Abstract
Perceptual Learning (PL - improved perceptual performance following practice) is traditionally viewed as relying on neural sensitivity increases in sensory brain regions. However, recent evidence suggests that PL involves higher-order regions in parietal and frontal cortices. This work focuses on two large–scale brain networks comprising fronto-parietal regions and their neural tuning as PL progresses. 20 Subjects performed an orientation discrimination task on Gabor stimuli over the course of 4 days (data from Kahnt et al. 2011). The first and last days were conducted during fMRI-BOLD imaging (1320 trials), while the second and third day were performed in a mock-scanner (3300 trials). 11 orientations were presented, allowing precise measurements of psychometric performance and orientation tuning functions in brain regions during PL. Performance significantly increased from day 1 to day 4 for all orientations, indicating substantial PL. Concomitantly, we find significant BOLD-response increases in a task-positive network (TPN: Insula, ACC, preSMA) and significant BOLD-response decreases in a task-negative network (TNN: LPC, PCC, vmPFC). BOLD changes in these two networks (but not in sensory areas) correlated with perceptual performance and thus scaled with task difficulty. Comparing the first and last day BOLD-profiles (i.e. PL-related changes) showed that in both networks, tuning functions change from nonlinear to linear and drastically increase their response range for all regions, nearly tripling for the TNN-regions. Our results show that PL encompasses marked influences on neural responses in large-scale brain networks comprising fronto-parietal areas. We show that such regions - often interpreted as reflecting a brain "default mode network" (cf. TNN) - change their task-relevant tuning over the course of PL. These data further strengthen the notion that PL is mostly driven by altering neural responses in higher-order decision regions rather than simply by changing sensory tuning.
Meeting abstract presented at VSS 2012