When most fMRI connectivity cannot be detected: insights from time course reliability

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

ABSTRACT The level of correlation between two phenomena is limited by the accuracy at which these phenomena are measured. Despite numerous group reliability studies, the strength of the fMRI connectivity correlation that can be detected given underlying within subject time course reliability remains elusive. Moreover, it is unclear how within subject time course reliability limits the robust detection of connectivity on the group level. We estimated connectivity from 50 individuals engaged in a working memory task. The grand mean connectivity of the connectome equaled r =0.41 (95% CI 0.31-0.50) for the test run and r =0.40 (95% CI 0.29-0.49) for the retest run. However, mean connectivity was reduced to r=0.09 (95% C.I. 0.03-0.16) when test-retest reliability and residual auto-correlations of single time courses were considered, suggesting that less than a quarter of the observed connectivity is reliably detectable. Null hypothesis significance testing (NHST)-based analysis revealed that within subject time course reliability markedly affects the significance levels at which paths can be detected at the group level. This was in particular the case when samples were small or connectome coordinates were randomly selected. With a sample of 50 individuals, the connectome of a test session was completely reproduced in retest sessions at P < 2.54e -6 . Despite perfect group reproducibility at conservative p-values, on average only 0.81 percent of the observed connectivity could be attributed to working memory-related time course fluctuations after corrections. Time course reliability can offer valuable insights on the detectable connectivity and should be assessed more frequently in fMRI investigations.

Authors 6

1. Hans Manner

   University of Graz

   Affiliation as printed

   Department of Economics, University of Graz

2. Cyril R Pernet

   Copenhagen University Hospital

   Affiliation as printed

   Dept. Neurology and Neurobiology Research Unit, Copenhagen University Hospital

3. André Schüppen Aachen IZKF-Interdisciplinary Center for Clinical Research

   RWTH Aachen University

   Affiliation as printed

   IZKF - Interdisciplinary Center for Clinical Research, RWTH Aachen University

4. Dénes Szűcs

   University of Cambridge

   Affiliation as printed

   Department of Psychology, University of Cambridge

5. Guilherme Maia de Oliveira Wood

   University of Graz

   Affiliation as printed

   Institute of Psychology, University of Graz

6. John P. A. Ioannidis

   Stanford University

   Affiliation as printed

   Department of Medicine, Department of Epidemiology and Population Health, Department of Biomedical Data Science, Department of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, United States of America,