bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.05.25.493371

The central autonomic system revisited - convergent evidence for a regulatory role of the insular and midcingulate cortex from neuroimaging meta-analyses

Abstract

The autonomic nervous system regulates dynamic body adaptations to internal and external environment changes. Capitalizing on two different algorithms (Analysis of Brain Coordinates and GingerALE) that differ in empirical assumptions, we scrutinized the meta-analytic convergence of human neuroimaging studies investigating the neural basis of peripheral autonomic signal processing. Among the selected studies, we identified 42 records reporting 44 different experiments and testing 792 healthy individuals. The results of the two different algorithms converge in identifying the bilateral dorsal anterior insula and midcingulate cortex as the critical areas of the central autonomic system (CAN). However, whereas the bilateral dorsal anterior insula appears to be involved in processing autonomic nervous system signals regardless of task type, activity in the midcingulate cortex appears to be primarily engaged in processing autonomic signals during cognitive tasks and task-free conditions. Applying an unbiased approach, we were able to identify a single functionally condition-independent circuit that supports CAN activity. Although partially overlapping with the salience network, this functional circuit includes, in addition to the bilateral insular cortex and midcingulate cortex, the bilateral inferior parietal lobules and small clusters in the bilateral middle frontal gyrus. Our results do not support the hypothesis of divergent pathways for the sympathetic and parasympathetic systems or a robust involvement of the default mode network, particularly during parasympathetic activity. However, these results may be due to the relatively low number of studies investigating the parasympathetic system (12%), making our results more consistent with the central processing network of sympathetic activity. Remarkably, the critical regions of the CAN observed in this meta-analysis are among the most reported co-activated areas in neuroimaging studies and have been repeatedly shown as being dysregulated across different mental and neurological disorders. This suggests that the central dynamic interaction maintaining bodily homeostasis reported in several brain imaging studies may be associated with increased autonomic nervous system engagement and that disruptions in this interplay may underpin unspecific pathological symptoms across mental and neurological disorders.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ferraro, S., Klugah-Brown, B., Tench, C., Chepngetich Bore, M., Nigri, A., Bruzzone, M. G., Demichelis, G., Palermo, S., Kendrick, K. M., Jiang, X., Yao, S., Zhao, W., Becker, B.. 2022-05-26. The central autonomic system revisited - convergent evidence for a regulatory role of the insular and midcingulate cortex from neuroimaging meta-analyses. https://doi.org/10.1101/2022.05.25.493371

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

KEEP EXPLORING

Related preprints

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↗

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↗

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↗