Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function

Abstract

The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial / episodic processing domains. These results suggest progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings including how repeating organizational motifs may emerge during development.

A 3.5-minute-long reading-based fMRI localizer for the language network

“…The standard language localizer (Fedorenko et al, 2010) investigated in our study has been widely used over the past decade (e.g., Fedorenko et al, 2010; Mahowald & Fedorenko, 2016; Braga et al, 2020; Lipkin et al, 2022; Du et al, 2024). The localizer contrasts the reading of well-formed sentences versus sequences of nonwords.…”

“…Correspondingly, reliance on these group-averaging approaches can lead to low sensitivity and functional resolution (Brett et al, 2002; Saxe et al, 2006; Nieto-Castañón & Fedorenko, 2012). Inter-individual variability is particularly problematic when functional regions of interest lie in proximity to functionally distinct regions, as is the case with both frontal and temporal language regions (e.g., Tomaiuolo et al, 1999; Fedorenko et al, 2012; Tahmasebi et al, 2012; Deen et al, 2015; Braga et al, 2020; Du et al, 2024; see Fedorenko & Blank, 2020, for discussion of this issue for ‘Broca’s area’).…”

Individual variability in neural representations of mind-wandering

“…For S3, the top and bottom networks, respectively, were a network that included language-related regions (e.g. left lateral temporal cortex) and a network that was consistent with frontoparietal network B (FPN-B) (Du et al, 2024); the positive associations between mind-wandering and the language network were even stronger than associations with DNa or DNb.…”