Consistency and variability in functional localisers

Abstract

A critical assumption underlying the use of functional localiser scans is that the voxels identified as the functional region-of-interest (fROI) are essentially the same as those activated by the main experimental manipulation. Intra-subject variability in the location of the fROI violates this assumption, reducing the sensitivity of the analysis and biasing the results. Here we investigated consistency and variability in fROIs in a set of 45 volunteers. They performed two functional localiser scans to identify word- and object-sensitive regions of ventral and lateral occipito-temporal cortex, respectively. In the main analyses, fROIs were defined as the category-selective voxels in each region and consistency was measured as the spatial overlap between scans. Consistency was greatest when minimally selective thresholds were used to define “active” voxels (p < 0.05 uncorrected), revealing that approximately 65% of the voxels were commonly activated by both scans. In contrast, highly selective thresholds (p < 10− 4 to 10− 6) yielded the lowest consistency values with less than 25% overlap of the voxels active in both scans. In other words, intra-subject variability was surprisingly high, with between one third and three quarters of the voxels in a given fROI not corresponding to those activated in the main task. This level of variability stands in striking contrast to the consistency seen in retinotopically-defined areas and has important implications for designing robust but efficient functional localiser scans.

Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

“…Dissemination of the data was approved by the IRBs of New York University Langone Medical Center and New Jersey Medical School (4). The word and object processing experiment (36) was approved by the Berkshire National Health Service Research Ethics Committee. The mixed-gambles experiment (35), the rhyme judgment experiment, and the living-nonliving experiments were approved by the University of California, Los Angeles, IRB.…”

Evidencing a place for the hippocampus within the core scene processing network

“…These need not, however, reflect differences in the degree of scene‐sensitivity per se . As discussed by other authors [Duncan et al, 2009; Rossion et al, 2012; Todorov, 2012], it is difficult to determine a priori the appropriate statistical thresholds for detecting activations within a given brain region. The reason for this may arise from several factors; for instance, the shape (and height) of the HRF has been shown to vary across both individuals and brain regions [Aguirre et al, 1998b; Goense et al, 2012; Handwerker et al, 2004].…”

“…In order to (a) avoid biasing the results through selection of an arbitrary threshold, and (b) explore how individual‐level response profiles vary across our putative scene‐sensitive ROIs, we adopted three uncorrected voxel‐wise thresholds for our individual‐level analyses [see Duncan et al, 2009; Engell and McCarthy, 2013]. The individual‐level whole brain Z statistic images (across three spatial smoothing filters) for scenes > objects were thresholded with the following criteria: (i) Z  = 2.3 ( P  = 0.01); (ii) Z  = 3.1 ( P  = 0.001); and (iii) Z  = 3.9 ( P  = 0.0001).…”

How Does Learning to Read Affect Speech Perception?

“…Using a one-back task has the advantage that stimulus category can be varied without changing the task, maintaining a constant cognitive set-the specific stimuli are almost incidental to the task. In addition, it is commonly used for functional localization (Kanwisher et al, 1999;Gazzaley et al, 2005;Peelen and Downing, 2005;Baker et al, 2007;Downing et al, 2007;Duncan et al, 2009).…”