Individual-subject functional localization increases univariate activation but not multivariate pattern discriminability in the ‘multiple-demand’ frontoparietal network

Abstract

The frontoparietal 'multiple-demand' (MD) control network plays a key role in goal-directed behavior. Recent developments of multivoxel pattern analysis (MVPA) for fMRI data allows for more fine-grained investigations into the functionality and properties of brain systems. In particular, MVPA in the MD network was used to gain better understanding of control processes such as attentional effects, adaptive coding, and representation of multiple task-relevant features, but its use for this network has been limited by overall low decoding levels. A common practice of applying MVPA is by investigating pattern discriminability within a region-of-interest (ROI) using a template mask, thus ensuring that the same brain areas are studied in all participants. This approach offers high sensitivity, but does not take into account differences between individuals in the spatial organization of brain regions. An alternative approach uses independent localizer data for each subject to select the most responsive voxels and define individual ROIs within the boundaries of a group template. Such an approach allows for a refined and targeted localization based on the unique pattern of activity of individual subjects while ensuring that functionally similar brain regions are studied for all subjects. In the current study we tested whether using individual ROIs leads to changes in decodability of task-related neural representations as well as univariate activity across the MD network compared to when using a group template. We used three localizer tasks to separately define subject-specific ROIs: spatial working memory, verbal working memory, and a Stroop task. We then systematically assessed univariate and multivariate results in a separate rule-based criterion task. All the localizer tasks robustly recruited the MD network and evoked highly reliable activity patterns in individual subjects. Consistent with previous studies, we found a clear benefit of the subject-specific ROIs for univariate results from the criterion task, with increased activity in the individual ROIs based on the localizers' data, compared to the activity observed when using the group template. In contrast, there was no benefit of the subject-specific ROIs, as well as no cost, for multivariate results. Both univariate and multivariate results were similar in the individual ROIs defined by each of the three localizers. Our results provide an important empirical evidence for researchers in the field of cognitive control for the use of individual ROIs in the frontoparietal network 2 for both univariate and multivariate analysis of fMRI data, and serve as another step towards standardization and increased comparability across studies.

Comprehension of computer code relies primarily on domain-general executive brain regions

“…This approach stands in contrast to the traditional approach, whereby neural responses are averaged across participants on a voxel-by-voxel basis, and the resulting activation clusters are interpreted via flawed 'reverse inference' from anatomy (e.g., Poldrack, 2006Poldrack, , 2011. Functional localization is particularly important when analyzing responses in fronto-temporo-parietal associative cortices, which are known to be functionally heterogeneous and variable across individuals (Blank et al, 2017;Braga et al, 2019;Fedorenko & Kanwisher, 2009;Shashidhara, Spronkers, et al, 2019).…”

“…Instead, we can directly interpret code-evoked activity within functionally defined regions of interest (Mather et al, 2013). In addition, localization of the MD and language networks is performed in individual participants, which is important given substantial variability in their precise locations across individuals Shashidhara, Spronkers, et al, 2019) and leads to higher sensitivity and functional resolution (Nieto-Castañón & Fedorenko, 2012).…”

Reward motivation increases univariate activity but has limited effect on coding of task-relevant information across the frontoparietal cortex

“…Further studies are required to tease apart the different roles and functions of regions within MD network, and linking the evidence across studies is essential. The double-masking approach that we used in our study to localize the MD network in individual subjects ensures that the targeted areas are similar for all subjects (i.e., within the MD template) and therefore allows for comparability across participants and studies (Shashidhara et al, 2019).…”

“…To compare between regions within the MD network and between sub-regions in LOC, we controlled for the ROI size and used the same number of voxels for all regions. We used a double-masking approach that allowed the use of both a template, consistent across participants, as well as subjectspecific data as derived from the functional localizers (Erez & Duncan, 2015;Shashidhara, Spronkers, & Erez, 2019). For each participant, beta estimates of each condition and run were extracted for each ROI based on the MD network and LOC templates.…”