Biology subjects

Shen, Y.

Publications and source records attributed to Shen, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

A post-mitotic bistable switch actively safeguards mature neurons against reciprocal transdifferentiation in vivo

How mature cells actively defend their identity against alternative fates is poorly understood. Here we show that two types of fully differentiated Drosophila somatosensory neurons, derived from distinct lineages, are continuously prevented from transdifferentiating into one another by a post-mitotic bistable switch. Two homeodomain transcription factors, Hmx and Cut, are co-expressed in both neuronal types but adopt opposite stoichiometric dominances through mutual repression, each defining one identity. Disrupting this balance in mature neurons triggers deterministic, lineage-crossing reprogramming of transcriptome, dendritic and axonal architecture, and sensory behavior without reversion to a progenitor state. This regulatory logic is evolutionarily conserved: Drosophila sensory identities share transcriptomic signatures with distinct human A{delta} mechanoreceptors, and human CUX and HMX proteins functionally replace their fly counterparts. Mature neuronal identity is thus not a fixed endpoint but a poised equilibrium actively maintained by ongoing competition between opposing selectors. TEASERMature somatosensory identity is a poised equilibrium actively maintained by continuous competition between opposing terminal selectors.

Developmental Biology↗

bioRxiv2026

Aberrant neuron-OPC synaptic transmission and deficient myelination define sex bias in major depressive disorder

Sex bias is a notable feature of major depressive disorder (MDD), yet its cellular and molecular origins remain unclear. We integrated computational analyses of human patient data with histological and biochemical validation in animal models to uncover female-specific MDD pathways. We identified female-specific mechanisms involving oligodendroglial lineage cells, especially oligodendrocyte precursor cells (OPCs), as key signal receivers with unidirectional preference in interactome networks. The neurexin (NRXN) pathway emerged as the most perturbed in MDD, with greater disruption in females. Subclustering further identified committed OPCs (cOPCs) as a disease-associated oligodendroglial subpopulation characterized by high expression of synaptic genes; cOPCs were also enriched of MDD-related transcriptional signatures revealed by trajectory analysis. High-dimensional weighted gene co-expression network analysis identified GABRG3 as an MDD-specific hub gene in cOPCs. The GABRG3 was also involved in the NRXN synaptic assembly cascade. Using Gabrg3 conditional knockout mice, we validated findings in patients and demonstrated that conditional deletion of Gabrg3 in cOPCs recapitulates MDD-like phenotypes, highlighting impaired neuron-cOPC synaptic communication, abnormal myelination, and depression-like behaviors. Together, our work defines a sex-specific cellular and molecular pathobiology of MDD, bridges clinical discovery with preclinical context, and provides a translatable framework for precision medicine targeting fundamental sex differences.

neuroscience↗

bioRxiv2026

Structural basis of substrate recognition and allosteric inhibition in human B0AT2

The SLC6 family is a major target for neuropsychiatric therapeutics. Human B0AT2 (SLC6A15) regulates amino acid homeostasis and glutamatergic transmission and is linked to major depressive disorder, yet its transport and inhibition mechanisms remain unclear. Here we report cryo-EM structures of B0AT2 in apo state and in complex with substrates (proline, leucine, methionine) and inhibitors (loratadine, tiagabine), capturing outward-open, early substrate-bound intermediate, outward-occluded, and inward-open conformations along the transport cycle. These structures reveal an early substrate-sensing mechanism at the substrate-binding pocket (S1), where a substrate-dependent rotameric switch of Phe308 remodels pocket geometry to tune substrate accommodation and selectivity. Loratadine stabilizes an outward-occluded state via allosteric inhibition at the extracellular S2 pocket, whereas tiagabine stabilizes the inward-open state through cooperative multi-site inhibition involving S1 and two previously unrecognized intracellular cavities (S3 and S4). Together with functional assays, these data define the molecular basis of B0AT2 substrate selectivity and state-dependent inhibition. Notably, the two intracellular cavities are conserved across SLC6 transporters, reflecting a shared intracellular vestibular architecture and enabling rational design of conformation-selective modulators for neuropsychiatric disorders.

biophysics↗

bioRxiv2026

Transcription factor CCTF1 plays a decisive role in regulating the proteasome activity during archaeal cell division

