PlumX Metrics
Embed PlumX Metrics

Data-driven models in human neuroscience and neuroengineering

Current Opinion in Neurobiology, ISSN: 0959-4388, Vol: 58, Page: 21-29
2019
  • 22
    Citations
  • 0
    Usage
  • 153
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    22
    • Citation Indexes
      22
  • Captures
    153
  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • News
        1

Most Recent News

Are we witnessing the dawn of post-theory science?

Does the advent of machine learning mean the classic methodology of hypothesise, predict and test has had its day? Isaac Newton apocryphally discovered his second law – the one about gravity – after an apple fell on his head. Much experimentation and data analysis later, he realised there was a fundamental relationship between force, mass and acceleration. He formulated a theory to describe that r

Review Description

Discoveries in modern human neuroscience are increasingly driven by quantitative understanding of complex data. Data-intensive approaches to modeling have promise to dramatically advance our understanding of the brain and critically enable neuroengineering capabilities. In this review, we provide an accessible primer to modern modeling approaches and highlight recent data-driven discoveries in the domains of neuroimaging, single-neuron and neuronal population responses, and device neuroengineering. Further, we suggest that meaningful progress requires the community to tackle open challenges in the realms of model interpretability and generalizability, training pipelines of data-fluent human neuroscientists, and integrated consideration of data ethics.

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know