Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review

Michael Pellegrini; Maryam Zoghi; Shapour Jaberzadeh

doi:10.1515/revneuro-2017-0083

Article

Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review

Michael Pellegrini , Maryam Zoghi and Shapour Jaberzadeh

Published/Copyright: January 12, 2018

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From the journal Reviews in the Neurosciences Volume 29 Issue 6

Abstract

Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability – the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

Keywords: grand mean average; non-responder; responder

Acknowledgements

This manuscript is based on research conducted by Michael Pellegrini, a PhD candidate at Monash University, Melbourne, Australia.

Conflict of interest: This project had no external funding, and no financial or other relationships pose a conflict of interest.

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Received: 2017-09-27

Accepted: 2017-11-25

Published Online: 2018-01-12

Published in Print: 2018-08-28

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https://doi.org/10.1515/revneuro-2017-0083

Keywords for this article

grand mean average; non-responder; responder