Pitch Enumeration: Failure to Subitize in Audition

Background: Subitizing involves recognition mechanisms that allow effortless enumeration of up to four visual objects, however despite ample resolution experimental data suggest that only one pitch can be reliably enumerated. This may be due to the grouping of tones according to harmonic relationships by recognition mechanisms prior to fine pitch processing. Poorer frequency resolution of auditory information available to recognition mechanisms may lead to unrelated tones being grouped, resulting in underestimation of pitch number. Methods, Results and Conclusion: We tested whether pitch enumeration is better for chords of full harmonic complex tones, where grouping errors are less likely, than for complexes with fewer and less accurately tuned harmonics. Chords of low familiarity were used to mitigate the possibility that participants would recognize the chord itself and simply recall the number of pitches. We found that accuracy of pitch enumeration was less than the visual system overall, and underestimation of pitch number increased for stimuli containing fewer harmonics. We conclude that harmonically related tones are first grouped at the poorer frequency resolution of the auditory nerve, leading to poor enumeration of more than one pitch

Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds

Humans can robustly recognize and localize objects by integrating visual and auditory cues. While machines are able to do the same now with images, less work has been done with sounds. This work develops an approach for dense semantic labelling of sound-making objects, purely based on binaural sounds. We propose a novel sensor setup and record a new audio-visual dataset of street scenes with eight professional binaural microphones and a 360 degree camera. The co-existence of visual and audio cues is leveraged for supervision transfer. In particular, we employ a cross-modal distillation framework that consists of a vision `teacher' method and a sound `student' method -- the student method is trained to generate the same results as the teacher method. This way, the auditory system can be trained without using human annotations. We also propose two auxiliary tasks namely, a) a novel task on Spatial Sound Super-resolution to increase the spatial resolution of sounds, and b) dense depth prediction of the scene. We then formulate the three tasks into one end-to-end trainable multi-tasking network aiming to boost the overall performance. Experimental results on the dataset show that 1) our method achieves promising results for semantic prediction and the two auxiliary tasks; and 2) the three tasks are mutually beneficial -- training them together achieves the best performance and 3) the number and orientations of microphones are both important. The data and code will be released to facilitate the research in this new direction.Comment: Project page: https://www.trace.ethz.ch/publications/2020/sound_perception/index.htm

Compression of Auditory Space during Forward Self-Motion

<div><h3>Background</h3><p>Spatial inputs from the auditory periphery can be changed with movements of the head or whole body relative to the sound source. Nevertheless, humans can perceive a stable auditory environment and appropriately react to a sound source. This suggests that the inputs are reinterpreted in the brain, while being integrated with information on the movements. Little is known, however, about how these movements modulate auditory perceptual processing. Here, we investigate the effect of the linear acceleration on auditory space representation.</p> <h3>Methodology/Principal Findings</h3><p>Participants were passively transported forward/backward at constant accelerations using a robotic wheelchair. An array of loudspeakers was aligned parallel to the motion direction along a wall to the right of the listener. A short noise burst was presented during the self-motion from one of the loudspeakers when the listener’s physical coronal plane reached the location of one of the speakers (null point). In Experiments 1 and 2, the participants indicated which direction the sound was presented, forward or backward relative to their subjective coronal plane. The results showed that the sound position aligned with the subjective coronal plane was displaced ahead of the null point only during forward self-motion and that the magnitude of the displacement increased with increasing the acceleration. Experiment 3 investigated the structure of the auditory space in the traveling direction during forward self-motion. The sounds were presented at various distances from the null point. The participants indicated the perceived sound location by pointing a rod. All the sounds that were actually located in the traveling direction were perceived as being biased towards the null point.</p> <h3>Conclusions/Significance</h3><p>These results suggest a distortion of the auditory space in the direction of movement during forward self-motion. The underlying mechanism might involve anticipatory spatial shifts in the auditory receptive field locations driven by afferent signals from vestibular system.</p> </div

Egocentric and allocentric representations in auditory cortex

A key function of the brain is to provide a stable representation of an object’s location in the world. In hearing, sound azimuth and elevation are encoded by neurons throughout the auditory system, and auditory cortex is necessary for sound localization. However, the coordinate frame in which neurons represent sound space remains undefined: classical spatial receptive fields in head-fixed subjects can be explained either by sensitivity to sound source location relative to the head (egocentric) or relative to the world (allocentric encoding). This coordinate frame ambiguity can be resolved by studying freely moving subjects; here we recorded spatial receptive fields in the auditory cortex of freely moving ferrets. We found that most spatially tuned neurons represented sound source location relative to the head across changes in head position and direction. In addition, we also recorded a small number of neurons in which sound location was represented in a world-centered coordinate frame. We used measurements of spatial tuning across changes in head position and direction to explore the influence of sound source distance and speed of head movement on auditory cortical activity and spatial tuning. Modulation depth of spatial tuning increased with distance for egocentric but not allocentric units, whereas, for both populations, modulation was stronger at faster movement speeds. Our findings suggest that early auditory cortex primarily represents sound source location relative to ourselves but that a minority of cells can represent sound location in the world independent of our own position

Plasma and cellular fibronectin: distinct and independent functions during tissue repair

Fibronectin (FN) is a ubiquitous extracellular matrix (ECM) glycoprotein that plays vital roles during tissue repair. The plasma form of FN circulates in the blood, and upon tissue injury, is incorporated into fibrin clots to exert effects on platelet function and to mediate hemostasis. Cellular FN is then synthesized and assembled by cells as they migrate into the clot to reconstitute damaged tissue. The assembly of FN into a complex three-dimensional matrix during physiological repair plays a key role not only as a structural scaffold, but also as a regulator of cell function during this stage of tissue repair. FN fibrillogenesis is a complex, stepwise process that is strictly regulated by a multitude of factors. During fibrosis, there is excessive deposition of ECM, of which FN is one of the major components. Aberrant FN-matrix assembly is a major contributing factor to the switch from normal tissue repair to misregulated fibrosis. Understanding the mechanisms involved in FN assembly and how these interplay with cellular, fibrotic and immune responses may reveal targets for the future development of therapies to regulate aberrant tissue-repair processes

Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds

Humans can robustly recognize and localize objects by integrating visual and auditory cues. While machines are able to do the same now with images, less work has been done with sounds. This work develops an approach for dense semantic labelling of sound-making objects, purely based on binaural sounds. We propose a novel sensor setup and record a new audio-visual dataset of street scenes with eight professional binaural microphones and a 360 degree camera. The co-existence of visual and audio cues is leveraged for supervision transfer. In particular, we employ a cross-modal distillation framework that consists of a vision `teacher' method and a sound `student' method -- the student method is trained to generate the same results as the teacher method. This way, the auditory system can be trained without using human annotations. We also propose two auxiliary tasks namely, a) a novel task on Spatial Sound Super-resolution to increase the spatial resolution of sounds, and b) dense depth prediction of the scene. We then formulate the three tasks into one end-to-end trainable multi-tasking network aiming to boost the overall performance. Experimental results on the dataset show that 1) our method achieves good results for all the three tasks; and 2) the three tasks are mutually beneficial -- training them together achieves the best performance and 3) the number and the orientations of microphones are both important.ISSN:0302-9743ISSN:1611-334