Individual differences in gradients of intrinsic connectivity within the semantic network relate to distinct aspects of semantic cognition

Whole-Brain Dimensions of Intrinsic Connectivity Capture Modality-Specific and Heteromodal Language Representations

Comprehension of spoken and written language involves a hierarchical sequence of modality-specific and heteromodal processes. While these have been localized to different regions, modality-selective responses extend beyond them, implicating large-scale network organization in language comprehension. Dimensions of whole-brain connectivity, derived from intrinsic activity, have been proposed as a general organizing framework for cognition. Here, we test their utility in accounting for the spatial distribution of task-evoked activity during language comprehension. We investigated brain activity in human males and females in response to psycholinguistic variables linked to input processing and meaning in a sentence comprehension task presented both visually and auditorily. Macroscale patterns of brain activity were similar across modalities for sentence-level and semantic variables, but effects of orthographic and phonological distance were negatively correlated between modalities. The first dimension, separating heteromodal and unimodal cortices, showed no differences across modalities for sentence processing and semantic variables and opposite effects of word length and orthographic/phonological distance for spoken and written words, supporting the notion that higher-order processing requires heteromodal resources different to those linked to input processing. The second dimension, separating auditory-motor and visual processes, showed an asymmetry in the recruitment of the unimodal systems-listening to long and semantically dissimilar words involved stronger recruitment of primary auditory-motor regions and low visual engagement. These findings show that the language system is organized according to large-scale axes of intrinsic connectivity, with psycholinguistic processes varying systematically along whole-brain dimensions. This supports the view that language comprehension reflects general principles of cortical organization.

Functional differentiation of the default and frontoparietal control networks predicts individual differences in creative achievement: evidence from macroscale cortical gradients

Much of the research on the neural correlates of creativity has emphasized creative cognition, and growing evidence suggests that creativity is related to functional properties of the default and frontoparietal control networks. The present work expands on this body of evidence by testing associations of creative achievement with connectivity profiles of brain networks assessed using macroscale cortical gradients. Using resting-state connectivity functional magnetic resonance imaging in 2 community samples (N's = 236 and 234), we found evidence that creative achievement is positively associated with greater functional dissimilarity between core regions of the default and frontoparietal control networks. These results suggest that creative achievement is supported by the ability of these 2 networks to carry out distinct cognitive roles. This research provides further evidence, using a cortical gradient approach, that individual differences in creative achievement can be predicted from functional properties of brain networks involved in higher-order cognition, and it aligns with past research on the functional connectivity correlates of creative task performance.

Changes in the structure of spontaneous speech predict the disruption of hierarchical brain organization in first-episode psychosis

Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher-order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis. We hypothesized that these changes as revealed in spontaneous speech patterns may act as readouts of alterations in the configuration of this unimodal-to-transmodal axis of cortical organization in psychosis. Results from 29 patients with first-episodic psychosis (FEP) and 29 controls scanned with 7 T resting-state fMRI confirmed a compression of the cortical hierarchy in FEP, which affected metrics of the hierarchical distance between the sensorimotor and default mode networks, and of the hierarchical organization within the semantic network. These organizational changes were predicted by graphs representing semantic and syntactic associations between meaningful units in speech produced during picture descriptions. These findings unite psychosis, language, and the cortical hierarchy in a single conceptual scheme, which helps to situate language within the neurocognition of psychosis and opens the clinical prospect for mental dysfunction to become computationally measurable in spontaneous speech.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Macroscale brain states support the control of semantic cognition

A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.

Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

Atypical cortical hierarchy in Aβ-positive older adults and its reflection in spontaneous speech

Abnormal deposition of Aβ amyloid is an early neuropathological marker of Alzheimer's disease (AD), arising long ahead of clinical symptoms. Non-invasive measures of associated early neurofunctional changes, together with easily accessible behavioral readouts of these changes, could be of great clinical benefit. We pursued this aim by investigating large-scale cortical gradients of functional connectivity with functional MRI, which capture the hierarchical integration of cortical functions, together with acoustic-prosodic features from spontaneous speech, in cognitively unimpaired older adults with and without Aβ positivity (total N = 188). We predicted distortions of the cortical hierarchy associated with prosodic changes in the Aβ + group. Results confirmed substantially altered cortical hierarchies and less variability in these in the Aβ + group, together with an increase in quantitative prosodic measures, which correlated with gradient variability as well as digit span test scores. Overall, these findings confirm that long before the clinical stage and objective cognitive impairment, increased risk of cognitive decline as indexed by Aβ accumulation is marked by neurofunctional changes in the cortical hierarchy, which are related to automatically extractable speech patterns and alterations in working memory functions.

Individual word representations dissociate from linguistic context along a cortical unimodal to heteromodal gradient

Language comprehension involves multiple hierarchical processing stages across time, space, and levels of representation. When processing a word, the sensory input is transformed into increasingly abstract representations that need to be integrated with the linguistic context. Thus, language comprehension involves both input-driven as well as context-dependent processes. While neuroimaging research has traditionally focused on mapping individual brain regions to the distinct underlying processes, recent studies indicate that whole-brain distributed patterns of cortical activation might be highly relevant for cognitive functions, including language. One such pattern, based on resting-state connectivity, is the 'principal cortical gradient', which dissociates sensory from heteromodal brain regions. The present study investigated the extent to which this gradient provides an organizational principle underlying language function, using a multimodal neuroimaging dataset of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) recordings from 102 participants during sentence reading. We found that the brain response to individual representations of a word (word length, orthographic distance, and word frequency), which reflect visual; orthographic; and lexical properties, gradually increases towards the sensory end of the gradient. Although these properties showed opposite effect directions in fMRI and MEG, their association with the sensory end of the gradient was consistent across both neuroimaging modalities. In contrast, MEG revealed that properties reflecting a word's relation to its linguistic context (semantic similarity and position within the sentence) involve the heteromodal end of the gradient to a stronger extent. This dissociation between individual word and contextual properties was stable across earlier and later time windows during word presentation, indicating interactive processing of word representations and linguistic context at opposing ends of the principal gradient. To conclude, our findings indicate that the principal gradient underlies the organization of a range of linguistic representations while supporting a gradual distinction between context-independent and context-dependent representations. Furthermore, the gradient reveals convergent patterns across neuroimaging modalities (similar location along the gradient) in the presence of divergent responses (opposite effect directions).

Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient

Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain-wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory-to-association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test-retest data from the young adult Human Connectome Project (HCP-YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge-wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting-state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP-aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP-YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge-wise FC measures in the search for brain-behavior associations.