Computational neuroscience articles within Nature Methods

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  • News & Views |

    A new article by Pandarinath et al. describes an artificial neural network model that captures some key aspects of the activity of populations of neurons in the primary motor cortex.

    • Aaron P. Batista
    •  & James J. DiCarlo

  • Article |

    LFADS, a deep learning method for analyzing neural population activity, can extract neural dynamics from single-trial recordings, stitch separate datasets into a single model, and infer perturbations, for example, from behavioral choices to these dynamics.

    • Chethan Pandarinath
    • , Daniel J. O’Shea
    •  & David Sussillo

  • Correspondence |

    Automated tracing algorithms can extract neuronal morphology from fluorescent or brightfield images. UltraTracer scales up the capability of existing tracing algorithms to handle datasets of ever-increasing size.

    • Hanchuan Peng
    • , Zhi Zhou
    •  & Michael Hawrylycz

  • Article |

    SyConn is a computational framework that infers the synaptic wiring of neurons in volume electron microscopy data sets with machine learning. It has been applied to zebra finch, mouse and zebrafish neuronal tissue samples.

    • Sven Dorkenwald
    • , Philipp J Schubert
    •  & Joergen Kornfeld

  • Commentary |

    In this Commentary, Ascoli et al. discuss recipes for setting up public data sharing initiatives based on their experiences with NeuroMorpho.Org.

    • Giorgio A Ascoli
    • , Patricia Maraver
    •  & Rubén Armañanzas

  • Research Highlights |

    By analogy to protein and DNA similarity searches, NBLAST provides a fast and efficient way of finding morphological similarities between neurons.

    • Nina Vogt

  • Article |

    LiFE is an algorithm that evaluates human connectome models derived from magnetic resonance imaging (MRI) and tractography methods. The algorithm achieves this goal by assessing the contribution of all the fiber tracts in a connectome to predict the measured MRI signal.

    • Franco Pestilli
    • , Jason D Yeatman
    •  & Brian A Wandell

  • News & Views |

    A new distributed computing framework for data analysis enables neuroscientists to meet the computational demands of modern experimental technologies.

    • John P Cunningham

  • Article |

    An open-source library of analytical tools for mapping large-scale patterns of brain activity using cluster computing finds structure in two-photon imaging data from mouse and whole-brain light-sheet functional imaging data from behaving larval zebrafish. Vladimirov et al., also in this issue, describes the light-sheet functional imaging system used here.

    • Jeremy Freeman
    • , Nikita Vladimirov
    •  & Misha B Ahrens

  • Commentary |

    New methods for mapping synaptic connections and recording neural signals generate rich and complex data on the structure and dynamics of brain networks. Making sense of these data will require a concerted effort directed at data analysis and reduction as well as computational modeling.

    • Olaf Sporns

  • Research Highlights |

    Researchers have taken first steps toward functional connectomics. By combining large-scale serial electron microscopy and functional imaging data, the structure of neural networks can be related to their function.

    • Erika Pastrana

  • Research Highlights |

    Using a virtual reality setup and a deep window into the brain, researchers can image the activity of neurons as mice navigate virtual environments.

    • Erika Pastrana

  • This Month |

    Fly brains light the way for neurobehavioral circuits.

    • Monya Baker

  • Research Highlights |

    New software tools help take the pain out of working with huge three-dimensional image datasets and aid in mapping neuronal networks.

    • Daniel Evanko

  • Article |

    Limitations in scanning speed have made it difficult for two-photon imaging to provide accurate temporal information on neuronal signaling. Refinements to random-access scanning using acousto-optic deflectors and an automated algorithm for reconstructing complex spike trains allowed in vivo high-speed optical recording of spiking activity in neuronal populations in the mouse neocortex.

    • Benjamin F Grewe
    • , Dominik Langer
    •  & Fritjof Helmchen

  • Research Highlights |

    The Negatome is a database of non-interacting protein pairs that can be used for training protein-protein interaction prediction algorithms.

    • Allison Doerr

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