The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex

Ramaswamy, Srikanth; Courcol, Jean-Denis; Abdellah, Marwan; Adaszewski, Stanisław; Antille, Nicolas; Arsever, Selim; Atenekeng, Guy; Bilgili, Ahmet; Brukau, Yury; Chalimourda, Athanassia; Chindemi, Giuseppe; Delalondre, Fabien; Dumusc, Raphael; Eilemann, Stefan; Gevaert, Michael; Gleeson, Padraig; Graham, Joe W.; Hernando, Juan; Kanari, Lida; Katkov, Yury Nikolaevich; Keller, Daniel; King, James G.; Ranjan, Rajnish; Reimann, Michael; Rössert, Christian; Shi, Ying; Shillcock, Julian C.; Telefont, Martin; Geit, Werner Van; Díaz, Jafet Villafranca; Walker, Richard; Wang, Yun; Zaninetta, Stefano M.; DeFelipe, Javier; Hill, Sean; Muller, Jeffrey; Segev, Idan; Schürmann, Felix; Müller, Eilif; Markram, Henry

doi:10.3389/fncir.2015.00044

Cited by 151 publications

(196 citation statements)

References 49 publications

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“…Many place code on the research group's website. This strategy has been adopted by both individual researchers and large research groups, such as the Allen Institute's Cell Types Database (celltypes.brain-map.org) and the Human Brain Project's Neocortical Micro-circuit Collaboration Portal (bbp.epfl.ch/nmc-portal/welcome) [125]. However, especially for small groups, lab websites are often only maintained as long as the lead researcher continues to work at the same university [126].…”

Section: Repositories and Standards: Code Data And Modelsmentioning

confidence: 99%

Reproducibility in Computational Neuroscience Models and Simulations

McDougal

Bulanova

Lytton

2016

IEEE Trans. Biomed. Eng.

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Objective Like all scientific research, computational neuroscience research must be reproducible. Big data science, including simulation research, cannot depend exclusively on journal articles as the method to provide the sharing and transparency required for reproducibility. Methods Ensuring model reproducibility requires the use of multiple standard software practices and tools, including version control, strong commenting and documentation, and code modularity. Results Building on these standard practices, model sharing sites and tools have been developed that fit into several categories: 1. standardized neural simulators, 2. shared computational resources, 3. declarative model descriptors, ontologies and standardized annotations; 4. model sharing repositories and sharing standards. Conclusion A number of complementary innovations have been proposed to enhance sharing, transparency and reproducibility. The individual user can be encouraged to make use of version control, commenting, documentation and modularity in development of models. The community can help by requiring model sharing as a condition of publication and funding. Significance Model management will become increasingly important as multiscale models become larger, more detailed and correspondingly more difficult to manage by any single investigator or single laboratory. Additional big data management complexity will come as the models become more useful in interpreting experiments, thus increasing the need to ensure clear alignment between modeling data, both parameters and results, and experiment.

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Section: Repositories and Standards: Code Data And Modelsmentioning

confidence: 99%

Reproducibility in Computational Neuroscience Models and Simulations

McDougal

Bulanova

Lytton

2016

IEEE Trans. Biomed. Eng.

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“…However, we are not aware of any rigorous argument in the present triptych of manuscripts Ramaswamy et al, 2015;Reimann et al, 2015), specifying the relevant level of granularity. For instance, are active dendrites, such as those of the tall, layer 5 pyramidal cells (Hay et al, 2011), essential?…”

Section: Booting Up the Virtual Slicementioning

confidence: 92%

A Biological Imitation Game

Koch

Buice

2015

Cell

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The digital reconstruction of a slice of rat somatosensory cortex from the Blue Brain Project provides the most complete simulation of a piece of excitable brain matter to date. To place these efforts in context and highlight their strengths and limitations, we introduce a Biological Imitation Game, based on Alan Turing's Imitation Game, that operationalizes the difference between real and simulated brains.

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“…One contains 1915 reconstructions of human pyramidal cells from different brain regions, whereas the other has 90 reconstructions of mouse pyramidal cells from the neocortex . A third set of 38 reconstructions of rat pyramidal neurons from the somatosensory cortex was downloaded from a different source . Table contains the count of reconstructions per data set aggregated by the number of basal dendrites.…”

Section: A Real‐world Application In Neuroanatomymentioning

confidence: 99%

“…37 A third set of 38 reconstructions of rat pyramidal neurons from the somatosensory cortex was downloaded from a different source. 38,39 Table IV contains the count of reconstructions per data set aggregated by the number of basal dendrites. We only pick those cases where the number of samples is at least six; otherwise, we are not able to estimate the KL divergence properly as with smaller samples the test set would be too small to provide a reliable KL estimation.…”

Section: Data Extraction and Modelingmentioning

confidence: 99%

Frobenius Norm Regularization for the Multivariate Von Mises Distribution

Rodriguez-Lujan

Larrañaga

Bielza

2016

Int. J. Intell. Syst.

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Penalizing the model complexity is necessary to avoid overfitting when the number of data samples is low with respect to the number of model parameters. In this paper, we introduce a penalization term that places an independent prior distribution for each parameter of the multivariate von Mises distribution. We also propose a circular distance that can be used to estimate the Kullback–Leibler divergence between any two circular distributions as goodness‐of‐fit measure. We compare the resulting regularized von Mises models on synthetic data and real neuroanatomical data to show that the distribution fitted using the penalized estimator generally achieves better results than nonpenalized multivariate von Mises estimator.

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The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex

Cited by 151 publications

References 49 publications

Reproducibility in Computational Neuroscience Models and Simulations

Reproducibility in Computational Neuroscience Models and Simulations

A Biological Imitation Game

Frobenius Norm Regularization for the Multivariate Von Mises Distribution

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