734 research outputs found

    Tolerance to Sound Intensity of Binaural Coincidence Detection in the Nucleus Laminaris of the Owl

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    Neurons of the owl's nucleus laminaris serve as coincidence detectors for measurement of interaural time difference. The discharge rate of nucleus laminaris neurons for both monaural and binaural stimulation increased with sound intensity until they reached an asymptote. Intense sounds affected neither the ratio between binaural and monaural responses nor the interaural time difference for which nucleus laminaris neurons were selective. Theoretical analysis showed that high afferent discharge rates cause coincidence detectors with only excitatory input to lose their selectivity for interaural time difference when coincidence of impulses from the same side becomes as likely as that of impulses from the two sides. We hypothesize that inhibitory input whose strength increases with sound intensity protects nucleus laminaris neurons from losing their sensitivity to interaural time difference with intense sounds

    Adaptive map alignment in the superior colliculus of the barn owl: a neuromorphic implementation

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    Adaptation is one of the basic phenomena of biology, while adaptability is an important feature for neural network. Young barn owl can well adapt its visual and auditory integration to the environmental change, such as prism wearing. At first, a mathematical model is introduced by the related study in biological experiment. The model well explained the mechanism of the sensory map realignment through axongenesis and synaptogenesis. Simulation results of this model are consistent with the biological data. Thereafter, to test the model’s application in hardware, the model is implemented into a robot. Visual and auditory signals are acquired by the sensors of the robot and transferred back to PC through bluetooth. Results of the robot experiment are presented, which shows the SC model allowing the robot to adjust visual and auditory integration to counteract the effects of a prism. Finally, based on the model, a silicon Superior Colliculus is designed in VLSI circuit and fabricated. Performance of the fabricated chip has shown the synaptogenesis and axogenesis can be emulated in VLSI circuit. The circuit of neural model provides a new method to update signals and reconfigure the switch network (the chip has an automatic reconfigurable network which is used to correct the disparity between signals). The chip is also the first Superior Colliculus VLSI circuit to emulate the sensory map realignment

    The Role of GABAergic Inhibition in Processing of lnteraural Time Difference in the Owl's Auditory System

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    The barn owl uses interaural time differences (ITDs) to localize the azimuthal position of sound. ITDs are processed by an anatomically distinct pathway in the brainstem. Neuronal selectivity for ITD is generated in the nucleus laminaris (NL) and conveyed to both the anterior portion of the ventral nucleus of the lateral lemniscus (VLVa) and the central (ICc) and external (ICx) nuclei of the inferior colliculus. With tonal stimuli, neurons in all regions are found to respond maximally not only to the real ITD, but also to ITDs that differ by integer multiples of the tonal period. This phenomenon, phase ambiguity, does not occur when ICx neurons are stimulated with noise. The main aim of this study was to determine the role of GABAergic inhibition in the processing of ITDs. Selectivity for ITD is similar in the NL and VLVa and improves in the ICc and ICx. Iontophoresis of bicuculline methiodide (BMI), a selective GABAA antagonist, decreased the ITD selectivity of ICc and ICx neurons, but did not affect that of VLVa neurons. Responses of VLVa and ICc neurons to unfavorable ITDs were below the monaural response levels. BMI raised both binaural responses to unfavorable ITDs and monaural responses, though the former remained smaller than the latter. During BMI application, ICx neurons showed phase ambiguity to noise stimuli and no longer responded to a unique ITD. BMI increased the response magnitude and changed the temporal discharge patterns in the VLVa, ICc, and ICx. Iontophoretically applied GABA exerted effects opposite to those of BMI, and the effects could be antagonized with simultaneous application of BMI. These results suggest that GABAergic inhibition (1) sharpens ITD selectivity in the ICc and ICx, (2) contributes to the elimination of phase ambiguity in the ICx, and (3) controls response magnitude and temporal characteristics in the VLVa, ICc, and ICx. Through these actions, GABAergic inhibition shapes the horizontal dimension of the auditory receptive fields

    A Novel Frequency Based Current-to-Digital Converter with Programmable Dynamic Range

