WORKSHOP ORGANIZERS
Amit
Majumdar
San Diego Supercomputer Center, University
of California San Diego, La Jolla, CA, USA
Subhashini
Sivagnanam
San Diego Supercomputer Center,
University of California San Diego, La Jolla, CA, USA
Ted
Carnevale
Department of Neuroscience, Yale
University, New Haven, CT, USA
Kenneth Yoshimoto
San Supercomputer Center, University of California San Diego, La Jolla, CA, USA
Abstract
of the workshop:
The Neuroscience Gateway (NSG) is a free and open platform, eliminates administrative and technical barriers and enables neuroscientists to do large scale modeling and data processing using various tools on supercomputers. NSG is also a platform for dissemination of neuroscience software. Presentations and discussions by NSG users and software developers will be showcased at this workshop .
Title of
Talks and Names of Speakers:
08:30 - 08:45 Introduction of the
workshop.
08:45 – 09:15 Introduction to the Neuroscience Gateway enabling large scale simulation, data processing and software dissemination., Subhashini Sivagnanam, San Diego Supercomputer Center, UCSD, La Jolla, CA, USA ; Kenneth Yoshimoto, San Diego Supercomputer Center, UCSD, La Jolla, CA, USA; Ted Carnevale, Department of Neuroscience, Yale University, New Haven, CT, USA; Amit Majumdar, San Diego Supercomputer Center, UCSD, La Jolla, CA, USA.
09:15 – 09:45 Writing massively parallel software with NEURON at the NSG, Charles Cohen, Fidelis Technologies, Delaware, USA
09:45 – 10:15
Investigating cortical oscillations in a multiscale model of the macaque auditory pathway, Erica Griffith, Salvador Durá-Bernal, SUNY Downstate Medical Center,Brooklyn, New York, USA
10:15 – 10:45
Biophysically detailed modeling of motor thalamocortical neurons in normal and dopamine-depleted states,
Francesco Cavarretta,
Emory University, Atlanta, GA, USA,
10:45 – 11:00 BREAK
11:00 – 11:30 NEMAR, the NeuroElectroMagnetic data Archive and tools Resource, Scott Makeig, Arnaud Delorme University of California San Diego, La Jolla, CA, USA
11:30 – 12:00
Human Neocortical Neurosolver: A Software Tool for Cell and Circuit Level Interpretation of MEG/EEG Signals,
Nicholas Tolley, Stephanie Jones, Brown University, Providence, RI
USA
12:00 – 12:30 Q/A
SCHEDULE OF EVENTS
08:30 - 08:45
Introduction of the Workshop
08:45 - 09:15
Introduction to the Neuroscience Gateway
Subhashini Sivagnanam
, Kenneth Yoshimoto, Amit Majumdar
San Diego Supercomputer Center,
University of California San Diego, La Jolla, CA, USA
Ted
Carnevale
Department of Neuroscience, Yale
University, New Haven, CT, USA
We
will provide a brief overview of the Neuroscience Gateway, including all the
tools, software and pipelines that are provided via NSG on supercomputing
resources. We will describe how users are using the NSG, developers
can use the NSG utilizing the cloud-based developer's platform and NSG enables dissemination of neuroscience software.
09:15 - 09:45
Writing massively parallel software with NEURON at the NSG.
Charles Cohen
Fidelis Technologies, Delaware, USA
My current research with NEURON and the NSG involves finding statistically-robust biophysical
parameter sets for detailed single neuron models. To this end, thousands of parallel optimization
trials are required to canvas the solution space in question, explaining the need for a massively
parallel approach. The Neuroscience Gateway (NSG) is indispensable to this process, enabling
easy access to supercomputers preconfigured with parallel implementations of NEURON. I have
found greatest success writing in HOC: little overhead, and virtually no functionality I could not
(eventually) program. In this talk, I will discuss my experience and some strategies for organizing
biophysical parameter sweeps on some neuronal morphology against voltage recordings. Provided
sufficient experimental data, the result is a robust neuron model operating on the lowest-availableerror
biophysical parameter set. This general strategy is captured in open-source software: Salto,
available at https://github.com/cccohen/Salto.
