Attention driven computational model of the auditory midbrain for sound localization in reverberant environments

2011 ◽  
Author(s):  
Jindong Liu ◽  
Harry Erwin ◽  
Guang-Zhong Yang
Keyword(s):  
Computational Model ◽  
Sound Localization ◽  
Auditory Midbrain ◽  
Reverberant Environments

scholarly journals Accurate Sound Localization in Reverberant Environments Is Mediated by Robust Encoding of Spatial Cues in the Auditory Midbrain

Neuron ◽  
2009 ◽  
Vol 62 (1) ◽  
pp. 123-134 ◽  
Author(s):  
Sasha Devore ◽  
Antje Ihlefeld ◽  
Kenneth Hancock ◽  
Barbara Shinn-Cunningham ◽  
Bertrand Delgutte
Keyword(s):  
Sound Localization ◽  
Spatial Cues ◽  
Auditory Midbrain ◽  
Reverberant Environments

scholarly journals Evidence for a neural source of the precedence effect in sound localization

2015 ◽  
Vol 114 (5) ◽  
pp. 2991-3001 ◽  
Author(s):  
Andrew D. Brown ◽  
Heath G. Jones ◽  
Alan Kan ◽  
Tanvi Thakkar ◽  
G. Christopher Stecker ◽  
...  
Keyword(s):  
Sound Localization ◽  
Normal Hearing ◽  
Nerve Fibers ◽  
Precedence Effect ◽  
Auditory Midbrain ◽  
Cochlear Function ◽  
Sound Sources ◽  
Human Patient ◽  
Bilateral Cochlear Implants ◽  
Reverberant Environments

Normal-hearing human listeners and a variety of studied animal species localize sound sources accurately in reverberant environments by responding to the directional cues carried by the first-arriving sound rather than spurious cues carried by later-arriving reflections, which are not perceived discretely. This phenomenon is known as the precedence effect (PE) in sound localization. Despite decades of study, the biological basis of the PE remains unclear. Though the PE was once widely attributed to central processes such as synaptic inhibition in the auditory midbrain, a more recent hypothesis holds that the PE may arise essentially as a by-product of normal cochlear function. Here we evaluated the PE in a unique human patient population with demonstrated sensitivity to binaural information but without functional cochleae. Users of bilateral cochlear implants (CIs) were tested in a psychophysical task that assessed the number and location(s) of auditory images perceived for simulated source-echo (lead-lag) stimuli. A parallel experiment was conducted in a group of normal-hearing (NH) listeners. Key findings were as follows: 1) Subjects in both groups exhibited lead-lag fusion. 2) Fusion was marginally weaker in CI users than in NH listeners but could be augmented by systematically attenuating the amplitude of the lag stimulus to coarsely simulate adaptation observed in acoustically stimulated auditory nerve fibers. 3) Dominance of the lead in localization varied substantially among both NH and CI subjects but was evident in both groups. Taken together, data suggest that aspects of the PE can be elicited in CI users, who lack functional cochleae, thus suggesting that neural mechanisms are sufficient to produce the PE.

Interdependence of Spatial and Temporal Coding in the Auditory Midbrain

2000 ◽  
Vol 83 (4) ◽  
pp. 2300-2314 ◽  
Author(s):  
U. Koch ◽  
B. Grothe
Keyword(s):  
Sound Localization ◽  
Feature Detection ◽  
Transfer Functions ◽  
Temporal Structure ◽  
Temporal Coding ◽  
Sound Recognition ◽  
Spatial Cues ◽  
Auditory Midbrain ◽  
Binaural Cues ◽  
Binaural Processing

