How is higher cognitive function organized in the human parietal cortex? A century of neuropsychology and 30 years of functional neuroimaging has implicated the parietal lobe in many different verbal and nonverbal cognitive domains. There is little clarity, however, on how these functions are organized, that is, where do these functions coalesce (implying a shared, underpinning neurocomputation) and where do they divide (indicating different underlying neural functions). Until now, there has been no multi-domain synthesis in order to reveal where there is fusion or fission of functions in the parietal cortex. This aim was achieved through a large-scale activation likelihood estimation (ALE) analysis of 386 studies (3952 activation peaks) covering 8 cognitive domains. A tripartite, domain-general neuroanatomical division and 5 principles of cognitive organization were established, and these are discussed with respect to a unified theory of parietal functional organization.

The default mode network (DMN) and semantic network (SN) are two of the most extensively studied systems, and both are increasingly used as clinical biomarkers in neurological studies. There are strong theoretical reasons to assume a relationship between the networks, as well as anatomical evidence that they might rely on overlapping cortical regions, such as the anterior temporal lobe (ATL) or angular gyrus (AG). Despite these strong motivations, the relationship between the two systems has received minimal attention. We directly compared the SN and DMN using a large (n = 69) distortion-corrected functional MRI (fMRI) dataset, spanning a range of semantic and nonsemantic tasks that varied input modality. The results showed that both networks fractionate depending on the semantic nature of the task, stimulus type, modality, and task difficulty. Furthermore, despite recent claims that both AG and ATL are semantic hubs, the two areas responded very differently, with results supporting the role of ATL, but not AG, in semantic representation. Specifically, the left ATL was positively activated for all semantic tasks, but deactivated during nonsemantic task performance. In contrast, the left AG was deactivated for all tasks, with the level of deactivation related to task difficulty. Thus, ATL and AG do not share a common interest in semantic tasks, but, rather, a common "disinterest" in nonsemantic tasks. The implications for the variability in the DMN, its cognitive coherence, and interpretation of resting-state fMRI data are discussed.semantic network | default mode network | distortion-corrected fMRI | anterior temporal lobe | angular gyrus T wo substantial bodies of research literature, spanning cognitive and clinical neuroscience fields, have been dedicated to exploring the function and components of the semantic network (SN) and the default mode network (DMN). The DMN is an anatomically defined network that shows task-related deactivation during many goal-directed tasks (i.e., rest > task) (1) and can be reliably delineated using techniques such as independent components analysis (ICA) of resting-state functional MRI (fMRI) (2). The SN is a fronto-temporo-parietal network that is sensitive to semantic content in comparisons of semantic tasks > rest/nonsemantic control tasks (3). Although investigations of the DMN and SN have been primarily independent of each other, there are good reasons to compare the two networks directly. First, the networks might share common cognitive functions. One prominent theory suggests that during "rest," the brain is engaged in the activation of rich conceptual representations, and thus default-mode processing places strong demands on the semantic system (4). Secondly, the DMN and SN engage some common anatomical areas. The DMN consistently includes medial prefrontal cortex, parietal areas [angular gyrus (AG), precuneus, posterior cingulate cortex (PCC)], and, somewhat more variably, the lateral anterior temporal lobe (ATL) and hippocampus (1, 5). Some of these areas are considered...

Numerous cognitive domains have been associated with the lateral parietal cortex, yet how these disparate functions are packed into this region remains unclear. Whilst areas within the dorsal and the ventral parietal cortex (DPC and VPC) show differential function, there is considerable disagreement as to what these functions might be. Studies focussed on individual domains have plotted out variations of function across the region. Direct cross-domain comparisons are rare yet, when they have been undertaken, at least some regions (particularly the intraparietal sulcus [IPS] and core angular gyrus [AG]) appear to have contrastive domain-general qualities. In order to pursue this parietal puzzle, this study utilized both functional and resting-state magnetic resonance imaging to investigate a potential unifying neurocomputational framework-in which both domain general as well as domain-selective regions arise from differential patterns of connectivity into subregions of the lateral parietal cortex. Specifically we found that, consistent with their contrastive patterns of functional connectivity, subregions of DPC (anterior IPS) and VPC (AG) exhibit counterpointed functions sensitive to task/item-difficulty irrespective of cognitive domain. We propose that these regions serve as top-down executively penetrated and automatic bottom-up domain-general buffers of active information, respectively. In contrast, other parietal and nonparietal regions are tuned toward specific domains.

