bioRxiv ScienceSearch

bioRxiv · 10.1101/790972

Brain, music and emotion: An EEG proof-of-concept study on musically continuous, non-personalized emotional responses

Abstract

It has been repeatedly reported that motivation for listening to music is majorly driven by the latters emotional effect. There is a relative opposition to this approach, however, suggesting that music does not elicit true emotions. Counteracting this notion, contemporary research studies indicate that listeners do respond affectively to music providing a scientific basis in differentially approaching and registering affective responses to music as of their behavioral or biological states. Nevertheless, no studies exist that combine the behavioral and neuroscientific research domains, offering a cross-referenced neuropsychological outcome, based on a non-personalized approach specifically using a continuous response methodology with ecologically valid musical stimuli for both research domains. Our study, trying to fill this void for the first time, discusses a relevant proof-of-concept protocol, and presents the technical outline on how to multimodally measure elicited responses on evoked emotional responses when listening to music. Specifically, we showcase how we measure the structural music elements as they vary from the beginning to the end within two different compositions, suggesting how and why to analyze and compare standardized, non-personalized behavioral to electroencephalographic data. Reporting our preliminary findings based on this protocol, we focus on the electroencephalographic data collected from n=13 participants in two separate studies (i.e., different equipment and sample background), cross-referencing and cross-validating the biological side of the protocols structure. Our findings suggest (a) that all participants - irrespectively of the study - reacted consistently in terms of hemispheric lateralization for each stimulus (i.e., uniform intra-subjective emotional reaction; non-statistically significant differentiation in individual variability) and (b) that diverse patterns of biological representations emerge for each stimulus between the subjects in the two studies (variable inter-subjective emotional reaction; statistically significant differentiation in group variability) pointing towards exogenous to the measurements process factors. We conclude discussing further steps and implications of our protocol approach.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Papatzikis, E., Herbst, A.. 2019-10-02. Brain, music and emotion: An EEG proof-of-concept study on musically continuous, non-personalized emotional responses. https://doi.org/10.1101/790972

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