bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.10.24.465655

Temporal changes in resting state networks induced by propofol anesthesia.

Choe, M.·Jin, S.-H.·Kim, J. S.·Chung, C. K.
View original source ↗Export metadata ↓

Abstract

The cerebral cortical changes associated with propofol-induced unconsciousness remain unknown. While the anesthetic agent affects the entire cerebral cortices, there might be spatiotemporal differences in cortical changes. In particular, we hypothesized that there might be spatiotemporal differences in cortical changes with propofol-anesthesia. To address this hypothesis, we investigated power spectrum changes in electrocorticography (ECoG) signals obtained during the induction phase from awake state to unconsciousness. We found that, 1) the power increased in the range of frequencies < 46 Hz (delta to low gamma), and decreased in the range (62-150) Hz (high gamma), in global channels during the induction phase. 2) The power in the frontoparietal network (FPN), specifically the superior parietal lobule and prefrontal cortex, started to change early, but took a long time to completely change. However, the power in the default mode network (DMN) started to change late, but took a short time to completely change. 3) The power change ({Delta}Power) in the DMN was more conspicuous than that of the dorsal attention network (DAN) in high gamma frequency. Considering that the FPN is involved in communication with the external world and that DMN is involved in communication with self, loss of consciousness induced by general anesthesia results from first, disrupted communication between self and external world, and is then followed by disrupted communication within self, with decreased activity of the FPN, and later, attenuated activity of the DMN. Significance StatementWe investigated the spatiotemporal changes of power spectrum in human electrocorticography (ECoG) during the induction phase from awake state to unconsciousness. We found that from delta to low gamma frequency, the power increased, while in high gamma frequency, the power decreased over all channels. The power in the frontoparietal network (FPN) preferentially changed, then the power in the DMN changed later. The power in DMN decreased more than those in other RSNs in high gamma frequency. Loss of consciousness induced by general anesthesia results from first, disrupted communication between self and external world, followed by disrupted communication within self, with decreased activity of the FPN, and later, attenuated activity of the DMN.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Choe, M., Jin, S.-H., Kim, J. S., Chung, C. K.. 2021-10-26. Temporal changes in resting state networks induced by propofol anesthesia.. https://doi.org/10.1101/2021.10.24.465655

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↗