Archaea of the order Sulfolobales exhibit a highly ordered cell cycle progression similar to that of eukaryotes. It has been demonstrated that degradation of the cell division protein CdvB by the proteasome controls the progression of cell division. However, how the proteasome itself is regulated during the cell cycle is not fully understood. Recently, the cyclically expressed ArsR family transcription factor CCTF1 (cell cycle transcription factor 1) was shown to represses expression of PAN (proteasome-activating nucleotidase) in Sulfolobus acidocaldarius. Here, using biochemical approaches, comparative transcriptomics and proteomics, we provide further insights into the CCTF1 function and show that it regulates PAN expression in Saccharolobus islandicus by binding to an AT-rich palindromic sequence within the pan promoter. We also reassessed the role of the cyclically expressed protein kinase aCcrK in regulation of proteasome activity and conclude that CCTF1, rather than aCcrK, is the primary factor controlling the proteasome activity. These findings advance our understanding of the proteosome-mediated cell cycle regulation in archaea.

microbiology↗

bioRxiv2026

Mitochondrial carrier SLC25A34 links clock, diet, and temperature control of interorganellar lipid cycling

Adipocyte lipid metabolism is coordinated by circadian rhythms, diet, and environmental temperature. Yet how these diverse signals are molecularly integrated remains unknown. Here we show that clock, diet, and temperature cues converge on the orphan mitochondrial transporter, SLC25A34, to orchestrate thermogenic cycling of lipid synthesis and oxidation. During sleep, the clock suppresses Slc25a34 transcription through REV-ERB. Waking, lipid-rich diets, or cold exposure abolish this repression, allowing lipolytic signals to stimulate Slc25a34 expression via PPAR. SLC25A34 then imports oxaloacetate into mitochondria to accelerate the export of substrates used for acetyl-CoA production in the cytosol. This feeds into cytosolic lipid synthesis and transcriptional induction of mitochondrial biogenesis, which collectively promote mitochondrial lipid oxidation. Thus, SLC25A34 confers circadian, dietary, and environmental control of thermogenic metabolism through interorganellar lipid cycling.

molecular biology↗

bioRxiv2026

Aberrant cortical subcortical somatosensory network organization is associated with impaired tactile-motion perception in akinetic-rigid Parkinson's disease

BackgroundParkinsons disease (PD) is associated with somatosensory dysfunction, yet higher-order tactile-motion processing and its neural basis remain poorly understood. Here, we combined psychophysical assessment of tactile-motion perception with resting-state functional MRI (rs-fMRI) to investigate how altered sensorimotor network organization relates to tactile perceptual deficits in akinetic-rigid dominant PD (PDAR). MethodsForty-six participants (25 PDAR and 21 healthy controls, HCs) underwent clinical evaluation and resting-state functional MRI scanning. A subset of participants (15 PDAR and 15 HCs) additionally completed a tactile-motion perception task assessing directional bias and speed sensitivity. ROI-to-ROI functional connectivity analyses were performed within a customized 26-node sensorimotor and cortico-basal ganglia-thalamo-cortical (CBGTC) network. ResultsCompared with HCs, PDAR patients exhibited significantly altered tactile-motion perception, including greater directional bias (p = 0.047) and reduced sensitivity to dynamic tactile speed (p < 0.001), reflecting diminished sensitivity to mid-to-high speeds. Resting-state functional connectivity analyses revealed widespread reductions in connectivity within cortical somatosensory regions (Areas 1, 2, 3a, 3b, 5), particularly between primary somatosensory and motor cortices. In contrast, increased connectivity was observed between basal ganglia-thalamic structures and cortical sensorimotor regions, including thalamus-M1 and GPi-sensorimotor connections (all p-FDR < 0.05). ConclusionsThese findings demonstrate a dual pattern of sensorimotor network reorganization in PDAR, characterized by disrupted cortical somatosensory integration alongside enhanced subcortical-cortical coupling. The present study provides evidence that higher-order tactile-motion dysfunction in PD is associated with large-scale abnormalities in distributed sensorimotor networks and highlights the somatosensory system as a potential target for future therapeutic intervention.

neuroscience↗

bioRxiv2026

A Unified Form of Batch Harmonization Equation for Normative Modeling: A Location Scale Framework