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    This work describes a novel frequency based Current to Digital converter, which would be fully realizable on a single chip. Biological systems make use of delay line techniques to compute many things critical to the life of an animal. Seeking to build up such a system, we are adapting the auditory localization circuit found in barn owls to detect and compute the magnitude of an input current. The increasing drive to produce ultra low-power circuits necessitates the use of very small currents. Frequently these currents need to accurately measured, but current solutions typically involve off-chip measurements. These are usually slow, and moving a current off chip increases noise to the system. Moving a system such as this completely on chip will allow for precise measurement and control of bias currents, and it will allow for better compensation of some common transistor mismatch issues. This project affords an extremely low power (100s nW) converter technology that is also very space efficient. The converter is completely asynchronous which yields ultra-low power standby operation [1]

    Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

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    International audienceNeurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo

    Unsupervised classification to improve the quality of a bird song recording dataset

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    Open audio databases such as Xeno-Canto are widely used to build datasets to explore bird song repertoire or to train models for automatic bird sound classification by deep learning algorithms. However, such databases suffer from the fact that bird sounds are weakly labelled: a species name is attributed to each audio recording without timestamps that provide the temporal localization of the bird song of interest. Manual annotations can solve this issue, but they are time consuming, expert-dependent, and cannot run on large datasets. Another solution consists in using a labelling function that automatically segments audio recordings before assigning a label to each segmented audio sample. Although labelling functions were introduced to expedite strong label assignment, their classification performance remains mostly unknown. To address this issue and reduce label noise (wrong label assignment) in large bird song datasets, we introduce a data-centric novel labelling function composed of three successive steps: 1) time-frequency sound unit segmentation, 2) feature computation for each sound unit, and 3) classification of each sound unit as bird song or noise with either an unsupervised DBSCAN algorithm or the supervised BirdNET neural network. The labelling function was optimized, validated, and tested on the songs of 44 West-Palearctic common bird species. We first showed that the segmentation of bird songs alone aggregated from 10% to 83% of label noise depending on the species. We also demonstrated that our labelling function was able to significantly reduce the initial label noise present in the dataset by up to a factor of three. Finally, we discuss different opportunities to design suitable labelling functions to build high-quality animal vocalizations with minimum expert annotation effort

    Coarse Analysis of Microscopic Models using Equation-Free Methods

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    Numerical investigation on aerodynamic noises of the lateral window in vehicles

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    The paper firstly conducted a numerical simulation for flow fields and aerodynamic noises of the lateral window region in vehicles, and verified its correctness using the experimental test. Numerical simulation shows that: A pillar has a complicated shape and large corner, so that airflows will be separated here. An eddy structure is caused in the lateral window region and develops along the A pillar to generate serious pressure pulsations. A low pressure region is formed behind the A pillar. Obvious airflow separation regions are in the A pillar, rear view mirrors, wheels and wheel chambers. These airflow separation regions are typical positions causing aerodynamic noises. Additionally, large separated regions are located at the tail part of the vehicle, which is a main reason for causing the aerodynamic resistance. Intensity and velocity of eddies near the lateral window surface are relatively large, while its intensity near edges of the rear view mirror is weak. The shape of eddies extends along the flow direction to be an oval shape. The separated and broken eddies are sources for causing pressure pulsations. According to sound pressures of observation points, it can be also found that the separated eddy is a main reason for causing aerodynamic noises. Sound pressures are low at the right upper corner of lateral windows. In addition, noise distributions on the lateral window become gradually uniform with the increased frequency. In order to reduce flow noises, a bionic saw-tooth structure is applied to A pillars and rear view mirrors. After the bionic structure is introduced, some fluids are adhered to A pillars and rear view mirrors, so that the energy of fluids reaching the lateral window is reduced. In addition, fluids in rear regions of the rear view mirror presented a spiral shape, so that the possibility of fluid diffusion will be also reduced. In the original model, the maximum energy is 57.77, while that in this region with the bionic saw-tooth structures is 55.00. Obviously, the eddy energy is weakened. Compared with the original model, flow noises of all the observation points are reduced to different degrees, and the noise reduction effect is obvious. The results fully prove that this region with bionic saw-teeth in this paper has obvious advantages in noise reduction
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