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The “cocktail party” problem—how a listener perceives speech in noisy environments—is typically studied using speech (multi-talker babble) or noise maskers. However, realistic cocktail party scenarios often include background music (e.g., coffee shops, concerts). Studies investigating music’s effects on concurrent speech perception have predominantly used highly controlled synthetic music or shaped noise, which do not reflect naturalistic listening environments. Behaviorally, familiar background music and songs with vocals/lyrics inhibit concurrent speech recognition. Here, we investigated the neural bases of these effects. While recording multichannel EEG, participants listened to an audiobook while popular songs (or silence) played in the background at a 0 dB signal-to-noise ratio. Songs were either familiar or unfamiliar to listeners and featured either vocals or isolated instrumentals from the original audio recordings. Comprehension questions probed task engagement. We used temporal response functions (TRFs) to isolate cortical tracking to the target speech envelope and analyzed neural responses around 100 ms (i.e., auditory N1 wave). We found that speech comprehension was, expectedly, impaired during background music compared to silence. Target speech tracking was further hindered by the presence of vocals. When masked by familiar music, response latencies to speech were less susceptible to informational masking, suggesting concurrent neural tracking of speech was easier during music known to the listener. These differential effects of music familiarity were further exacerbated in listeners with less musical ability. Our neuroimaging results and their dependence on listening skills are consistent with early attentional-gain mechanisms where familiar music is easier to tune out (listeners already know the song’s expectancies) and thus can allocate fewer attentional resources to the background music to better monitor concurrent speech material.

Studies of acoustic communication often focus on the categories and units of vocalizations, but subtle variation also occurs in how these signals are uttered. In human speech, it is not only phonemes and words that carry information but also the timbre, intonation, and stress of how speech sounds are delivered (often referred to as “paralinguistic content”). In non-human animals, variation across utterances of vocal signals also carries behaviorally relevant information across taxa. However, the discriminability of these cues has been rarely tested in a psychophysical paradigm. Here, we focus on acoustic communication in the zebra finch ( Taeniopygia guttata ), a songbird species in which the male produces a single stereotyped motif repeatedly in song bouts. These motif renditions, like the song repetitions of many birds, sound very similar to the casual human listener. In this study, we show that zebra finches can easily discriminate between the renditions, even at the level of single song syllables, much as humans can discriminate renditions of speech sounds. These results support the notion that sensitivity to fine acoustic details may be a primary channel of information in zebra finch song, as well as a shared, foundational property of vocal communication systems across species.

pTau217 is a well validated plasma biomarker for Alzheimer's disease (AD), sensitive to the accumulation of amyloid pathology in the preclinical stages of disease. We leveraged whole blood RNA sequencing and plasma pTau217 measures of amyloid burden to identify blood transcriptomic gene-network changes that relate to plasma pTau217 levels in cognitively normal older adults. We then quantified the abundance of cell populations from the transcriptomic data to identify blood cell abundance alterations that correlate with plasma ptau217 levels. Whole blood RNA sequencing and plasma pTau217 data were obtained from 1739 participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) Study. RNAseq data were aligned, sorted, counted, batch normalized, and iteratively adjusted for covariates. 20,718 genes were available for analysis following quality control. Plasma samples (n = 1597) were analyzed for pTau217 using the Eli Lilly and Company Diagnostics Laboratory immunoassay. Samples from 724 participants (63% females, mean age 71, 61% amyloid+) with RNA sequencing and biomarker data were used for analysis. Cell fractions were quantified using CIBERSORTx (LM22 used as reference) and WGCNA was used to calculate gene co-expression modules. Linear regression related gene module expression or cell fraction to mean pTau217 levels covarying for age, sex, education, APOE ε2 and ε4 status. Correction for multiple comparisons used the false discovery rate. Gene enrichment was performed using Gene Ontology. Five gene modules were associated with plasma pTau217. For the turquoise module (β=-0.81, p.fdr=0.005), higher expression was associated with higher p-tau217 while higher expression in the blue (β=-0.70, p.fdr=0.01), lightcyan (β=-0.68, p.fdr=0.01), grey60 (β=-0.64, p.fdr=0.02), and brown (β=-0.55, p.fdr=0.04) modules were associated with lower p-tau217. These modules were enriched for phagocytosis, ribonucleoprotein complex biogenesis, immunoglobulin mediated immune response, nucleosome assembly, and cytoplasmic translation pathway genes. In cell fraction analysis, higher predicted abundance of neutrophils related to ptau217 levels (β=0.33, p.fdr=0.03). Our results demonstrate an association between immune response and epigenetic pathway genes with plasma pTau217 levels in preclinical AD. Future work will seek to clarify whether these signatures also relate to brain amyloid PET to evaluate blood transcription networks as complementary biomarkers to improve preclinical prediction.

