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Reply to: Towards increasing the clinical applicability of machine learning biomarkers in psychiatry

The Original Article was published on 05 April 2021

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Fig. 1: Distribution of classification accuracies obtained with random permutations of group membership labels.
Fig. 2: Discriminating locations produced by varying the number of voxels included from each participant.

Data availability

No new data are used in this response; all data are available in the original publication upon reasonable request from the corresponding author.

Code availability

The custom computer code that was used in the main analysis of this study is available at


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The data were analysed by M.A.J. and V.L.C. The paper was written by M.A.J., V.L.C. and D.B.

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Correspondence to Marcel Adam Just.

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The authors declare no competing interests.

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Peer review information Nature Human Behaviour thanks Barry Horwitz and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Supplementary Information

Supplementary Discussion, Supplementary Fig. 1 and Supplementary References.

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Just, M.A., Cherkassky, V.L. & Brent, D. Reply to: Towards increasing the clinical applicability of machine learning biomarkers in psychiatry. Nat Hum Behav 5, 433–435 (2021).

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