Auditory Scene Analysis (ASA) refers to the grouping of acoustic signals into auditory objects. Previously, we have shown that perceived musicality of auditory sequences varies with high-level organizational features. Here, we explore the neural mechanisms mediating ASA and auditory object perception. Participants performed musicality judgments on randomly generated pure-tone sequences and manipulated versions of each sequence containing low-level changes (amplitude; timbre). Low-level manipulations affected auditory object perception as evidenced by changes in musicality ratings. fMRI was used to measure neural activation to sequences rated most and least musical, and the altered versions of each sequence. Next, we generated two partially overlapping networks: (i) a music processing network (music localizer) and (ii) an ASA network (base sequences vs. ASA manipulated sequences). Using Representational Similarity Analysis, we correlated the functional profiles of each ROI to a model generated from behavioral musicality ratings as well as models corresponding to low-level feature processing and music perception. Within overlapping regions, areas near primary auditory cortex correlated with low-level ASA models, whereas right IPS was correlated with musicality ratings. Shared neural mechanisms that correlate with behavior and underlie both ASA and music perception suggests that low-level features of auditory stimuli play a role in auditory object perception.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183742 | PMC |
http://dx.doi.org/10.1093/cercor/bhac501 | DOI Listing |
Proc Biol Sci
January 2025
Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy.
Perceptual adaptation has been widely used to infer the existence of numerosity detectors, enabling animals to quickly estimate the number of objects in a scene. Here, we investigated, in humans, whether numerosity adaptation is influenced by stimulus feature changes as previous research suggested that adaptation is reduced when the colour of adapting and test stimuli did not match. We tested whether such adaptation reduction is due to unspecific novelty effects or changes of stimuli identity.
View Article and Find Full Text PDFIn the field of image processing, optical neural networks offer advantages such as high speed, high throughput, and low energy consumption. However, most existing coherent optical neural networks (CONN) rely on coherent light sources to establish transmission models. The use of laser inputs and electro-optic modulation devices at the front end of these neural networks diminishes their computational capability and energy efficiency, thereby limiting their practical applications in object detection tasks.
View Article and Find Full Text PDFPlant Biol (Stuttg)
January 2025
Department of Behavioral Physiology and Sociobiology, University of Würzburg, Würzburg, Germany.
Nature offers a bewildering diversity of flower colours. Understanding the ecology and evolution of this fantastic floral diversity requires knowledge about the visual systems of their natural observers, such as insect pollinators. The key question is how flower colour and pattern can be measured and represented to characterise the signals that are relevant to pollinators.
View Article and Find Full Text PDFJ Exp Psychol Gen
January 2025
Department of Experimental Psychology, Helmholtz Institute, Utrecht University.
Predicting the location of moving objects in noisy environments is essential to everyday behavior, like when participating in traffic. Although many objects provide multisensory information, it remains unknown how humans use multisensory information to localize moving objects, and how this depends on expected sensory interference (e.g.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Experimental Psychology, Justus Liebig University Giessen, Giessen, Germany.
The human visual system possesses a remarkable ability to detect and process faces across diverse contexts, including the phenomenon of face pareidolia--seeing faces in inanimate objects. Despite extensive research, it remains unclear why the visual system employs such broadly tuned face detection capabilities. We hypothesized that face pareidolia results from the visual system's optimization for recognizing both faces and objects.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!