bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.02.05.578828

Neural signatures of opioid-induced risk-taking behavior in the prelimbic prefrontal cortex

Abstract

Opioid use disorder occurs alongside impaired risk-related decision-making, but the underlying neural correlates are unclear. We developed an approach-avoidance conflict task using a modified conditioned place preference procedure to study neural signals of risky opioid seeking in the prefrontal cortex, a region implicated in executive decision-making. Following morphine conditioned place preference, rats underwent a conflict test in which fear-inducing cat odor was introduced in the previously drug-paired side of the apparatus. While the saline-exposed control group avoided cat odor, the morphine group included two subsets of rats that either maintained a preference for the paired side despite the presence of cat odor (Risk-Takers) or exhibited increased avoidance (Risk-Avoiders), as revealed by K-means clustering. Single-unit recordings from the prelimbic cortex (PL) demonstrated decreased neuronal activity upon acute morphine exposure in both Risk-Takers and Risk-Avoiders, but this firing rate suppression was absent after repeated morphine administration. Risk-Avoiders also displayed distinct post-morphine excitation in PL which persisted across conditioning. During the preference test, subpopulations of PL neurons in all groups were either excited or inhibited when rats entered the paired side. Interestingly, the inhibition in PL activity was lost during the subsequent conflict test in both saline and Risk-Avoider groups, but persisted in Risk-Takers. Additionally, Risk-Takers showed an increase in the proportion of PL neurons displaying location-specific firing in the drug-paired side from the preference to the conflict test. Together, our results suggest that persistent PL inhibitory signaling in the drug-associated context during motivational conflict may underlie increased risk-taking behavior following opioid exposure. SIGNIFICANCE STATEMENTRisky opioid use is well established in opioid use disorder, but the underlying neural correlates are poorly understood. In this study, we present findings from a novel behavioral task in which rats face a motivational conflict between contextual opioid reward memory and a naturalistic predator threat. Performing neuronal recordings in the prelimbic prefrontal cortex (PL), a brain region critical for executive decision-making, we demonstrate enhanced representation of drug-associated context and persistent inhibitory signaling by PL neurons that occur alongside opioid-induced risk-taking behavior. Our findings refine a preclinical model for studying addiction, establish PL as a prime region for investigating drug-environment interactions, and positions the prefrontal cortex as a candidate region for translational studies targeting risky opioid use.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Quave, C. B., Vasquez, A. M., Aquino-Miranda, G., Bora, E. P., Chidomere, C. L., Zhang, X. O., Engelke, D. S., Do-Monte, F. H.. 2024-02-06. Neural signatures of opioid-induced risk-taking behavior in the prelimbic prefrontal cortex. https://doi.org/10.1101/2024.02.05.578828

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↗