Proactive and reactive cognitive control rely on flexible use of the ventrolateral prefrontal cortex

Abstract

The role of ventral versus dorsolateral prefrontal regions in instantiating proactive and reactive cognitive control remains actively debated, with few studies parsing cue versus probe‐related activity. Rapid sampling (460 ms), long cue–probe delays, and advanced analytic techniques (deconvolution) were therefore used to quantify the magnitude and variability of neural responses during the AX Continuous Performance Test (AX‐CPT; N = 46) in humans. Behavioral results indicated slower reaction times during reactive cognitive control (AY trials) in conjunction with decreased accuracy and increased variability for proactive cognitive control (BX trials). The anterior insula/ventrolateral prefrontal cortex (aI/VLPFC) was commonly activated across comparisons of both proactive and reactive cognitive control. In contrast, activity within the dorsomedial and dorsolateral prefrontal cortex was limited to reactive cognitive control. The instantiation of proactive cognitive control during the probe period was also associated with sparse neural activation relative to baseline, potentially as a result of the high degree of neural and behavioral variability observed across individuals. Specifically, the variability of the hemodynamic response function (HRF) within motor circuitry increased after the presentation of B relative to A cues (i.e., late in HRF) and persisted throughout the B probe period. Finally, increased activation of right aI/VLPFC during the cue period was associated with decreased motor circuit activity during BX probes, suggesting a possible role for the aI/VLPFC in proactive suppression of neural responses. Considered collectively, current results highlight the flexible role of the VLPFC in implementing cognitive control during the AX‐CPT task but suggest large individual differences in proactive cognitive control strategies.

A comparison of denoising pipelines in high temporal resolution task‐based functional magnetic resonance imaging data

“…MMAT HRFs were based on the first 22.08 s following block onset. Based on our previous publications (Mayer et al, ; Ryman et al, ), PSC was calculated by summing all beta coefficients between 3.68 and 5.06 s (AX‐CPT) or 4.14 and 8.28 s (MMAT) post‐onset, corresponding to the peak period of the HRF, then dividing by the average of the constant term across the individual runs.…”

“…The primary dataset consisted of 46 healthy participants (28 males; mean age = 31.8 ± 7.4 years; mean education = 15.2 ± 1.9 years) collected during an erfMRI (AX Continuous Performance Test [AX‐CPT]) and rsfMRI paradigm on a 32‐channel coil with multiband capabilities (Ryman et al, ). Forty‐four of these subjects also completed a relatively short duration bdfMRI (multimodal attention task [MMAT]).…”

“…An intermodal version of the AX‐CPT was used as our erfMRI design (Ryman et al, ). Briefly, participants were exposed to a continuous stream of letters that were presented in either the visual (i.e., the cues) or auditory (i.e., the probes) modality.…”

“…The primary sensorimotor cortex (SMC) and supplementary motor area (SMA) were empirically defined as signal regions based all tasks/trials commonly involving a button press. The ventrolateral prefrontal cortex (VLPFC) was defined using a 12-mm sphere (Talairach coordinates: 49,28,and 10) and has been shown to be active across all selected contrasts (Dolcos, Wang, & Mather, 2014;Mayer et al, 2016;Mayer, Franco, Canive, & Harrington, 2009;Ryman et al, 2019). Thus, any potential effects on signal should be greatest within motor regions with differential motor To maximize consistency across comparisons, data from the MP24 pipeline results were next compared to FIX and AROMA pipeline results for the AX-CPT task.…”

“…MMAT HRFs were based on the first 22.08 s following block onset. Based on our previous publications(Mayer et al, 2016;Ryman et al, 2019), PSC was calculated by summing all beta coefficients between 3.68 and 5.06 s (AX-CPT) or 4.14 and 8.28 s (MMAT) post-onset, corresponding to the peak period of the HRF, then dividing by the average of the constant term across the individual runs.The primary outcome variable was a t-statistic resulting from pairwise PSC comparisons at the group level. This metric informs as to whether differences in the denoising pipelines were statistically meaningful and robust enough to be detected using standard thresholding criteria.…”