INTRODUCTION Early biological pathways explaining the risk for Alzheimer's disease (AD)–related cognitive decline remain poorly understood. METHODS Using linear mixed‐effects models, we investigated whether whole blood gene expression (RNA sequencing) moderates the relationship between AD biomarkers measured by amyloid beta (Aβ) and tau‐PET (positron emission tomography) imaging and longitudinal cognition in 770 cognitively unimpaired older adults (Agemean = 71.3, 62% female) from Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) (A4/LEARN). RESULTS We identified protective and AD risk–related gene expression signatures on the autosome and X chromosome. Six genes (ngenes(%); 2(33%) X‐linked) interacted with Aβ‐PET, whereas 103 genes (3(3%) X‐linked) interacted with neocortical tau‐PET, to influence cognitive decline. A total of 110 genes (17(15%) X‐linked) and 3156 genes (121(4%) X‐linked) were moderated by both sex and Aβ‐ or tau‐PET, respectively. Pathway enrichment analyses reflected immunity, protein synthesis, and lipid metabolism. DISCUSSION These findings underscore the importance of peripheral transcriptomic markers in identifying sex‐differentiated pathways related to risk of and protection from cognitive decline in preclinical AD. Highlights Whole blood gene expression moderates biomarker–cognition associations in preclinical AD Six genes interacted with amyloid beta positron emission tomography (Aβ‐PET) and 103 with tau‐PET to influence cognitive decline Over 3000 gene‐by‐sex interactions reveal sex‐specific transcriptomic vulnerability Pathways implicate immunity, ribosomal biology, and vesicle trafficking processes Findings support blood‐based, sex‐aware biomarkers for precision AD risk stratification

\"Cocktail party\" speech perception is largely studied using either linguistic or nonspeech noise maskers. Few studies have addressed how listeners understand speech during concurrent music. We used popular songs to probe the effects of familiarity and different inherent properties of background music (i.e., isolated vocals, isolated instruments, or unprocessed song) on speech recognition. Participants performed an open-set sentence recognition task in the presence of familiar and unfamiliar music maskers (−5 dB signal-to-noise ratio [SNR]) composed of the full unprocessed song, only the instrumentals, or only the vocals. We found that full songs negatively affected recognition performance more so than isolated vocals and instrumentals. Surprisingly, there was also an interaction with music familiarity; well-known music impaired performance in the homologous full song and instrumental conditions. Our results show strong effects of song component and familiarity on speech recognition ability, highlighting interactions between both physical and psychological characteristics of musical noise on task performance. Familiarity impairs speech perception when background music features the instrumentals with or without the vocals. Our findings have implications for understanding the possible facilitation (or interference) of background music during concurrent linguistic tasks including academic study in attempts to promote learning.

