Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations

@inproceedings{Kaplan2015MultivariateCA,
  title={Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations},
  author={Jonas T. Kaplan and Kingson Man and Steven G. Greening},
  booktitle={Front. Hum. Neurosci.},
  year={2015}
}
Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has… CONTINUE READING
Tweets
This paper has been referenced on Twitter 13 times. VIEW TWEETS

Figures and Topics from this paper.

Explore Further: Topics Discussed in This Paper

Citations

Publications citing this paper.
SHOWING 1-10 OF 21 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 92 REFERENCES

Sight and sound

  • K. Man, J. T. Kaplan, A. Damasio, K. Meyer
  • 2012
Highly Influential
10 Excerpts

Similar Papers

Loading similar papers…