To date, most physiological studies that investigated binaural auditory processing have addressed the topic rather exclusively in the context of sound localization. However, there is strong psychophysical evidence that binaural processing serves more than only sound localization. This raises the question of how binaural processing of spatial cues interacts with cues important for feature detection. The temporal structure of a sound is one such feature important for sound recognition. As a first approach, we investigated the influence of binaural cues on temporal processing in the mammalian auditory system. Here, we present evidence that binaural cues, namely interaural intensity differences (IIDs), have profound effects on filter properties for stimulus periodicity of auditory midbrain neurons in the echolocating big brown bat, Eptesicus fuscus. Our data indicate that these effects are partially due to changes in strength and timing of binaural inhibitory inputs. We measured filter characteristics for the periodicity (modulation frequency) of sinusoidally frequency modulated sounds (SFM) under different binaural conditions. As criteria, we used 50% filter cutoff frequencies of modulation transfer functions based on discharge rate as well as synchronicity of discharge to the sound envelope. The binaural conditions were contralateral stimulation only, equal stimulation at both ears (IID = 0 dB), and more intense at the ipsilateral ear (IID = −20, −30 dB). In 32% of neurons, the range of modulation frequencies the neurons responded to changed considerably comparing monaural and binaural (IID =0) stimulation. Moreover, in ∼50% of neurons the range of modulation frequencies was narrower when the ipsilateral ear was favored (IID = −20) compared with equal stimulation at both ears (IID = 0). In ∼10% of the neurons synchronization differed when comparing different binaural cues. Blockade of the GABAergic or glycinergic inputs to the cells recorded from revealed that inhibitory inputs were at least partially responsible for the observed changes in SFM filtering. In 25% of the neurons, drug application abolished those changes. Experiments using electronically introduced interaural time differences showed that the strength of ipsilaterally evoked inhibition increased with increasing modulation frequencies in one third of the cells tested. Thus glycinergic and GABAergic inhibition is at least one source responsible for the observed interdependence of temporal structure of a sound and spatial cues.

scholarly journals Localize Animal Sound Events Reliably (LASER): A New Software for Sound Localization in Zoos

2021 ◽  
Vol 2 (2) ◽  
pp. 146-163
Author(s):  
Sebastian Schneider ◽  
Paul Wilhelm Dierkes
Keyword(s):  
Animal Welfare ◽  
Sound Localization ◽  
Background Noise ◽  
Physiological State ◽  
Basic Research ◽  
Correct Position ◽  
Reverberant Environments ◽  
In The Wild ◽  
The One

Locating a vocalizing animal can be useful in many fields of bioacoustics and behavioral research, and is often done in the wild, covering large areas. In zoos, however, the application of this method becomes particularly difficult, because, on the one hand, the animals are in a relatively small area and, on the other hand, reverberant environments and background noise complicate the analysis. Nevertheless, by localizing and analyzing animal sounds, valuable information on physiological state, sex, subspecies, reproductive state, social status, and animal welfare can be gathered. Therefore, we developed a sound localization software that is able to estimate the position of a vocalizing animal precisely, making it possible to assign the vocalization to the corresponding individual, even under difficult conditions. In this study, the accuracy and reliability of the software is tested under various conditions. Different vocalizations were played back through a loudspeaker and recorded with several microphones to verify the accuracy. In addition, tests were carried out under real conditions using the example of the giant otter enclosure at Dortmund Zoo, Germany. The results show that the software can estimate the correct position of a sound source with a high accuracy (median of the deviation 0.234 m). Consequently, this software could make an important contribution to basic research via position determination and the associated differentiation of individuals, and could be relevant in a long-term application for monitoring animal welfare in zoos.

Computational model for the dynamic aspects of sound processing in the auditory midbrain

2001 ◽  
Vol 38-40 ◽  
pp. 1127-1134 ◽  
Author(s):  
Alla Borisyuk ◽  
Malcolm N. Semple ◽  
John Rinzel
Keyword(s):  
Computational Model ◽  
Auditory Midbrain ◽  
Sound Processing

Sound Localization in Auditory Midbrain

2013 ◽  
Vol 21 (6) ◽  
pp. 1028-1033
Author(s):  
Huixian MEI ◽  
Zhijin ZHOU ◽  
Qicai CHEN
Keyword(s):  
Sound Localization ◽  
Auditory Midbrain
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