Rxivist logo

Measures of neural similarity

By Sebastian Bobadilla-Suarez, Christiane Ahlheim, A. Mehrotra, A. Panos, Bradley C Love

Posted 12 Oct 2018
bioRxiv DOI: 10.1101/439893 (published DOI: 10.1007/s42113-019-00068-5)

One fundamental question is what makes two brain states similar. For example, what makes the activity in visual cortex elicited from viewing a robin similar to a sparrow? One common assumption in fMRI analysis is that neural similarity is described by Pearson correlation. However, there are a host of other possibilities, including Minkowski and Mahalanobis measures, with each differing in its mathematical, theoretical, neural computational assumptions. Moreover, the operable measures may vary across brain regions and tasks. Here, we evaluated which of several competing similarity measures best captured neural similarity. Our technique uses a decoding approach to assess the information present in a brain region and the similarity measures that best correspond to the classifier's confusion matrix are preferred. Across two published fMRI datasets, we found the preferred neural similarity measures were common across brain regions, but differed across tasks. Moreover, Pearson correlation was consistently surpassed by alternatives.

Download data

  • Downloaded 2,936 times
  • Download rankings, all-time:
    • Site-wide: 4,294
    • In neuroscience: 376
  • Year to date:
    • Site-wide: 22,391
  • Since beginning of last month:
    • Site-wide: 30,086

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News