Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.03.25.714036

Decoding of arousal and valence from fMRI data obtained during emotion inductions

Abstract

Arousal and valence are fundamental dimensions of affective experience signifying levels of activation and pleasantness, respectively. These dimensions play a crucial role in shaping emotional responses and behaviors, with significant implications for psychopathology. Previous machine learning studies had some success decoding these states from brain activation patterns observed during task-based functional magnetic resonance imaging (fMRI), but the results have varied across studies. Moreover, prior studies have often been limited by small sample sizes, weak decoding performance, and non-whole-brain analyses, leaving the neural representations of arousal and valence largely unresolved. Here we successfully decoded arousal and valence from whole-brain task-fMRI data collected from 132 participants during exposure to 300 unique emotional stimuli, including 150 movie clips and 150 text scenarios that reliably induced a wide range of arousal and valence states. Mass univariate general linear models identified block-level activation (emotion stimuli > washout) from all gray matter voxels. Multivariate regression analysis predicted arousal and valence ratings based on these gray matter activations. Patterns in the fMRI data underlying arousal and valence were robust, as they were successfully decoded across both induction modalities using five different linear multivariate regression models. Although significant, decoding from scenarios was less successful than from movies, likely due to their more imaginative nature. In particular, decoding arousal from scenarios only showed low predictive utility. Representations of arousal and valence were widespread throughout the brain, and we reveal cerebellar and brainstem contributions that have largely been absent in past fMRI decoding studies. These findings clarify the distributed neural basis of arousal and valence and provide a foundation for future clinical research on the role of these constructs in affective dysregulation.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

White, J. S., Ding, Y., Muncy, N. M., Graner, J. L., Faul, L., LaBar, K. S.. 2026-03-28. Decoding of arousal and valence from fMRI data obtained during emotion inductions. https://doi.org/10.64898/2026.03.25.714036

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A Mechanistic Account of Dedifferentiation in the Aging Visual System

To uncover the mechanisms of age-related dedifferentiation, we simulated neural degradation in a computational model of the ventral visual stream. Severing connections or adding noise, whether in inferotemporal cortex (IT) or upstream, reduced IT differentiation, indicating that dedifferentiation need not originate locally. Degrading peripheral V1, which preferentially drove place-selective IT neurons, selectively reduced place differentiation, a candidate mechanism for the stronger place dedifferentiation reported in aging.

neuroscience↗

Reusing pipettes in Patch-seq: a foundation for automated multimodal profiling

Patch-seq is a technique for single-cell multimodal characterization. It combines whole-cell electrophysiology, single-cell transcriptomics, and morphological reconstruction in single neurons. Patch-seq morphologies are a critical bridge among cell types, genes, physiology, and large-scale connectivity platforms such as EM connectomes and single-cell-resolution projectomes. However, patch-seq experimental complexity and operator dependence limit throughput. Automation could enable scalable Patch-seq but requires procedural adaptations, including detergent-based pipette cleaning, robotic nucleus extraction and collection. The impact of these automations on Patch-seq quality has not been systematically evaluated. Here, we show that each of these modifications preserves or improves key Patch-seq outcomes. Automated nucleus extraction performs comparably to, or better than, expert manual operation, preserving key RNA and morphological metrics. Detergent-cleaned, reused pipettes supported a viable sealing success rate across multiple cleaning cycles and preserved electrophysiological quality and transcriptomic yield without introducing excess contamination. Sonication effectively allows collection of nuclear material without damaging RNA and supports subsequent pipette cleaning and reuse. Enhanced automated sealing and break-in procedures increased throughput regardless of brain region, cell type or species. Together, these results validate the core procedural adaptations required for automated Patch-seq and establish a foundation for high-throughput, standardized multimodal single-cell characterization.

neuroscience↗

Development of direction selectivity in the Xenopus tadpole optic tectum and midbrain tegmentum

Detecting motion direction is a fundamental function performed by direction selective (DS) neurons. DS neurons in the optic tectum (superior colliculus in mammals) enable the tracking of moving objects. DS neurons of the accessory optic system support reflexive eye / head movements that stabilize gaze during self-motion. By developmental stage 48 (10 days postfertilization), Xenopus tadpoles display visually guided behaviors that require both types of DS neurons. Our previous work has shown that these two regions are not only functionally distinct but also follow different developmental programs. Here we characterized and compared how direction selectivity develops in both visual processing centers. Using in vivo electrophysiological recordings during moving bar visual stimulation, we measured DS synaptic inputs and spiking outputs in both regions across three key developmental stages of the retinotectal projection. Tegmental neurons were direction selective ab initio, and both input and output tuning remained stable across development. Tectal neurons were observed to receive DS inputs early, and their input selectivity also remained stable across development. However, their spiking output grew substantially more DS at the later developmental stage. This was due at least in part to a naturally occurring decrease in intrinsic excitability which preferentially dampened overall spike rates, but especially in response to the non-preferred direction of motion, thereby increasing direction selectivity. These results reveal distinct developmental trajectories in parallel visual pathways. Tegmental direction selectivity is established early and stays stable, whereas tectal output tuning sharpens during development through a decrease in intrinsic excitability.

neuroscience↗