Task performance changes the amplitude and timing of the BOLD signal

Abstract

Translational studies comparing imaging data of animals and humans have gained increasing scientific interests. With this upcoming translational approach, however, identifying harmonized statistical analysis as well as shared data acquisition protocols and/or combined statistical approaches is necessary. Following this idea, we applied Bayesian Adaptive Regression Splines (BARS), which have until now mainly been used to model neural responses of electrophysiological recordings from rodent data, on human hemodynamic responses as measured via fMRI. Forty-seven healthy subjects were investigated while performing the Attention Network Task in the MRI scanner. Fluctuations in the amplitude and timing of the BOLD response were determined and validated externally with brain activation using GLM and also ecologically with the influence of task performance (i.e. good vs. bad performers). In terms of brain activation, bad performers presented reduced activation bilaterally in the parietal lobules, right prefrontal cortex (PFC) and striatum. This was accompanied by an enhanced left PFC recruitment. With regard to the amplitude of the BOLD-signal, bad performers showed enhanced values in the left PFC. In addition, in the regions of reduced activation such as the parietal and striatal regions, the temporal dynamics were higher in bad performers. Based on the relation between BOLD response and neural firing with the amplitude of the BOLD signal reflecting gamma power and timing dynamics beta power, we argue that in bad performers, an enhanced left PFC recruitment hints towards an enhanced functioning of gamma-band activity in a compensatory manner. This was accompanied by reduced parieto-striatal activity, associated with increased and potentially conflicting beta-band activity.

Keywords

• functional neuroimaging
• bayesian adaptive regression spline
• fmri time courses
• attention