Search

Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.

Peer reviewed: True, Understanding how thought emerges from the topographical structure of the cerebral cortex is a primary goal of cognitive neuroscience. Recent work has revealed a principal gradient of intrinsic connectivity capturing the separation of sensory-motor cortex from transmodal regions of the default mode network (DMN); this is thought to facilitate memory-guided cognition. However, studies have not explored how this dimension of connectivity changes when conceptual retrieval is controlled to suit the context. We used gradient decomposition of informational connectivity in a semantic association task to establish how the similarity in connectivity across brain regions changes during familiar and more original patterns of retrieval. Multivoxel activation patterns at opposite ends of the principal gradient were more divergent when participants retrieved stronger associations; therefore, when long-term semantic information is sufficient for ongoing cognition, regions supporting heteromodal memory are functionally separated from sensory-motor experience. In contrast, when less related concepts were linked, this dimension of connectivity was reduced in strength as semantic control regions separated from the DMN to generate more flexible and original responses. We also observed fewer dimensions within the neural response towards the apex of the principal gradient when strong associations were retrieved, reflecting less complex or varied neural coding across trials and participants. In this way, the principal gradient explains how semantic cognition is organised in the human cerebral cortex: the separation of DMN from sensory-motor systems is a hallmark of the retrieval of strong conceptual links that are culturally shared.

When we remember a city that we have visited, we retrieve places related to finding our goal but also non-target locations within this environment. Yet, understanding how the human brain implements the neural computations underlying holistic retrieval remains unsolved, particularly for shared aspects of environments. Here, human participants learned and retrieved details from three partially overlapping environments while undergoing high-resolution functional magnetic resonance imaging (fMRI). Our findings show reinstatement of stores even when they are not related to a specific trial probe, providing evidence for holistic environmental retrieval. For stores shared between cities, we find evidence for pattern separation (representational orthogonalization) in hippocampal subfield CA2/3/DG and repulsion in CA1 (differentiation beyond orthogonalization). Additionally, our findings demonstrate that medial prefrontal cortex (mPFC) stores representations of the common spatial structure, termed schema, across environments. Together, our findings suggest how unique and common elements of multiple spatial environments are accessed computationally and neurally., The authors examine how we differentiate highly similar places from each other. They provide evidence for complementary neural mechanisms in the human hippocampus and prefrontal cortex involved in processing interfering and common elements important to remembering places that we have visited.

The flexible retrieval of knowledge is critical in everyday situations involving problem solving, reasoning and social interaction. Current theories emphasise the importance of a left-lateralised semantic control network (SCN) in supporting flexible semantic behaviour, while a bilateral multiple-demand network (MDN) is implicated in executive functions across domains. No study, however, has examined whether semantic and non-semantic demands are reflected in a common neural code within regions specifically implicated in semantic control. Using functional MRI and univariate parametric modulation analysis as well as multivariate pattern analysis, we found that semantic and non-semantic demands gave rise to both similar and distinct neural responses across control-related networks. Though activity patterns in SCN and MDN could decode the difficulty of both semantic and verbal working memory decisions, there was no shared common neural coding of cognitive demands in SCN regions. In contrast, regions in MDN showed common patterns across manipulations of semantic and working memory control demands, with successful cross-classification of difficulty across tasks. Therefore, SCN and MDN can be dissociated according to the information they maintain about cognitive demands.

While the multiple-demand network plays an established role in cognitive flexibility, the role of default mode network is more poorly understood. In this study, we used a semantic feature matching task combined with multivoxel pattern decoding to test contrasting functional accounts. By one view, default mode and multiple-demand networks have opposing roles in cognition; consequently, while multiple-demand regions can decode current goal information, semantically-relevant default network regions might decode conceptual similarity irrespective of task demands. Alternatively, default mode regions might show sensitivity to changing task demands like multiple-demand regions, consistent with evidence that both networks dynamically alter their patterns of connectivity depending on the context. Our task required participants to integrate conceptual knowledge with changing task goals, such that successive decisions were based on different features of the items (colour, shape and size). This allowed us to simultaneously decode semantic category and current goal information using a whole-brain searchlight decoding approach. As expected, multiple-demand regions represented information about the currently-relevant conceptual feature, yet similar decoding results were found in default mode network regions, including angular gyrus and posterior cingulate cortex. Semantic category irrespective of task demands could be decoded in lateral occipital cortex, but not in most regions of default mode network. These results show that conceptual information related to the current goal dominates the multivariate response within default mode network. In this way, default mode network nodes support flexible memory retrieval by modulating their response to suit active task goals, alongside regions of multiple-demand cortex.Significance StatementWe tested contrasting accounts of default mode network (DMN) function using multivoxel pattern analysis. By one view, semantically-relevant parts of DMN represent conceptual similarity, irrespective of task context. By an alternative view, DMN tracks changing task demands. Our semantic feature matching task required participants to integrate conceptual knowledge with task goals, such that successive decisions were based on different features of the items. We demonstrate that DMN regions can decode current goal, alongside multiple-demand regions traditionally associated with cognitive control. The successful decoding of goal information plus largely absent category decoding effects within DMN indicates that this network supports flexible semantic cognition.

Emerging studies have emphasized the importance of the fidelity of cortical representation in forming enduring episodic memory. No study, however, has examined whether there are age-related reductions in representation fidelity that can explain memory declines in normal aging. Using functional MRI and multivariate pattern analysis, we found that older adults showed reduced representation fidelity in the visual cortex, which accounted for their decreased memory performance even after controlling for the contribution of reduced activation level. This reduced fidelity was specifically due to older adults' poorer item-specific representation, not due to their lower activation level and variance, greater variability in neuro-vascular coupling, or decreased selectivity of categorical representation (i.e., dedifferentiation). Older adults also showed an enhanced subsequent memory effect in the prefrontal cortex based on activation level, and their prefrontal activation was associated with greater fidelity of representation in the visual cortex and better memory performance. The fidelity of cortical representation thus may serve as a promising neural index for better mechanistic understanding of the memory declines and its compensation in normal aging.