Prior evidence suggests that neocortical tau in those with higher β-amyloid (Aβ) may be the main driver of Alzheimer's disease (AD)-related neurodegeneration leading to insidious cognitive decline and ultimately a diagnosis of AD dementia. Resistance to the 'spread' of neocortical tau pathology from localized medial temporal (MTL) regions can be defined as individuals having lower neocortical tau than expected given their individual characteristics, such as demographics and Aβ burden. We examined associations between resistance to neocortical tau pathology and various markers of AD pathology, cognitive performance, and brain reserve. We calculated tau resistance using our published inverse learning method (Figure 1B), which estimates the deviation away from a model trained on an expectation sample (278 Aβ-PET+ older adults with high neocortical tau-PET (PVC_SUVR :inferior temporal/inferior parietal/fusiform/middle temporal) burden based on Gaussian Mixture Modeling;Figure 2A). We ran a series of linear regression models on the remaining 1,374 older adults pooled from the Harvard Aging Brain Study (HABS), ADNI, and A4/LEARN (Demographics in Figure 1A). We examined associations between tau resistance and 1) MTL tau-PET (PVC_SUVR ; entorhinal/amygdala/parahippocampal), 2) measures of brain reserve (hippocampal volume and entorhinal cortical thickness), 3) neocortical Aβ-PET burden (Centiloids), 4) an interaction between MTL tau and Aβ-PET, and 5) cognitive performance (PACC). All models adjusted for age, sex, education, cohort, and APOEε4. Lower MTL tau, lower Aβ, and younger age were significantly associated with higher neocortical tau resistance (β =-0.22(0.06), p <0.001, Figure 2B; β =-0.13(0.03), p <0.001Figure 2C;β =-0.62(0.02), p <0.001). Higher PACC, greater hippocampal volume and thicker entorhinal cortices were associated with lower resistance (β =-0.29(0.02), p <0.001, Figure 2D;β =-0.10(0.03), p <0.001, β =-0.14(0.03), p <0.001). Greater Aβ and MTL tau burden interacted to influence lower resistance (Figure 3). In a sample limited to Aβ+ (N = 537), we found only lower PACC and younger age significantly associated with tau resistance. These findings suggest that baseline levels of MTL tau and age play a role in resisting the advancement of tauopathy into neocortical brain regions, and might be mediated by Aβ in early disease stages. The counter-intuitive association with cognition and brain reserve measures implies that tau resistance is most likely represented by those with greater cognitive impairment and lower reserve, as neocortical tau burden is much lower in clinically-normal older adults.

Prior evidence suggests that neocortical tau in those with higher β-amyloid (Aβ) may be the main driver of Alzheimer's disease (AD)-related neurodegeneration leading to insidious cognitive decline and ultimately a diagnosis of AD dementia. Resistance to the 'spread' of neocortical tau pathology from localized medial temporal (MTL) regions can be defined as individuals having lower neocortical tau than expected given their individual characteristics, such as demographics and Aβ burden. We examined associations between resistance to neocortical tau pathology and various markers of AD pathology, cognitive performance, and brain reserve. We calculated tau resistance using our published inverse learning method (Figure 1B), which estimates the deviation away from a model trained on an expectation sample (278 Aβ-PET+ older adults with high neocortical tau-PET (PVC_SUVR :inferior temporal/inferior parietal/fusiform/middle temporal) burden based on Gaussian Mixture Modeling;Figure 2A). We ran a series of linear regression models on the remaining 1,374 older adults pooled from the Harvard Aging Brain Study (HABS), ADNI, and A4/LEARN (Demographics in Figure 1A). We examined associations between tau resistance and 1) MTL tau-PET (PVC_SUVR ; entorhinal/amygdala/parahippocampal), 2) measures of brain reserve (hippocampal volume and entorhinal cortical thickness), 3) neocortical Aβ-PET burden (Centiloids), 4) an interaction between MTL tau and Aβ-PET, and 5) cognitive performance (PACC). All models adjusted for age, sex, education, cohort, and APOEε4. Lower MTL tau, lower Aβ, and younger age were significantly associated with higher neocortical tau resistance (β =-0.22(0.06), p < 0.001, Figure 2B; β =-0.13(0.03), p <0.001Figure 2C;β =-0.62(0.02), p < 0.001). Higher PACC, greater hippocampal volume and thicker entorhinal cortices were associated with lower resistance (β =-0.29(0.02), p < 0.001, Figure 2D;β =-0.10(0.03), p < 0.001, β =-0.14(0.03), p < 0.001). Greater Aβ and MTL tau burden interacted to influence lower resistance (Figure 3). In a sample limited to Aβ+ (N = 537), we found only lower PACC and younger age significantly associated with tau resistance. These findings suggest that baseline levels of MTL tau and age play a role in resisting the advancement of tauopathy into neocortical brain regions, and might be mediated by Aβ in early disease stages. The counter-intuitive association with cognition and brain reserve measures implies that tau resistance is most likely represented by those with greater cognitive impairment and lower reserve, as neocortical tau burden is much lower in clinically-normal older adults.

