Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/740779

Prolonged tonic pain in healthy humans disrupts intrinsic brain networks implicated in pain modulation

Meeker, T. J.·Schmid, A.-C.·Keaser, M. L.·Khan, S.·Gullapalli, R. P.·Dorsey, S. G.·Greenspan, J. D.·Seminowicz, D.
View original source ↗Export metadata ↓

Abstract

Neural mechanisms of ongoing nociceptive processing in the human brain remain largely obscured by the dual challenge of accessing neural dynamics and safely applying sustained painful stimuli. Recently, pain-related neural processing has been measured using fMRI resting state functional connectivity (FC) in chronic pain patients. However, ongoing pain-related processing in normally pain-free humans remains incompletely understood. Therefore, differences between chronic pain patients and controls may be due to comorbidities with chronic pain. Decreased FC among regions of the descending pain modulation network (DPMN) are associated with presence and severity of chronic pain disorders. We aimed to determine if the presence of prolonged tonic pain would lead to disruption of the DPMN. High (10%) concentration topical capsaicin was combined with a warm thermode applied to the leg to create a flexible, prolonged tonic pain model to study the FC of brain networks in otherwise healthy, pain-free subjects in two separate cohorts (n=18; n=32). We contrasted seed-based FC during prolonged tonic pain with a pain-free passive task. In seed-based FC analysis prolonged tonic pain led to enhanced FC between the anterior middle cingulate cortex (aMCC) and the somatosensory leg representation. Additionally, FC was enhanced between the pregenual anterior cingulate cortex (pACC), right mediodorsal thalamus and the posterior parietal cortex bilaterally. Further, in the seed-driven PAG network, positive FC with the left DLPFC became negative FC during prolonged tonic pain. These data suggest that some altered DPMN FC findings in chronic pain could partially be explained by the presence of ongoing pain.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Meeker, T. J., Schmid, A.-C., Keaser, M. L., Khan, S., Gullapalli, R. P., Dorsey, S. G., Greenspan, J. D., Seminowicz, D.. 2019-08-21. Prolonged tonic pain in healthy humans disrupts intrinsic brain networks implicated in pain modulation. https://doi.org/10.1101/740779

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↗