BioModels—15 years of sharing computational models in life science

Nucleic Acids Research, Journal Year: 2019, Volume and Issue: unknown

Published: Nov. 6, 2019

Computational modelling has become increasingly common in life science research. To provide a platform to support universal sharing, easy accessibility and model reproducibility, BioModels (https://www.ebi.ac.uk/biomodels/), repository for mathematical models, was established 2005. The current allows submission of models encoded diverse formats, including SBML, CellML, PharmML, COMBINE archive, MATLAB, Mathematica, R, Python or C++. submitted are curated verify the computational representation biological process reproducibility simulation results reference publication. curation also involves encoding standard formats annotation with controlled vocabularies following MIRIAM (minimal information required biochemical models) guidelines. now accepts large-scale auto-generated models. With gradual growth content over 15 years, currently hosts about 2000 from published literature. 800 world's largest emerged as third most used data resource after PubMed Google Scholar among scientists who use their Thus, benefits modellers by providing access reliable semantically enriched that share, reproduce reuse.

Language: Английский

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NetPyNE, a tool for data-driven multiscale modeling of brain circuits

eLife, Journal Year: 2019, Volume and Issue: 8

Published: April 26, 2019

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic graphical interfaces develop data-driven multiscale network models in NEURON. clearly separates model parameters from implementation code. Users provide specifications a high level via standardized declarative language, for example connectivity rules, create millions cell-to-cell connections. then enables users generate the NEURON network, run efficiently parallelized simulations, optimize explore through automated batch runs, use built-in functions visualization analysis - matrices, voltage traces, spike raster plots, local field potentials, information theoretic measures. also facilitates sharing by exporting importing formats (NeuroML SONATA). is already being used teach computational neuroscience students modelers investigate brain regions phenomena.

Language: Английский

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Systematic generation of biophysically detailed models for diverse cortical neuron types

Nature Communications, Journal Year: 2018, Volume and Issue: 9(1)

Published: Feb. 13, 2018

Abstract The cellular components of mammalian neocortical circuits are diverse, and capturing this diversity in computational models is challenging. Here we report an approach for generating biophysically detailed 170 individual neurons the Allen Cell Types Database to link systematic experimental characterization cell types construction cortical models. We build from 3D morphologies somatic electrophysiological responses measured same cells. Densities active conductances additional parameters optimized with a genetic algorithm match features. evaluate by applying stimuli comparing model data. Applying technique across diverse set adult mouse primary visual cortex, verify that preserve distinctiveness intrinsic properties between subsets cells observed experiments. accessible online alongside Code optimization simulation also openly distributed.

Language: Английский

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Large and fast human pyramidal neurons associate with intelligence

eLife, Journal Year: 2018, Volume and Issue: 7

Published: Dec. 18, 2018

It is generally assumed that human intelligence relies on efficient processing by neurons in our brain. Although grey matter thickness and activity of temporal frontal cortical areas correlate with IQ scores, no direct evidence exists links structural physiological properties to intelligence. Here, we find high scores large associate larger, more complex dendrites pyramidal neurons. We show silico larger dendritic trees enable track synaptic inputs higher precision, due fast action potential kinetics. Indeed, individuals sustain kinetics during repeated firing. These findings provide the first associated neuronal complexity, information transfer from output within

Language: Английский

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Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0

Frontiers in Neuroinformatics, Journal Year: 2018, Volume and Issue: 12

Published: Dec. 18, 2018

Recordings of extracellular electrical, and later also magnetic, brain signals have been the dominant technique for measuring activity decades. The interpretation such is however nontrivial, as measured result from both local distant neuronal activity. In volume-conductor theory potentials can be calculated a distance-weighted sum contributions transmembrane currents neurons. Given same currents, to magnetic field recorded inside outside computed. This allows development computational tools implementing forward models grounded in biophysics underlying electrical measurement modalities. LFPy (LFPy.readthedocs.io) incorporated well-established scheme predicting individual neurons with arbitrary levels biological detail. It relies on NEURON (neuron.yale.edu) compute multicompartment which then used combination an electrostatic model. Its functionality now extended allow modeling networks concurrent calculations current dipole moments. moments are then, suitable head models, non-invasive measures activity, like scalp (electroencephalographic recordings; EEG) fields (magnetoencephalographic MEG). One built-in model four-sphere incorporating different electric conductivities brain, cerebrospinal fluid, skull scalp. We demonstrate new software by constructing network biophysically detailed neuron Neocortical Microcircuit Collaboration (NMC) Portal (bbp.epfl.ch/nmc-portal) corresponding statistics connections synapses, vivo-like (local potentials, LFP; electrocorticographical signals, ECoG) From we estimate EEG MEG using show strong scaling performance numbers message-passing interface (MPI) processes, sizes density connections. open-source equally execution laptops parallel high-performance computing (HPC) facilities publicly available GitHub.com.

