Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.03.08.483524

Social closeness modulates brain dynamics during distrust anticipation

Abstract

Anticipation of trust from a partner with high social closeness generates the preconditions for cooperative and reciprocal interactions to occur. However, if there is uncertainty in the interaction because the partner is a stranger or because the person has mistrusted us on another occasion, an aversive experience is generated. Hence, low social closeness or mistrust makes people keep track of the others behavior. In case of experiencing deviations from social norms, the person will monitor the intentions of the partner and update their priors regarding their social preferences. The anterior insula (AIns) seems to be sensitive to these social norm violations in functional magnetic resonance imaging (fMRI) experiments, however, the monitoring of partners with different levels of social closeness has not been investigated. In our study we wanted to find the brain regions related to (dis)trust anticipation from partners who differ in their level of social closeness. For this, we designed an experiment in which participants played an economic decision game with three people (trustors): A computer, a stranger, and a real friend. We covertly manipulated their decisions in the game so that they unexpectedly distrusted our participants. Using task-fMRI, our whole-brain analysis found that the AIns was active during the anticipation of the decisions from human partners (humans vs computer), but not during anticipation between high and low social closeness (friend vs stranger). However, using a psychophysiological interaction analysis, we found increases in functional coupling between the AIns and regions in the "mentalizing" network (such as temporal regions and parieto-occipital cortices) during trust anticipation between a high versus low social closeness partner. These results suggest that there may be a modulation of the AIns activity, specifically for high social closeness trustors, by regions that encode the intentions underlying the truster behavior.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jimenez, S., Mercadillo-Caballero, R., Angeles-Valdes, D., Sanchez-Sosa, J. J., Munoz-Delgado, J., Garza-Villarreal, E. A.. 2022-03-09. Social closeness modulates brain dynamics during distrust anticipation. https://doi.org/10.1101/2022.03.08.483524

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↗