Enhanced neural tracking of the fundamental frequency of the voice

Van Canneyt, J.; Wouters, J.; Francart, T.

doi:10.1101/2020.10.28.359034

Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.10.28.359034

Enhanced neural tracking of the fundamental frequency of the voice

Van Canneyt, J.·Wouters, J.·Francart, T.

View original source ↗Export metadata ↓

Abstract

Objective F0 tracking is a novel method that investigates the neural processing of the fundamental frequency of the voice (f0) in continuous speech. Through linear modelling, a feature that reflects the stimulus f0 is predicted from the EEG data. Then, the neural response strength is evaluated through the correlation between the predicted and actual f0 feature. The aim of this study was to improve upon this f0 tracking method by optimizing the f0 feature. ApproachSpecifically, we aimed to design a feature that approximates the expected EEG responses to the f0. We hypothesized that this would improve neural tracking results, because the more similar the feature and the neural response are, the easier it will be to reconstruct the one from the other. Two techniques were explored: a phenomenological model to simulate neural processing in the auditory periphery and a low-pass filter to approximate the effect of more central processing on the f0 response. Since these optimizations target different aspects of the auditory system, they were also applied in a cumulative fashion. ResultsResults obtained from EEG evoked by a Flemish story in 34 subjects indicated that both the use of the auditory model and the addition of the low-pass filter significantly improved the correlations between the actual and reconstructed feature. The combination of both strategies almost doubled the mean correlation over subjects, from 0.78 to 0.13. Moreover, canonical correlation analysis with the modelled feature revealed two distinct processes contributing to the f0 response: one driven by the compound activity of auditory nerve fibers with center frequency up to 8 kHz and one driven predominantly by the auditory nerve fibers with center frequency below 1 kHz. SignificanceThe optimized f0 features developed in this study enhance the analysis of f0-tracking responses and facilitate future research and applications.

Source connections

Published article ↗

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Van Canneyt, J., Wouters, J., Francart, T.. 2020-10-28. Enhanced neural tracking of the fundamental frequency of the voice. https://doi.org/10.1101/2020.10.28.359034

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↗