Computational neuroscience articles from across Nature Portfolio

Computational neuroscience is the field of study in which mathematical tools and theories are used to investigate brain function. It can also incorporate diverse approaches from electrical engineering, computer science and physics in order to understand how the nervous system processes information.

Latest Research and Reviews

News and Comment

  • News & Views |

    Using long-term brain recordings in patients with chronic pain, we identified objective biomarkers of real-world subjective pain intensity over many months. Spontaneous chronic pain states were predicted most reliably by sustained changes in the activity of the orbitofrontal cortex, whereas acute pain was most associated with signals from the anterior cingulate cortex.

    Nature Neuroscience 26, 928-929
  • News & Views |

    In this issue, Shinn et al. demonstrate a close relationship between complex brain network topology and lower-level statistical properties of neuroimaging data. They also highlight the potential of these statistical measures, which capture similarity in space and time, to provide imaging-based markers of aging and pharmacological states.

    • Shiyu Wang
    •  & Catie Chang
    Nature Neuroscience 26, 732-734
  • News & Views |

    This work involved the design of a multi-view manifold learning algorithm that capitalizes on various types of structure in high-dimensional time-series data to model dynamic signals in low dimensions. The resulting embeddings of human functional brain imaging data unveil trajectories through brain states that predict cognitive processing during diverse experimental tasks.