easy for a child, yet difficult for advanced computer systems. A particular challenge to most existing systems is dealing with complex acoustic environments, background noises and competing talkers: A challenge often experienced in cocktail parties (Cherry, 1953) and formally referred to as auditory scene analysis (Bregman, 1990). Progress in this field has tremendous implications and long- term benefits covering the medical, industrial, military and robotics domains; as well as improving communication aids (hearing aids, cochlear implants, speech-based human-computer interfaces) for the sensory-impaired and aging brains. Despite its importance for both engineering and perceptual sciences, the study of the neural underpinnings of auditory scene analysis remains in its infancy. This field is particularly challenged by the lack of integrative theories which incorporate our knowledge of the perceptual bases of scene analysis with the neural mechanisms along various stages of the auditory pathway. Because of the nature of the problem, the neural circuitry at play is intricate and multi-scale by design. The objective of the proposed research is to provide a systems view to modeling scene analysis which integrates mechanisms at the single neuron level, population level and across area interactions. The intellectual merit of the proposed theory is to elucidate the specific mechanisms and computational rules at play; facilitate its integration in engineering systems and enable generating novel testable predictions. The proposal investigates the key hypothesis that attention to a feature of a complex sound instantiates all elements that are coherent with this feature, thus binding them together as one perceptual "object" or stream. This "binding hypothesis" requires three scales of analyses: a micro-level mapping of complex sounds into a multidimensional cortical feature representation; a meso-level coherence analysis correlating activity in populations of cortical neurons; and macro-level feedback processes of attention and expectations that mediate auditory object formation. We shall formulate this hypothesis within a multi-scale computational framework that provides a unified theory for the neural underpinnings of auditory scene analysis. The three core research aims of this project explore all facets of this model employing computational and physiological approaches: Aim I. A multi-scale coherence model: The main goal is to formulate the "binding hypothesis" as a unified biologically plausible theory of auditory streaming, integrating multi-scale sensory with cognitive cortical mechanisms. This computational effort will incorporate findings from experiments in Aims II and III, generate testable predictions, as well as provide effective algorithmic implementations to tackle the "cocktail party problem" in biomedical applications; Aim II. Physiological investigations of the multi-scale coherence theory: Our aim is to use an animal model to record single-unit (micro-level, meso-level) and across area (macro-level) physiological activity in both primary auditory and prefrontal cortex, while presenting sufficiently complex acoustic environments so as to test and refine the computational model; Aim III. Refinement of the coherence theory with physiological and perceptual testing in humans: The objective is to directly test predictions from the model in human subjects, using magnetoencephalography (MEG) and psychoacoustic experiments. We shall particularly focus on the role of cortical mechanisms in scene analysis in normal and aging brains. The proposed research draws upon the expertise of a cross-disciplinary team integrating neurobiology and engineering. It is unique in that it is the first effort to postulate a role for coherence in the scene analysis problem, and to investigate the "binding hypothesis" integrating cortical and attention mechanisms in auditory streaming experiments. In addition, by testing the theory directly on human subjects and comparing normal and aging brains (known to face perceptual difficulties in cocktail party settings), we hope to better understand the neural underpinnings of scene analysis under their normal and malfunctioning states, hence enhancing the translational potential of the model. The broader impact of this effort is to provide versatile and tractable models of auditory stream segregation, significantly facilitating the integration of such capabilities in engineering systems.

3. PD/PI – Ilya A. Rybak, Drexel University

  • R01NS069220 (09/01/2010- 08/31/2015)
  • Multiscale model of neural control of breathing
  • Abstract: Respiration in mammals is a primal homeostatic process, regulating levels of oxygen (O2) and carbon dioxide (CO2) in blood and tissues and is crucial for life. Rhythmic respiratory movements must occur continuously throughout life and originate from neural activity generated by specially organized circuits in the brain stem constituting the respiratory central pattern generator (CPG). The respiratory CPG generates rhythmic patterns of motor activity that produce coordinated movements of the respiratory pump (diaphragm, thorax, and abdomen), controlling lung inflation and deflation, and upper airway muscles, controlling airflow. These coordinated rhythmic movements drive exchange and transport of O2 and CO2 that maintain physiological homeostasis of the brain and body. Uncovering complex multilevel and multiscale mechanisms operating in the respiratory system, leading to mechanistic understanding of breathing, including breathing in different disease states requires a Physiome-type approach that relies on the development and explicit implementation of multiscale computational models of particular organs and physiological functions. The specific aims of this multi-institutional project are: (1) develop a Physiome-type, predictive, multiscale computational model of neural control of breathing that links multiple physiological mechanisms and processes involved in the vital function of breathing but operating at different scales of functional and structural organization, (2) validate this model in a series of complementary experimental investigations and (3) use the model as a computational framework for formulating predictions about possible sources and mechanisms of respiratory pattern alteration associated with heart failure. The project brings together a multidisciplinary team of scientists with long standing collaboration and complementary expertise in respiration physiology, neuroscience and translational medical studies (Thomas E. Dick, Case Western Reserve University; Julian F.R. Paton, University of Bristol, UK; Robert F. Rogers, Drexel University; Jeffrey C. Smith, NINDS, NIH, intramural), mathematics, system analysis and bioengineering (Alona Ben-Tal, Massey University, NZ), and computational neuroscience and neural control (Ilya A. Rybak, Drexel University). The end result of our proposed cross-disciplinary modeling and experimental studies will be the development and implementation of a new, fully operational, multiscale model of the integrated neurophysiological control system for breathing based on the current state of physiological knowledge.