Language: Английский

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Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds

eLife, Journal Year: 2017, Volume and Issue: 6

Published: Nov. 22, 2017

Interactions between cervical and lumbar spinal circuits are mediated by long propriospinal neurons (LPNs). Ablation of descending LPNs in mice disturbs left-right coordination at high speeds without affecting fore-hind alternation. We developed a computational model consisting four rhythm generators coupled commissural interneurons (CINs), providing interactions, LPNs, mediating homolateral diagonal interactions. The proposed CIN LPN connections contribute to speed-dependent gait transition from walk, trot, then gallop bound; the ensure alternation all gaits. reproduces expression intact genetically transformed disruption hindlimb following ablation LPNs. Inputs CINs can affect interlimb change independent speed. suggest that these represent main targets for supraspinal sensory afferent signals adjusting gait.

Language: Английский

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Neural Basis for Looming Size and Velocity Encoding in the Drosophila Giant Fiber Escape Pathway

Current Biology, Journal Year: 2019, Volume and Issue: 29(6), P. 1073 - 1081.e4

Published: Feb. 28, 2019

Identified neuron classes in vertebrate cortical [1Hubel D.H. Wiesel T.N. Receptive fields, binocular interaction and functional architecture the cat's visual cortex.J. Physiol. 1962; 160: 106-154Crossref PubMed Scopus (8580) Google Scholar, 2Hubel fields of monkey striate 1968; 195: 215-243Crossref (4405) 3Maunsell J.H.R. Newsome W.T. Visual processing extrastriate cortex.Annu. Rev. Neurosci. 1987; 10: 363-401Crossref (793) 4Zhao X. Liu M. Cang J. cortex modulates magnitude but not selectivity looming-evoked responses superior colliculus awake mice.Neuron. 2014; 84: 202-213Abstract Full Text PDF (119) Scholar] subcortical [5Shang C. Z. Chen Shi Y. Wang Q. S. Li D. Cao P. A parvalbumin-positive excitatory pathway to trigger fear mice.Science. 2015; 348: 1472-1477Crossref (172) 6Sun H. Frost B.J. Computation different optical variables looming objects pigeon nucleus rotundus neurons.Nat. 1998; 1: 296-303Crossref (175) 7Dunn T.W. Gebhardt Naumann E.A. Riegler Ahrens M.B. Engert F. Del Bene Neural circuits underlying visually evoked escapes larval zebrafish.Neuron. 2016; 89: 613-628Abstract (174) 8Liu Y.J. B. Neuronal cat.Brain Behav. Evol. 2011; 77: 193-205Crossref (55) areas invertebrate peripheral [9Hatsopoulos N. Gabbiani Laurent G. Elementary computation object approach by a wide-field neuron.Science. 1995; 270: 1000-1003Crossref (212) 10de Vries S.E.J. Clandinin T.R. Loom-sensitive neurons link action Drosophila system.Curr. Biol. 2012; 22: 353-362Abstract (100) 11Oliva Tomsic system motion-sensitive crab Neohelice.J. Neurophysiol. 112: 1477-1490Crossref (34) central [12O'Carroll Feature-detecting dragonflies.Nature. 1993; 362: 541-543Crossref (150) 13von Reyn C.R. Breads Peek M.Y. Zheng G.Z. Williamson W.R. Yee A.L. Leonardo A. Card G.M. spike-timing mechanism for selection.Nat. 17: 962-970Crossref (143) 14Seelig J.D. Jayaraman V. Feature detection orientation tuning complex.Nature. 2013; 503: 262-266Crossref (186) brain neuropils encode specific features panorama. How downstream integrate these control vital behaviors, like escape, is unclear [15Ziemba C.M. Freeman Representing "stuff" cortex.Proc. Natl. Acad. Sci. USA. 942-943Crossref (5) Scholar]. In Drosophila, timing single spike giant fiber (GF) descending [16Levine Tracey Structure function motorneuron melanogaster.J. Comp. 1973; 87: 213-235Crossref (49) 17Tanouye M.A. Wyman R.J. Motor outputs nerve Drosophila.J. 1980; 44: 405-421Crossref (216) 18Bacon J.P. Strausfeld N.J. The dipteran "giant fibre" pathway: signals.J. Neuroethol. Sens. 1986; 158: 529-548Crossref (83) determines whether fly uses short or long takeoff when escaping predator [13von We previously proposed that GF results from summation two whose highly conserved across animals [19von Nern Wu Namiki integration drives probabilistic behavior escape response.Neuron. 2017; 94: 1190-1204.e6Abstract (63) Scholar]: an object's subtended angular size its velocity 20Peek Comparative approaches escape.Curr. Opin. Neurobiol. 41: 167-173Crossref (37) 21Laurent Collision-avoidance: nature's many solutions.Nat. 261-263Crossref (22) attributed encoding input lobula columnar type 4 (LC4) projection neurons, size-encoding source remained unknown. Here, we show plate/lobula columnar, 2 (LPLC2) anatomically specialized detect [22Klapoetke N.C. Rogers E.M. Rubin Reiser Ultra-selective radial motion opponency.Nature. 551: 237-241Crossref (70) provide entire component. find LPLC2 be necessary GF-mediated LC4 synapse directly onto via reconstruction electron microscopy (EM) volume [23Zheng Lauritzen J.S. Perlman E. Robinson C.G. Nichols Milkie Torrens O. Price Fisher C.B. Sharifi et al.A complete adult melanogaster.Cell. 2018; 174: 730-743.e22Abstract (359) silencing eliminates component response patch-clamp recordings, leaving only model summing linear (provided LC4) Gaussian LPLC2) replicates dynamics predicts peak time. thus present identified circuit which information feature-detecting combined common post-synaptic target determine behavioral output.

