bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/864603

Bipartite functional fractionation within the default network supports disparate forms of internally oriented cognition

Chiou, R.·Humphreys, G.·Lambon Ralph, M.
View original source ↗Export metadata ↓

Abstract

The default network (DN) becomes active when the mind is steered internally towards self-generated thoughts but turns dormant when the mind is directed externally towards the outside world. While hypotheses have been proposed to characterise the association and dissociation between different component areas of the DN, it remains unclear how they coalesce into a unitary network and fractionate into different sub-networks. Here we identified two distinct subsystems within the DN - while both subsystems show common disinterest in externally-oriented visuospatial tasks, their functional profiles differ strikingly according to the preferred contents of thoughts, preferred modes of task requirement, and causative neural dynamics among network nodes. Specifically, one subsystem comprises key nodes of the frontotemporal semantic regions. This network shows moderate dislike to visuospatial tasks, shows proclivity for task-contexts with restraints on thoughts and responses, and prefers thoughts that are focused on other people. By contrast, the other subsystem comprises the cortical midline structure and angular gyri. This network shows strong aversion to visuospatial tasks, favours task-contexts allowing free self-generated thoughts without constraints, and prefers thoughts that are focused on self. Furthermore, causative connectivity reveals that task-contexts systematically alter the dynamics within and between subsystems, suggesting flexible adaption to situational demands. This self/inward vs. others/outward separation within the broad DN resembles recent discoveries regarding a dyadic structure within the frontoparietal network that comprises regions controlling memories/thoughts vs. regions controlling sensory-motoric processes, and echoes burgeoning views that the brain is organised with a spectrum-like architecture along gradational changes of inward vs. outward preferences. SignificanceRather than construing the default network (DN) as task-negative regions that passively react to off-task mind-wandering, researchers have begun to acknowledge the active role of the DN in supporting internally-directed cognition. Here we found a striking dichotomy within the DN in terms of the subsystems task-driven functional and connectivity profiles, extending beyond previous inferences using meta-analysis and resting-state fMRI. This dichotomy reflects a local manifestation of a macro-scale gradient representation spanning across the broad cerebral cortex. This cortical gradient increases its representational complexity, from primitive sensory and motoric processing, through lexical-semantic codes for language tasks, to abstract self-generated thoughts in task-free contexts. These findings enable a framework where the separate yet related literatures of semantic cognition and default-mode processes converge.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chiou, R., Humphreys, G., Lambon Ralph, M.. 2019-12-05. Bipartite functional fractionation within the default network supports disparate forms of internally oriented cognition. https://doi.org/10.1101/864603

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