Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2016 Mar;19(3):356-65.
doi: 10.1038/nn.4244.

Using goal-driven deep learning models to understand sensory cortex

Daniel L K Yamins  1   2 , James J DiCarlo  1   2
Affiliations
Review

Using goal-driven deep learning models to understand sensory cortex

Daniel L K Yamins et al. Nat Neurosci. 2016 Mar.

Abstract

Fueled by innovation in the computer vision and artificial intelligence communities, recent developments in computational neuroscience have used goal-driven hierarchical convolutional neural networks (HCNNs) to make strides in modeling neural single-unit and population responses in higher visual cortical areas. In this Perspective, we review the recent progress in a broader modeling context and describe some of the key technical innovations that have supported it. We then outline how the goal-driven HCNN approach can be used to delve even more deeply into understanding the development and organization of sensory cortical processing.

PubMed Disclaimer

Comment in

References

    1. Proc Natl Acad Sci U S A. 2014 Jun 10;111(23):8619-24 - PubMed
    1. J Neurosci. 2015 Sep 30;35(39):13402-18 - PubMed
    1. Nat Rev Neurosci. 2011 Nov 23;13(1):51-62 - PubMed
    1. Cereb Cortex. 1991 Jan-Feb;1(1):1-47 - PubMed
    1. Annu Rev Neurosci. 1995;18:555-86 - PubMed