Language: Английский

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Visualization of currents in neural models with similar behavior and different conductance densities

eLife, Journal Year: 2019, Volume and Issue: 8

Published: Jan. 31, 2019

Conductance-based models of neural activity produce large amounts data that can be hard to visualize and interpret. We introduce visualization methods display the dynamics ionic currents models’ response perturbations. To currents’ dynamics, we compute percent contribution each current them over time using stacked-area plots. The waveform membrane potential change as are perturbed. represent these changes a range perturbation control parameter, distributions waveforms. illustrate procedures in six examples bursting model neurons with similar but differ much threefold their conductance densities. These provide heuristic insight into why individual or networks behavior respond widely differently

Language: Английский

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Paranoia as a deficit in non-social belief updating

eLife, Journal Year: 2020, Volume and Issue: 9

Published: May 26, 2020

Paranoia is the belief that harm intended by others. It may arise from selective pressures to infer and avoid social threats, particularly in ambiguous or changing circumstances. We propose uncertainty be sufficient elicit learning differences paranoid individuals, without threat. used reversal behavior computational modeling estimate updating across individuals with mental illness, online participants, rats chronically exposed methamphetamine, an elicitor of paranoia humans. associated a stronger prior on volatility, accompanied elevated sensitivity perceived changes task environment. Methamphetamine exposure recapitulates this impaired uncertainty-driven rigid anticipation volatile Our work provides evidence fundamental, domain-general individuals. This paradigm enables further assessment interplay between belief-updating species.

Language: Английский

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Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

Journal of Translational Medicine, Journal Year: 2020, Volume and Issue: 18(1)

Published: Sept. 29, 2020

Abstract The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand predict the trajectory pathophysiology, disease genesis, spread in support clinical policy decisions. In such cases, inappropriate or ill-placed trust model outcomes may result negative outcomes, hence illustrate need formalize execution communication practices. Although verification validation been generally accepted significant components model’s credibility, they cannot be assumed equate holistic credible practice, which includes activities that can impact comprehension in-depth examination inherent development reuse models. For past several years, Committee on Credible Practice Modeling Simulation Healthcare, an interdisciplinary group seeded from U.S. interagency initiative, has worked codify best Here, we provide Ten Rules for practice healthcare developed comparative analysis by Committee’s multidisciplinary membership, followed large stakeholder community survey. These rules establish unified conceptual framework design, implementation, evaluation, dissemination usage across life-cycle. While biomedical science care domains somewhat different requirements expectations our study converged would useful broad swath types. brief, are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform standards. some these common sense guidelines, found many often missed misconstrued, even seasoned practitioners. Computational models already widely used basic generate new knowledge. As penetrate policy, contributing personalized precision medicine, safety will require established guidelines healthcare.

Language: Английский

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