Normative modeling quantifies individual deviation from population norms by estimating the conditional mean and variance of brain-derived measures as functions of clinically relevant parameters such as age. The rapid growth of multi-center consortia has created an urgent need for normative models that incorporate batch harmonization. Several harmonization methods based on linear mixed models--ComBat, GAMLSS, HBR, and Generalized Normative Modeling (GNM)--offer explicit formulations of the mean and variance, making them natural candidates for batch-harmonized normative modeling; yet the absence of a unified theoretical framework leaves it unclear whether and how these methods support the computation of batch-harmonized z-scores. We bridge this gap by writing existing harmonization methods as special cases of a single location-scale equation, y = m(x, {Theta})+{sigma}(x, {Theta}){varepsilon} , which we term the unified form of batch harmonization equation for normative modeling. The methods differ only in the functional forms of m and{sigma} , how batch parameters enter{Theta} , and how{Theta} is estimated. This unified form yields both harmonized data y* and site-invariant z-scores from the same model, providing a common theoretical language for harmonized normative modeling. Building on this framework, we evaluate the underlying regression engines (parametric, spline, Gaussian process, kernel, deep learning), sensitivity to outliers, computational scalability, and federated decomposability for privacy-preserving multi-center computation. By clarifying what each method assumes, what it delivers, and where the boundaries of current methodology lie, the unified equation establishes a principled foundation for method selection and charts a path toward reliable, scalable, and privacy-aware normative modeling across multi-center neuroimaging.

bioengineering↗

bioRxiv2026

The CNS-penetrant MAP4K inhibitor famlasertib restrains medulloblastoma dissemination without developmental toxicity

Cerebellum tissue invasion and dissemination are major drivers of recurrence and metastatic spread in medulloblastoma (MB), yet no invasion-inhibitory therapy is currently available. The serine/threonine kinase MAP4K4 is highly expressed in MB and promotes invasive behavior downstream of growth factor signaling, while its physiological postnatal downregulation suggests that disrupted developmental control may contribute to tumor pathogenesis. Here, we investigate pharmacological targeting of MAP4K4 using famlasertib, a CNS-penetrant, neuroprotective MAP4K inhibitor, as a strategy to suppress invasion in MB. Using 3D invasion assays and quantitative live-cell microscopy, we demonstrate that famlasertib markedly reduces invasive behavior and single-cell motility of MB cells. Organotypic cerebellum tissue and orthotopically implanted zebrafish larval models further confirm anti-invasive efficacy without detectable developmental toxicity at effective concentrations. Phospho-proteomics and functional analyses revealed that MAP4K inhibition alters kinase signaling linked to cytoskeletal remodeling, leading to suppressed F-actin dynamics, increased cell clustering, and enhanced cortical accumulation of tight junction protein 1 (TJP1). Collectively, our findings confirm MAP4Ks as therapeutically targetable regulators of MB invasion and establish famlasertib as a candidate migrastatic agent that restrains tumor cell dissemination while preserving developmental integrity.

cancer biology↗

bioRxiv2026

Divergent signaling profiles in mTOR gain-of-function Smith-Kingsmore syndrome (SKS) and TSC2 deficiency

Smith-Kingsmore syndrome (SKS) is a rare neurodevelopmental disorder caused by gain-of-function mutations in MTOR, yet whether these mutations phenocopy TSC2 loss or establish a distinct signaling state remains unclear. Using quantitative proteomics, phosphoproteomics, and transcriptomics in isogenic cell models of SKS (MTOR{Delta}4aa), TSC2 loss (TSC2-/-), and wild-type controls under glucose depletion and refeeding, we find that MTOR{Delta}4aa and TSC2-/- cells occupy fundamentally distinct regulatory states. TSC2-/- cells exhibit broad anabolic remodeling and a transcriptional program dominated by NF-{kappa}B- and STAT-driven inflammatory responses. MTOR{Delta}4aa cells instead display enrichment of nuclear and RNA processing programs, E2F/MYC-driven transcription, and a constrained proteomic dynamic range across nutrient states. Phosphoproteomic analysis of MTOR{Delta}4aa reveals rerouting of nutrient-responsive signaling toward MAPK/ERK- and Ca2+/CaMK-dependent pathways with limited canonical mTORC1/S6K1 engagement. These findings establish SKS as a signaling rewiring disorder distinct from classical mTORC1 hyperactivation, with implications for therapeutic targeting.