Higher levels of plasma p-tau are closely associated with increased Aβ-PET burden, and subsequent cognitive decline in older adults, supporting it as a sensitive, early marker of AD. Previous studies implicated X-linked gene expression in AD but were limited to gene expression from postmortem tissue resulting in findings less clinically relevant to early stages of disease. To better inform the relationship between X-linked genes and AD during the earliest disease processes, we aimed to identify associations between whole blood X-linked gene expression and plasma p-tau levels in clinically normal older adults from A4/LEARN. We leveraged Aβ-PET( F-Florbetapir), plasma p-tau (immunoassay, Eli Lilly), and whole blood RNAseq data from 724 cognitively unimpaired participants (72.2years(±4.6); 63%Female; 35%APOEε4+; 26%Aβ+) from the A4 clinical trial at baseline (placebo[31%], treatment[30%]) and the LEARN[39%] observational study. We ran linear regressions adjusting for age, BMI, and cohort to determine associations between the following terms and p-tau (pg/mL): gene, gene*APOEε4, gene*sex, gene*Aβ , and gene*sex*Aβ . Though focusing on X-linked genes, results were FDR-corrected for both autosomal and X-linked genes (n = 20,621). No X-linked genes were directly associated with p-tau levels. 119 X-linked genes were moderated by Aβ and 27 genes by Aβ*sex on p-tau . Notably, we identified 4 genes previously implicated in AD: FAM156B, KDM6A, WWC3, and MIDI1IP1, which are involved in chromatin remodeling, hippo pathway signaling, and lipid signaling. In gene*Aβ models, higher FAM156B expression (β=-0.09(0.03), p <0.001, Figure 1A) was associated with lower p-tau levels among individuals with high Aβ-PET burden whereas higher KDM6A expression (β=0.31(0.10), p =0.003, Figure 1B) was associated with higher p-tau levels in both sexes. In females with elevated Aβ-PET, higher WWC3 expression was associated with lower p-tau (β=-0.44(0.15), p =0.004, Figure 1C). In males with high Aβ-PET burden, both greater WWC3 (β=0.37(0.14), p =0.01, Figure 1C) and MID1IP1 (β=0.60(0.15), p <0.001, Figure 1D) expression was associated with higher p-tau . Significant whole-blood X-linked gene expression associations with p-tau levels in clinically normal older adults are largely moderated by Aβ-PET burden and sex. This study identified both protective and risk genes, highlighting novel gene candidates for further validation and supporting the need to study sex chromosomes in AD.

Bulk brain tissue studies of gene expression have discovered novel biological pathways associated with Alzheimer's disease (AD) neuropathology and pre-morbid cognitive decline. These findings are primarily tuned to much older adults and are focused on end-of-life changes. The objective of this study was to ascertain transcriptomic signals from whole blood associated with cognitive decline in clinically unimpaired older adults from the A4 and LEARN studies. Identifying genes in whole blood that are associated with in vivo AD phenotypes can elucidate biological pathways implicated in the earliest disease processes. 1,737 participants were included from the A4 clinical trial of solanazumab. Both placebo and treatment arms were included (and participants who screen failed at baseline to inform our model intercepts), and the adjoining LEARN observational study (Aβ-). All participants had whole blood gene expression data from the autosome and X chromosome (20,621 genes), and 770 participants (71.3±4.7 years; 62% Female; 45% APOEε4+; 59% Aβ+) had at least two cognitive assessments measured using the PACC. Linear mixed-effects models determined the association between gene expression alone and interactions with sex, APOEε4, continuous Aβ-PET burden, and p-tau on longitudinal PACC. All analyses included random intercepts/slopes, and adjusted for age, education, cohort, PACC version, and cumulative dose. All analyses were FDR corrected. No individual transcript was associated with longitudinal cognition after FDR correction. 167 genes were associated with longitudinal cognition when modified through different markers. One gene (TRBV4-2; Figure 2C) was moderated by APOEε4 x sex, 6 genes by Aβ-PET, 118 genes by Aβ-PET x sex, and 17 genes weakly by p-tau (Figure 1). Of note, lower ETF1P2 expression, a noncoding pseudogene that resembles ETF1 and plays a role in protein synthesis, was associated with faster cognitive decline among participants with high baseline Aβ-PET burden (Figure 2A; b =2.33(0.456), p  = 0.011). Similarly, greater ZSCAN2 expression, implicated in regulating inflammation, was associated with faster cognitive decline particularly among males with higher baseline Aβ-PET burden (Figure 2D; b =-6.92(1.33), p  = 0.004). Whole blood transcriptomic signals were primarily associated with cognitive decline via interactions with Aβ-PET, Aβ-PET x sex, and p-tau . Further work, such as enrichment analysis and validation in external cohorts, will elucidate relevant biological pathways.