Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.08.11.607503

Efficient modular system identification provides a high-resolution assay of temporal processing and reveals the multilevel effects of attention along the human auditory pathway

Abstract

Human studies of auditory temporal processing and the effects therein of aging, hearing loss, musicianship, and other auditory processing disorders have conventionally employed brainstem evoked potentials (e.g., FFRs/EFRs targeting specific modulation frequencies). Studies of temporal processing in forebrain structures are fewer and are often restricted to the 40 Hz steady-state response. One factor contributing to the limited investigation is the lack of a fast and reliable method to characterize temporal processing non-invasively in humans over a wide range of modulation frequencies. Here, we use a system-identification approach where white noise, modulated using an extended maximum-length sequence (em-seq), is employed to target stimulus energy toward a modulation-frequency range of interest and efficiently obtain a robust auditory modulation-temporal response function or mod-TRF. The mod-TRF can capture activity from sources in the early processing pathway (5-7 ms latency), middle-latency region (MLR), and late latency region (LLR). The mod-TRF is a high-resolution, modular assay of the temporal modulation transfer function (tMTF) in that the distinct neural components contributing to the tMTF can be separated on the basis of their latency, modulation frequency band, and scalp topography. This decomposition provides the insight that the seemingly random individual variation in the shape of the tMTF can be understood as arising from individual differences in the weighting and latency of similar underlying neural sources in the composite scalp response. We measured the mod-TRF under different states of attention and found a reduction in latency or enhancement of amplitude of the response from specific sources. Surprisingly, we found that attention effects can extend to the earliest parts of the processing pathway (5ms) in highly demanding tasks. Taken together, the mod-TRF is a promising tool for dissecting auditory temporal processing and obtain further insight into a variety of phenomenon such as aging, hearing loss, and neural pathology.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Singh, R., Bharadwaj, H.. 2024-08-12. Efficient modular system identification provides a high-resolution assay of temporal processing and reveals the multilevel effects of attention along the human auditory pathway. https://doi.org/10.1101/2024.08.11.607503

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↗