molecular biology↗

bioRxiv2026

Bacterial Membrane Vesicles in Wastewater Disseminate Antibiotic Resistance Genes

Bacterial membrane vesicles (BMVs) have emerged as important contributors to the dissemination of antibiotic resistance genes (ARGs) in the environment. Here, we developed a high-performance immunomagnetic isolation method that improves the purity and selectivity of BMV recovery from wastewater, minimizes contamination from eDNA and viruses, and enables differentiation of BMVs originating from Gram-positive versus Gram-negative bacteria with minimal cross-reactivity. Using this approach, we found that ARGs such as the kanamycin resistance gene (kanR) was highly abundant in BMVs from both raw and treated wastewater, exhibited persistence following treatment, and retained the ability to generate antibiotic-resistant bacteria via transformation. Metagenomic sequencing further revealed that tetracycline resistance genes were the most abundant ARG class across all wastewater samples, while the composition of BMV-associated ARGs differed from the bulk ARG profile. These findings highlight the critical yet underrecognized role of BMVs in the spread of antimicrobial resistance and underscore the need to address BMV-mediated pathways within a One Health framework linking environmental and human health.

microbiology↗

bioRxiv2026

Integrated Metagenomics and Metabolomics Studies Reveal Core Bacterial Guild Regulating Carbohydrate Metabolism in Pediatric MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent pediatric disorder with limited treatment options, primarily due to an incomplete understanding of its molecular drivers. Recent research underscores the role of microbial guilds in metabolic health, but the mechanisms by which dysbiosis driven by core species and co-abundant symbionts disrupt metabolic homeostasis in pediatric MASLD remain unclear. ResultsHere, we conducted integrated metagenomic and metabolomic analyses on 285 pediatric subjects including MASLD patients, obese and healthy controls. The gut dysbiosis in MASLD was characterized by a depletion of Phocaeicola vulgatus, Bacteroides uniformis, Parabacteroides distasonis, and Bacteroides thetaiotaomicron. Co-abundance network analysis, integrating our cohort with four public datasets, identified these species as core guild members associated with MASLD. Microbial enrichment analysis showed significant disruptions in carbohydrate metabolism, particularly the downregulation of the tricarboxylic acid (TCA) cycle, fructose and sucrose metabolism, and pentose and glucuronate interconversions. P. vulgatus and B. uniformis were identified as dominant species linked to the downregulation of KEGG orthologs (KOs) in these disrupted pathways that were inversely correlated with hepatic injury biomarkers. CAZyme database analysis further emphasized P. vulgatus as the primary contributor to glycoside hydrolases involved in monosaccharide utilization. Finally, both untargeted and targeted metabolomics analysis validated a disrupted metabolic network centered on the TCA cycle and monosaccharide metabolism in pediatric MASLD. ConclusionOur findings suggest the core guild species P. vulgatus and B. uniformis may serve as critical regulators of carbohydrate metabolism in pediatric MASLD, offering potential mechanistic targets for gut microbiome-based interventions.

microbiology↗

bioRxiv2026

GenNA: Conditional generation of nucleotide sequences guided by natural-language annotations

Deciphering the mapping between linear biomolecular sequences and complex biological functions remains a central challenge in genomics. Although existing generative nucleotide language models have made substantial progress in modeling sequence distributions, they generally lack explicit access to high-level biological semantics, limiting their ability to support semantics-guided conditional generation. To address this limitation, we present GenNA, a generative nucleotide foundation model guided by natural-language annotations. GenNA is pretrained on a multimodal nucleotide-text corpus spanning 2,221 eukaryotic species and comprising approximately 416 billion characters, and learns the relationships between sequence patterns and functional annotations within a unified autoregressive framework. Systematic evaluations show that, even without explicit supervision from biological rules, GenNA yields distinguishable perplexity scores in response to semantic mismatches between sequences and functional annotations, to different mutation types, and to perturbations of species labels. Moreover, across a range of natural-language-guided nucleotide generation tasks, the model produces sequences consistent with both target semantics and species context. Overall, GenNA provides a unified framework for natural-language-guided nucleotide modeling and conditional generation, and offers a feasible route toward integrating high-level functional descriptions with low-level sequence design.

bioinformatics↗

bioRxiv2026

Ratiometric Fluorescent Protein Biosensors Reveal Citrate Dynamics and Cellular Heterogeneity

