RESUMEN
OBJECTIVE: Cochlear implants (CI) provide users with a spectrally degraded acoustic signal that could impact their auditory emotional experiences. This study evaluated the effects of CI-simulated spectral degradation on emotional valence and arousal elicited by environmental sounds. DESIGN: Thirty emotionally evocative sounds were filtered through a noise-band vocoder. Participants rated the perceived valence and arousal elicited by each of the full-spectrum and vocoded stimuli. These ratings were compared across acoustic conditions (full-spectrum, vocoded) and as a function of stimulus type (unpleasant, neutral, pleasant). STUDY SAMPLE: Twenty-five young adults (age 19 to 34 years) with normal hearing. RESULTS: Emotional responses were less extreme for spectrally degraded (i.e., vocoded) sounds than for full-spectrum sounds. Specifically, spectrally degraded stimuli were perceived as more negative and less arousing than full-spectrum stimuli. CONCLUSION: By meticulously replicating CI spectral degradation while controlling for variables that are confounded within CI users, these findings indicate that CI spectral degradation can compress the range of sound-induced emotion independent of hearing loss and other idiosyncratic device- or person-level variables. Future work will characterize emotional reactions to sound in CI users via objective, psychoacoustic, and subjective measures.
RESUMEN
Background: Recent Alzheimer's disease (AD) discoveries are increasingly based on studies from a variety of omics technologies on large cohorts. Currently, there is no easily accessible resource for neuroscientists to browse, query, and visualize these complex datasets in a harmonized manner. Objective: Create an online portal of public omics datasets for AD research. Methods: We developed Alzheimer DataLENS, a web-based portal, using the R Shiny platform to query and visualize publicly available transcriptomics and genetics studies of AD on human cohorts. To ensure consistent representation of AD findings, all datasets were processed through a uniform bioinformatics pipeline. Results: Alzheimer DataLENS currently houses 2 single-nucleus RNA sequencing datasets, over 30 bulk RNA sequencing datasets from 19 brain regions and 3 cohorts, and 2 genome-wide association studies (GWAS). Available visualizations for single-nucleus data include bubble plots, heatmaps, and UMAP plots; for bulk expression data include box plots and heatmaps; for pathways include protein-protein interaction network plots; and for GWAS results include Manhattan plots. Alzheimer DataLENS also links to two other knowledge resources: the AD Progression Atlas and the Astrocyte Atlas. Conclusions: Alzheimer DataLENS is a valuable resource for investigators to quickly and systematically explore omics datasets and is freely accessible at https://alzdatalens.partners.org.