bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2023.05.03.539222

Evoked Responses to Localized Sounds Suggest Linear Representation of Elevation in Human Auditory Cortex

Bialas, O.·Maess, B.·Schoenwiesner, M.
View original source ↗Export metadata ↓

Abstract

The auditory system computes the position of a sound along each of the three spatial axes, azimuth, elevation and distance, from very different acoustical cues. The extraction of sound azimuth from binaural cues (differences in arrival time and intensity between the ears) is well understood, as is the representation of these binaural cues in the auditory cortex of different species. Sound elevation is computed from monaural spectral cues arising from direction-dependent filtering of the pinnae, head, and upper body. The cortical representation of these cues in humans is still debated. We have shown that the fMRI blood-oxigen level-dependent activity in small parts of auditory cortex relates monotonically to perceived sound elevation and tracks listeners internal adaptation to new spectral cues. Here we confirm the previously suggested cortical code with a different method that reflects neural activity rather than blood oxigenation (electroencephalography), show that elevation is represented relatively late in the cortex, with related activity peaking at about 400 ms after sound onset, and show that differences in sound elevation can be decoded from the electroencephalogram of listeners, particularely from those who can distinguish elevations well. We used an adaptation design to isolate elevation-specific brain responses from those to other features of the stimuli. These responses gradually increased with decreasing sound elevation, consistent with our previous fMRI findings and population rate code for sound elevation. The long latency as well as the topographical distribution of the elevation-specific brain response indicates the involvement of higher-level cognitive processes not present for binaural cue representation. The differences between brain responses to sounds at different elevations predicted the listeners sound localization accuracy, suggesting that these responses reflect perceived elevation. This is, to our knowledge, the first study that demonstrates the cortical encoding of sound elevation in humans with high-temporal resolution. Our results agree with previous findings from functional magnetic resonance imaging, providing strong support for the hypothesis that elevation is represented in a population-rate code. This represents a critical advance in our understanding of spatial auditory processing along a dimension that is still poorly understood.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bialas, O., Maess, B., Schoenwiesner, M.. 2023-05-03. Evoked Responses to Localized Sounds Suggest Linear Representation of Elevation in Human Auditory Cortex. https://doi.org/10.1101/2023.05.03.539222

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↗