Representational Organization of Novel Task Sets during Proactive Encoding

Abstract

Recent multivariate analyses of brain data have boosted our understanding of the organizational principles that shape neural coding. However, most of this progress has focused on perceptual visual regions (Connolly et al., 2012), whereas far less is known about the organization of more abstract, action-oriented representations. In this study, we focused on humans' remarkable ability to turn novel instructions into actions. While previous research shows that instruction encoding is tightly linked to proactive activations in frontoparietal brain regions, little is known about the structure that orchestrates such anticipatory representation. We collected fMRI data while participants (both males and females) followed novel complex verbal rules that varied across control-related variables (integrating within/across stimuli dimensions, response complexity, target category) and reward expectations. Using representational similarity analysis (Kriegeskorte et al., 2008), we explored where in the brain these variables explained the organization of novel task encoding, and whether motivation modulated these representational spaces. Instruction representations in the lateral PFC were structured by the three control-related variables, whereas intraparietal sulcus encoded response complexity and the fusiform gyrus and precuneus organized its activity according to the relevant stimulus category. Reward exerted a general effect, increasing the representational similarity among different instructions, which was robustly correlated with behavioral improvements. Overall, our results highlight the flexibility of proactive task encoding, governed by distinct representational organizations in specific brain regions. They also stress the variability of motivation-control interactions, which appear to be highly dependent on task attributes, such as complexity or novelty.

Neural representation of newly instructed rule identities during early implementation trials

“…One such study by Muhle-Karbe et al (2017) identified LPFC activity patterns associated with highly familiar categorization routines regarding house pictures vs. face pictures – but, importantly, not regarding the concrete stimulus-response rules (e.g., the instructed responses for each of two different faces) underlying a multitude of individual face or house categorization tasks each involving a unique set of stimuli. Similar conclusions apply to related studies (González-García et al, 2017; Palenciano et al, 2019). Another approach pursued by Cole et al (Cole et al, 2011; Cole et al, 2013) provided evidence for the principle of ‘rule compositionality’ (see also Reverberi et al, 2012; Yang et al, 2019).…”

Neural oscillations track the maintenance and proceduralization of novel instructions

“…A growing number of fMRI studies has primarily focused on revealing which brain regions support the implementation of novel task sets (Demanet et al, 2016;González-García, Arco, Palenciano, Ramírez, & Ruz, 2017;Hartstra, Kühn, Verguts, & Brass, 2011;Hartstra, Waszak, & Brass, 2012;Ruge & Wolfensteller, 2010) and, more recently, on characterizing implementation-specific neural representations (Bourguignon, Braem, Hartstra, De Houwer, & Brass, 2018; González-García, Formica, Wisniewski, & Brass, 2019;Muhle-Karbe, Duncan, De Baene, Mitchell, & Brass, 2017;Palenciano, González-García, Arco, Pessoa, & Ruz, 2019;Ruge, Schäfer, Zwosta, Mohr, & Wolfensteller, 2019). These results consistently point towards a crucial role of frontoparietal regions, and in particular of the prefrontal cortex (PFC).…”

Frontoparietal action-oriented codes support novel instruction implementation

“…As a first step, we investigated which brain regions were predominantly involved in instruction prioritization. Our intuition was that prioritization would boost implementation signals and, as such, we expected a frontoparietal network to be particularly crucial, as it is usually involved in the implementation of novel task sets 11,14–17,24 . We thus established a set of a priori candidate regions that encompassed frontal (inferior and middle frontal gyri) and (inferior and superior) parietal cortices (see Fig.…”

“…To elucidate which signals govern implementation in control-related regions, we carried out the template tracking procedure on each FPN region separately. Furthermore, we decided to include the ventral visual cortex (VVC) in this analysis to explore the effect of implementation in higher-order visual regions, since these have been consistently shown to be involved in instruction processing 11,13,14,16 .…”

“…Instruction implementation also has a profound impact on brain activity, as shown by electroencephalography and fMRI studies. In particular, the intention to execute an instruction induces automatic motor activation 8,9 , engages different brain regions to coordinate novel stimuli and responses 10–14 , and alters the neural code of the encoded instruction 15,16 .…”