bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.01.29.478308

Categorization and discrimination of human and non-human primate affective vocalizations: investigation of the frontal cortex activity through fNIRS.

Debracque, C.·Ceravolo, L.·Clay, Z.·Grandjean, D.·Gruber, T.
View original source ↗Export metadata ↓

Abstract

Many species, including humans and non-human primates, react differently to threatening or pleasant situations. Because of its adaptiveness, recognizing affective signals is likely to be reflected in a capability of modern humans to recognize other closely related species call content. However, at both behavioural and neural levels, only few studies have used a comparative approach to understand affective decoding processes in humans, particularly with respect to affective vocalizations. Previous research in neuroscience about the recognition of human affective vocalizations has shown the critical involvement of temporal and frontal regions. In particular, frontal regions have been reported as crucial in the explicit decoding of vocal emotions especially in different task complexity such as discrimination or categorization. The aim of this study using functional Near Infrared Spectroscopy (fNIRS) was to specifically investigate the neural activity of the inferior frontal cortex pars triangularis (IFGtri) and the prefrontal cortex (PFC) underlying categorization (A versus B) and discrimination (A versus non-A) mechanisms of positive and negative affects in human, great apes (chimpanzee and bonobo), and monkey (rhesus macaque) vocalizations. We also analysed participants behavioural responses and correlated them with the recorded frontal activations. While performing the tasks, fNIRS data revealed a clear distinction between the two frontal regions, with a general positive activation of IFGtri compared to a decrease of PFC activity. We also found a modulation of IFGtri and PFC activations depending on both the species considered and on task complexity; with generally more activity in the IFGtri during discrimination compared to categorization, and a more intense decrease of the PFC in categorization compared to discrimination. Behaviourally, participants recognized almost all affective cues in all species vocalizations at above chance levels in the discrimination task (except for threatening bonobo calls). For categorization, they mostly correctly identified at levels significantly above chance affective contents in human and great ape vocalizations but not in macaque calls. Overall, these findings support the hypothesis of a pre-human origin of affective recognition processing inherited from our common ancestor with other great apes and processed in the frontal cortex. Our results also highlight behavioural differences related to task complexity, i.e. between categorization and discrimination processes, and the differential involvement of the PFC and the IFGtri, which seems necessary to explicitly decode affects in all primate vocalizations.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Debracque, C., Ceravolo, L., Clay, Z., Grandjean, D., Gruber, T.. 2022-01-29. Categorization and discrimination of human and non-human primate affective vocalizations: investigation of the frontal cortex activity through fNIRS.. https://doi.org/10.1101/2022.01.29.478308

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↗