Citrate is a central intermediate metabolite linking the tricarboxylic acid cycle and lipid biosynthesis. Tools for monitoring of spatiotemporal citrate dynamics are critical for getting a better understanding of cellular metabolism. Here, we develope genetically encoded excitation ratiometric biosensors for citrate, based on our previous intensiometric green fluorescence protein-based citrate biosensor, Citron1. We find that a single mutation in the Citron1 chromophore-forming tripeptide provided an excitation ratiometric response. Further rounds of directed evolution yield highly responsive variants, exhibiting citrate-dependent fluorescence changes between two excitation peaks. When expressed in mammalian cells, these biosensors enable citrate dynamics to be monitored in both the cytosol and mitochondria. Comparative analysis across multiple human breast cancer cell lines uncovers cell line-specific differences in citrate levels and their heterogeneity, which could be linked to their malignancy. Furthermore, flow cytometry-based measurements in mouse embryonic stem cells demonstrate the proteomics signatures underlying the population-level variability in citrate concentrations and citrate rewiring during stem cell differentiation. Together, these results show that these excitation ratiometric citrate biosensors enable quantitative, compartment-resolved, and population-scale analysis of cellular metabolism.

molecular biology↗

bioRxiv2026

Virtual multiplex staining of the pancreatic islets across type 1 diabetes progression using a Schroedinger bridge

Classical hematoxylin and eosin (H&E) staining enables review of tissue morphology but lacks information regarding the molecular state of cells. Immunohistochemical (IHC) techniques label specific proteins in tissue, allowing differentiation of relevant structures that may go undetectable in H&E. However, the IHC process is complex, expensive, and time-consuming, especially for multiplex IHC (mIHC) limiting its use in large cohorts. Stain conversion of H&E to IHC using generative artificial intelligence models such as generative adversarial networks (GANs) represent one solution to this problem. However, GANs are unstable during out of distribution sampling and are prone to hallucinations or mode collapse, limiting their accuracy in challenging image conversion tasks. To address this, the field has recently turned to diffusion models. Here, we introduce Schrodinger-bridge for Multiplex ImmunoLabel Estimation (SMILE). Unlike conventional diffusion models that map from source to target through an intermediate Gaussian noise, Schrodinger-bridge diffusion models skip this step and have been shown to better preserve structures during image translation. To test the performance of SMILE, we generated a large cohort of high-fidelity H&E-mIHC image pairs from pancreatic organ donors, targeting insulin, glucagon, and CD3. Our dataset well-sampled across type-1 diabetes status, pancreas anatomical location, age, and sex. Using this cohort, we demonstrate the superiority of SMILE compared to GANs via a comprehensive evaluation framework incorporating texture, distribution, and antibody-specific metrics, as well as blinded pathologist reviews. We further confirmed the ability of SMILE to generate accurate mIHC images from H&Es generated at an external site, to perform whole slide image conversion, and to generate realistic three-dimensional maps of the pancreatic islets in non-diabetic, auto-antibody positive, and type-1 diabetic donor tissue. Finally, we performed stain conversion of paired H&E to HER2 and Ki67 images in breast cancer, confirming the superiority of SMILE in diverse stain conversion applications. Collectively, this framework provides a scalable pipeline for high-throughput proteomic inference from archival H&Es, providing transformative potential for pancreatic research and digital pathology.

bioinformatics↗

bioRxiv2026

Dynamic dissociation of the IFT complex drives ciliary dysfunction during C. elegans ageing

Intraflagellar transport (IFT) is essential for cilia, and its dysfunction drives ciliopathies and systemic ageing. However, the in vivo dynamics of individual components in the IFT complexes remain obscured, leaving the mechanisms of age-dependent IFT failure largely unknown. Here, we report a dual-color super-resolution imaging strategy to dissect the structural integrity and kinetics of IFT trains in the sensory cilia of young and aged Caenorhabditis elegans. We show that IFT complexes are not static entities. Instead, distinct components undergo dynamic dissociation within IFT trains. This intra-complex dissociation causes a remarkable reduction in IFT velocity and is significantly exacerbated in the cilia of aged worms. Mechanistically, we identify the conserved TRiC/CCT chaperonin complex and daf-19/RFX, the master transcription factor driving IFT genes, as critical regulators of IFT stability. We demonstrate that their age-dependent downregulation drives the progressive IFT component dissociation. Our findings re-frame the IFT complex as a highly dynamic assembly, uncover a new dimension of IFT regulation, and identify the progressive uncoupling of IFT components as a key driver of ciliary dysfunction during ageing.

