Temporal multivariate pattern analysis (tMVPA): A single trial approach exploring the temporal dynamics of the BOLD signal

Luca Vizioli, Alexander Bratch, Junpeng Lao, Kamil Ugurbil, Lars Muckli, Essa Yacoub

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Background: fMRI provides spatial resolution that is unmatched by non-invasive neuroimaging techniques. Its temporal dynamics however are typically neglected due to the sluggishness of the hemodynamic signal. New Methods: We present temporal multivariate pattern analysis (tMVPA), a method for investigating the temporal evolution of neural representations in fMRI data, computed on single-trial BOLD time-courses, leveraging both spatial and temporal components of the fMRI signal. We implemented an expanding sliding window approach that allows identifying the time-window of an effect. Results: We demonstrate that tMVPA can successfully detect condition-specific multivariate modulations over time, in the absence of mean BOLD amplitude differences. Using Monte-Carlo simulations and synthetic data, we quantified family-wise error rate (FWER) and statistical power. Both at the group and single-subject levels, FWER was either at or significantly below 5%. We reached the desired power with 18 subjects and 12 trials for the group level, and with 14 trials in the single-subject scenario. Comparison with existing methods: We compare the tMVPA statistical evaluation to that of a linear support vector machine (SVM). SVM outperformed tMVPA with large N and trial numbers. Conversely, tMVPA, leveraging on single trials analyses, outperformed SVM in low N and trials and in a single-subject scenario. Conclusion: Recent evidence suggesting that the BOLD signal carries finer-grained temporal information than previously thought, advocates the need for analytical tools, such as tMVPA, tailored to investigate BOLD temporal dynamics. The comparable performance between tMVPA and SVM, a powerful and reliable tool for fMRI, supports the validity of our technique.

Original languageEnglish (US)
Pages (from-to)74-87
Number of pages14
JournalJournal of Neuroscience Methods
StatePublished - Oct 1 2018

Bibliographical note

Publisher Copyright:
© 2018 Elsevier B.V.


  • BOLD
  • MVPA
  • Mean BOLD amplitude
  • Multivariate
  • Temporal analysis


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