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Built upon a wealth of neuroimaging, neurostimulation, and neuropsychology data, a recent proposal set forth a framework termed controlled semantic cognition (CSC) to account for how the brain underpins the ability to flexibly use semantic knowledge (Lambon Ralph et al., 2017; Nature Reviews Neuroscience). In CSC, the ‘semantic control’ system, underpinned predominantly by the prefrontal cortex, dynamically monitors and modulates the ‘semantic representation’ system that consists of a ‘hub’ (anterior temporal lobe, ATL) and multiple ‘spokes’ (modality-specific areas). CSC predicts that unfamiliar and exacting semantic tasks should intensify communication between the ‘control’ and ‘representation’ systems, relative to familiar and less taxing tasks. In the present study, we used functional magnetic resonance imaging (fMRI) to test this hypothesis. Participants paired unrelated concepts by canonical colours (a less accustomed task – e.g., pairing ketchup with fire-extinguishers due to both being red) or paired well-related concepts by semantic relationship (a typical task – e.g., ketchup is related to mustard). We found the ‘control’ system was more engaged by atypical than typical pairing. While both tasks activated the ATL ‘hub’, colour pairing additionally involved occipitotemporal ‘spoke’ regions abutting areas of hue perception. Furthermore, we uncovered a gradient along the ventral temporal cortex, transitioning from the caudal ‘spoke’ zones preferring canonical colour processing to the rostral ‘hub’ zones preferring semantic relationship. Functional connectivity also differed between the tasks: Compared with semantic pairing, colour pairing relied more upon the inferior frontal gyrus, a key node of the control system, driving enhanced connectivity with occipitotemporal ‘spoke’. Together, our findings characterise the interaction within the neural architecture of semantic cognition – the control system dynamically heightens its connectivity with relevant components of the representation system, in response to different semantic contents and difficulty levels.

Our understanding about the functionality of the brain’s default network (DN) has significantly evolved over the past decade. Whereas traditional views define this network based on its suspension/disengagement during task-oriented behavior, contemporary accounts have characterized various situations wherein the DN actively contributes to task performance. However, it is unclear how different task-contexts drive componential regions of the DN to coalesce into a unitary network and fractionate into different subnetworks. Here we report a compendium of evidence that provides answers to these questions. Across multiple analyses, we found a striking dyadic structure within the DN in terms of the profiles of task-triggered fMRI response and effective connectivity, significantly extending beyond previous inferences based on meta-analysis and resting-state activities. In this dichotomy, one subset of DN regions prefers mental activities “interfacing with” perceptible events, while the other subset prefers activities “detached from” perceptible events. While both show a common “aversion” to sensory-motoric activities, their differential preferences manifest a subdivision that sheds light upon the taxonomy of the brain’s memory systems. This dichotomy is consistent with proposals of a macroscale gradational structure spanning across the cerebrum. This gradient increases its representational complexity, from primitive sensory-motoric processing, through lexical-semantic representations, to elaborated self-generated thoughts.

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The parietal cortex (PC) is implicated in a confusing myriad of different cognitive processes/tasks. Consequently, understanding the nature and organization of the core underlying neurocomputations is challenging. According to the Parietal Unified Connectivity-biased Computation model, two properties underpin PC function and organization. Firstly, PC is a multidomain, context-dependent buffer of time- and space-varying input, the function of which, over time, becomes sensitive to the statistical temporal/spatial structure of events. Secondly, over and above this core buffering computation, differences in long-range connectivity will generate graded variations in task engagement across subregions. The current study tested these hypotheses using a group independent component analysis technique with two independent functional magnetic resonance imaging datasets (task and resting state data). Three functional organizational principles were revealed: Factor 1, inferior PC was sensitive to the statistical structure of sequences for all stimulus types (pictures, sentences, numbers); Factor 2, a dorsal–ventral variation in generally task-positive versus task-negative (variable) engagement; and Factor 3, an anterior–posterior dimension in inferior PC reflecting different engagement in verbal versus visual tasks, respectively. Together, the data suggest that the core neurocomputation implemented by PC is common across domains, with graded task engagement across regions reflecting variations in the connectivity of task-specific networks that interact with PC.