Evidence map›Paper›PMID 35098264›Full record

ArticlePEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online)2020

Simulating Large-scale Models of Brain Neuronal Circuits using Google Cloud Platform.

Subhashini Sivagnanam, Wyatt Gorman, Donald Doherty, Samuel A Neymotin, Stephan Fang, Hermine Hovhannisyan, William W Lytton, Salvador Dura-Bernal

Open access · bronzeAbstract read
In one paragraph

Article in PEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Subhashini SivagnanamState University of New York DMC, Brooklyn NY; San Diego Supercomputer Center / University California San Diego, La Jolla CA.
Wyatt GormanGoogle Corporation, Mountain View CA.
Donald DohertyState University of New York DMC, Brooklyn NY.
Samuel A NeymotinNathan Kline Institute for Psychiatric Research, Orangeburg NY USA.
Stephan FangGoogle Corporation, Mountain View CA.
Hermine HovhannisyanGoogle Corporation, Mountain View CA.
William W LyttonState University of New York DMC, Brooklyn NY; King's County Hospital, Brooklyn NY.
Salvador Dura-BernalState University of New York DMC, Brooklyn NY; Nathan Kline Institute for Psychiatric Research, Orangeburg NY USA.
Google (United States) · USSUNY Downstate Health Sciences University · USUniversity of California, San Diego · US

Funding

Cortical and thalamic mechanisms of selective auditory attentionR01DC012947 · NIDCD · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI NEYMOTIN, SAMUEL A, SCHROEDER, CHARLES E · 2013 to 2022
$5.2M
Microconnectomics of neocortex: a multiscale computer modelU01EB017695 · NIBIB · SUNY DOWNSTATE MEDICAL CENTER · PI LYTTON, WILLIAM W · 2014 to 2017
$2.3M
Dissemination of a tool for data-driven multiscale modeling of brain circuitsU24EB028998 · NIBIB · SUNY DOWNSTATE MEDICAL CENTER · PI DURA-BERNAL, SALVADOR · 2019 to 2023
$1.6M
NIBIB NIH HHS U01 EB017695NIBIB NIH HHS U24 EB028998NIDCD NIH HHS R01 DC012947
6 · The paper itself

Abstract

Biophysically detailed modeling provides an unmatched method to integrate data from many disparate experimental studies, and manipulate and explore with high precision the resultin brain circuit simulation. We developed a detailed model of the brain motor cortex circuits, simulating over 10,000 biophysically detailed neurons and 30 million synaptic connections. Optimization and evaluation of the cortical model parameters and responses was achieved via parameter exploration using grid search parameter sweeps and evolutionary algorithms. This involves running tens of thousands of simulations requiring significant computational resources. This paper describes our experience in setting up and using Google Compute Platform (GCP) with Slurm to run these large-scale simulations. We describe the best practices and solutions to the issues that arose during the process, and present preliminary results from running simulations on GCP.

Indexed as

Applied computing → Life and medical sciencesBrain modelingComputational neuroscienceComputing methodologies → Modeling and simulationGoogle Cloud PlatformLarge-scale simulations

Identifiers

PMID35098264
PMCPMC8796663
OpenAlexW3044773125

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.