09:45 – 10:15
Investigating cortical oscillations in a multiscale model of the macaque auditory pathway
Erica Griffith, Salvador Durá-Bernal
SUNY Downstate Medical Center,Brooklyn, New York, USA
We developed a biophysically-detailed model of the macaque auditory thalamocortical pathway in order to reproduce and investigate cortical oscillations in primary auditory cortex (A1). This model used the NEURON simulator and the NetPyNE modeling tool to integrate information at the subcellular, cellular, and circuit-level scales. Our A1 cortical column contained over 12k neurons and 30M synapses, with properties such as long-range and local connectivity, neuron electrophysiology, and network geometry all derived from published experimental data. The simulated A1 column was reciprocally connected to auditory thalamic structures in a manner mimicking anatomical connectivity. The auditory thalamic structures included medial geniculate body and thalamic reticular nuclei, complete with core and matrix neurons with layer-specific projection patterns to A1, and thalamic interneurons projecting locally. Simulations, optimization, and analyses were conducted on high-performance computing (HPC) platforms, such as the Google Cloud and CINECA HPCs. The model generated cell type and layer-specific firing rates consistent with overall ranges observed experimentally, and accurately simulated the corresponding local field potentials (LFP), current source density (CSD), and electroencephalogram (EEG) signals. Physiological oscillations emerged spontaneously across frequency bands, without external rhythmic inputs, and were comparable to those recorded in vivo. We used the model to unravel the contributions of distinct cell type and layer-specific neuronal populations to these oscillation events. Overall, this computational model provides a quantitative theoretical framework to integrate and interpret a wide range of experimental data in auditory circuits. It also constitutes a powerful tool to evaluate hypotheses and make predictions about the cellular and network mechanisms underlying common experimental measurements, including LFP, CSD and EEG signals.
10:15 – 10:45
Biophysically detailed modeling of motor thalamocortical neurons in normal and dopamine-depleted states
Francesco Cavarretta
Emory University, Atlanta, GA, USA
Basal ganglia receiving motor thalamus (BGMT) is implicated in multiple motor functions, such as movement preparation and initiation. In particular, thalamocortical cells (TC) are a fundamental component of BGMT: they integrate glutamatergic inputs from motor cortical and motor-related subcortical areas with inhibition from substantia nigra reticulata, and influence motor cortical activity through their feedback projections. Our experiments in vitro showed that dopamine depletion causes important homeostatic alterations in these neurons, enhancing their excitability and the ability in generating rebound bursts. However, how these changes impact the in vivo activity patterns remains unclear, and difficult to study experimentally. We addressed this problem by using biophysically detailed simulations, using the NEURON simulation environment. Using the BluePyOptimizer toolkit, we fitted two populations of BGMT thalamocortical neuron models replicating the different firing properties observed in vitro in normal or dopamine depleted conditions. We then modeled the synaptic inputs conveyed on BGMT TCs, replicating specific synaptic conductances for excitatory and inhibitory inputs, and representing their presynaptic activity by artificial spike trains. The models thus predict the BGMT TC responses during motor tasks in normal and dopamine depleted states.
10:45 - 11:00 BREAK
11:00 – 11:30
NEMAR, the NeuroElectroMagnetic data Archive and tools Resource
Scott Makeig and Arnaud Delorme
University
of California San Diego, La Jolla , CA, USA
NEMAR, the NeuroElectroMagnetic data Archive and tools Resource, is an NIMH BRAIN Initiative funded data, tools, and compute resource for (EEG, MEG, and iEEG) data shared publicly through the (all modalities) OpenNeuro archive of human neuroimaging data. Neuroelectromagnetic (NEM) datasets (EEG, MEG, iEEG) are formatted according to the BIDS standards (bids.neuroimaging.io) and submitted to OpenNeuro through its website (openneuro.org). NEM datasets in OpenNeuro are copied to NEMAR, housed in the San Diego Supercomputer Center (sdsc.edu) that provides cyberinfrastructure resources for storage, high performance computing and administration. NEMAR allows to (i) search through OpenNeuro NEM data using search on dataset metadata - soon including, when available, detailed descriptions of experimental events stored using the Hierarchical Event Descriptor (HED) system (hedtags.org), (ii) optionally view a range of data statistics, measures, and transforms, to aid data selection and (iii) select datasets and data recordings to include in user analysis using scripts on the Neuroscience Gateway.
11:30 - 12:00
Human Neocortical Neurosolver: A Software Tool for Cell and Circuit Level Interpretation of MEG/EEG Signals
Nicholas Tolley, Stephanie Jones
Brown University, Providence, RI, USA
MEG/EEG signals are correlated with nearly all healthy and pathological brain functions. However, it is still extremely difficult to infer the underlying cellular and circuit level origins. This limits the translation of MEG/EEG signals into novel principles of information processing, or into new treatment modalities for pathologies. To address this limitation, we built the Human Neocortical Neurosolver (HNN): an open-source software tool to help researchers and clinicians without formal computational modeling or coding experience interpret the neural origin of their human MEG/EEG data. HNN provides a graphical user interface (GUI) to an anatomically and biophysically detailed model of a neocortical circuit, with layer specific thalamocortical and cortical-cortical drives. Tutorials are provided to teach users how to begin to study the cell and circuit level origin of sensory event related potentials (ERPs) and low frequency rhythms. Once users have an understanding of the basic workflows and tutorials in the HNN GUI, those familiar with Python can work in the HNN-core Pythonic interface. We’ll give a didactic overview of the background and development of HNN and describe current and planned resources to use HNN through the Neuroscience Gateway Portal.
12:00 – 12:30 Q/A