Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks

Abstract

Using procedures optimized to explore network organization within the individual, the topography of a candidate language network was characterized and situated within the broader context of adjacent networks. The candidate network was first identified using functional connectivity and replicated across individuals, acquisition tasks, and analytic methods. In addition to classical language regions near to perisylvian cortex and temporal pole, regions were also observed in dorsal posterior cingulate, midcingulate, anterior superior frontal and inferior temporal cortex. The candidate network was selectively activated when processing meaningful (as contrasted to non-word) sentences, while spatially adjacent networks showed minimal or even decreased activity. Results were replicated and triplicated across two prospectively acquired cohorts. Examined in relation to adjacent networks, the topography of the language network was found to parallel the motif of other association networks including the transmodal association networks linked to theory of mind and episodic remembering (often collectively called the default network). The several networks contained juxtaposed regions in multiple association zones. Outside of these juxtaposed higher-order networks, we further noted a distinct frontotemporal network situated between language regions and a frontal orofacial motor region and a temporal auditory region. A possibility is that these functionally-related sensorimotor regions might anchor specialization of neighboring association regions that develop into a language network. What is most striking is that the canonical language network appears to be just one of multiple similarly organized, differentially specialized distributed networks that populate the evolutionarily expanded zones of human association cortex.

Altered sense of self during seizures in the posteromedial cortex

“…47 and 48). This finding has now been confirmed in multiple individuals (50,51). Here, the aim was to recapitulate these previous observations in patient S19_137 to best estimate their idiosyncratic network organization within PMC.…”

Light through the fog: using precision fMRI data to disentangle the neural substrates of cognitive control

“…With a large amount of data, functional connectivity measures can achieve high within-subject reliability (test-retest r > 0.85 with over 30 min. of low motion data in the cortex [13]), producing detailed individualized maps of brain systems [12,13,16,[38][39][40]. Regions identified with precision fMRI approaches have been shown to match individualized visual [16] and motor areas [13] identified based on more traditional task localizer approaches.…”

“…Precision fcMRI has also been used to map higher-level association regions. For example, Braga and colleagues used precision fcMRI to identify and separate closely juxtaposed networks associated with "default mode" locations of the brain, which mapped onto differences in task activations associated with episodic projection and social cognition, respectively [39]. This work was recently extended to map a third network associated with language [40].…”

Fronto-parietal homotopy in resting-state functional connectivity predicts task-switching performance

“…Data from the practice phase, first trial in a block, error (incorrect or no response) and post-error trials were excluded from analysis. For each trial type (i.e., single-task, repeat and switch trials) at each CTI, response time (RT) values more extreme than one and a half times the interquartile range (i.e., the difference between the upper and lower quartile) above the upper quartile or below the lower quartile were identified as outliers (Borcard et al 2011) and excluded (mean excluded trials = 5.1%, SD = 1.9%). Mean RTs were, then, computed for each trial type at each CTI and used to calculate two behavioral cost measures: (i) switching costs (Monsell 2003), computed as the difference between the mean RT from switch trials and that from repeat trials; (ii) and mixing costs (Rubin and Meiran 2005), computed as the difference between the mean RT from repeat trials and that from pure trials.…”