cell biology↗

bioRxiv2026

Learning latent conformational landscapes encoded in cryo-EM

A protein populates a landscape of structural states, abundant snapshots of which are sampled in every cryo-EM experiment. Current analysis averages these snapshots into single density maps or partitions them into discrete classes, discarding the continuous dynamics encoded in the data. Continuous latent-space methods offer a promising alternative, yet whether their learned representations are physically grounded remains unresolved. Here, we realize cryo-EM as structural landscape microscopy, in which latent density directly reflects the probabilistic distribution of molecular states. A central question is whether such a landscape reflects physical reality. For integrin v{beta}8, the learned landscape shows strong agreement with independently derived molecular dynamics simulations, supporting its physical plausibility. We then apply the landscape to structural states that conventional cryo-EM cannot resolve. For LIS1-mediated dynein activation, the landscape reveals a spectrum of states from dominant conformations to low-population intermediates defined by distinct binding modes, including a previously unresolved state. For the KCTD5/CUL3NTD/G{beta}{gamma} complex, the landscape resolves continuous conformational pathways directly from experimental data. Probability-guided particle selection further improves reconstruction quality.

molecular biology↗

bioRxiv2026

Forensic Identification of Confiscated Helmeted Hornbill (Rhinoplax vigil) Casques and Implications for Individual Quantification in Wildlife Crimes

In wildlife forensic practice, species identification and estimation of the Minimum Number of Individuals (MNI) for highly processed specimens have long relied on weight-based conversion methods, which may result in underestimation of the number of individuals involved in a case. Focusing on 41 confiscated casque products of the helmeted hornbill (Rhinoplax vigil), including 32 newly added Tianjin samples, this study combines macroscopic morphological examination with mitochondrial DNA barcoding (16S rRNA, COI, and Cytb) to explore a more robust approach for individual quantification. The results demonstrate that the conventional "weight-based" approach overlooks critical biological information contained in anatomical structures and cannot accurately reflect the actual number of individuals involved. Based on this, we propose an anatomy-based criterion centered on the principle of structural uniqueness: specimens retaining biologically unique beak or casque structures should be directly assigned to a single individual, whereas weight-based estimation should only be applied when original anatomical features are entirely absent. In addition, based on morphometric calibration using a larger sample size (n = 40), we propose updating the reference benchmark for estimating the number of individuals in heavily processed solid casque products from 86 g to 65 g. This approach improves the scientific rigor and accuracy of forensic identification and provides reliable technical support for the conviction, sentencing, and law enforcement of wildlife trafficking cases involving helmeted hornbill and other endangered species.

zoology↗

bioRxiv2026

Modeling the Influence of Bandwidth and Envelope on Categorical Loudness Scaling

In a loudness-matching paradigm, a reduction in the loudness of sounds with bandwidths less than one-half octave compared to a tone of equal sound pressure level has been observed previously for five-tone complexes at 60 dB SPL centered at 1 kHz. Here, this loudness-reduction phenomenon is explored using band-limited noise across wide ranges of frequency and level. Additionally, these measurements are simulated by a model of loudness judgement based on neural ensemble averaging (NEA), which serves as a proxy for central auditory signal processing. Multi-frequency equal-loudness contours (ELC) were measured for each of the adult participants (N=100) with pure-tone average (PTA) thresholds that ranged from normal to moderate hearing loss using a categorical-loudness-scaling (CLS) paradigm. Presentation level and center frequency of the test stimuli were determined on each trial according to a Bayesian adaptive algorithm, which enabled multi-frequency ELC estimation within about five minutes of testing. Three separate test conditions differed by stimulus type: (1) pure-tone, (2) quarter-octave noise and (3) octave noise. For comparison, loudness judgements for all three stimulus types were also simulated by the NEA model, which comprised a nonlinear, active, time-domain cochlear model with an appended stage of neural spike generation. Mid-bandwidth loudness reduction was observed to be greatest at moderate stimulus levels and frequencies near 1 kHz. This feature was approximated by the NEA model, which suggests involvement of an early stage of the central auditory system in the formation of loudness judgements.

neuroscience↗