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      Comparison of auditory spatial bisection and minimum audible angle in front, lateral, and back space

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          Abstract

          Although vision is important for calibrating auditory spatial perception, it only provides information about frontal sound sources. Previous studies of blind and sighted people support the idea that azimuthal spatial bisection in frontal space requires visual calibration, while detection of a change in azimuth (minimum audible angle, MAA) does not. The influence of vision on the ability to map frontal, lateral and back space has not been investigated. Performance in spatial bisection and MAA tasks was assessed for normally sighted blindfolded subjects using bursts of white noise presented frontally, laterally, or from the back relative to the subjects. Thresholds for both tasks were similar in frontal space, lower for the MAA task than for the bisection task in back space, and higher for the MAA task in lateral space. Two interpretations of the results are discussed, one in terms of visual calibration and the use of internal representations of source location and the other based on comparison of the magnitude or direction of change of the available binaural cues. That bisection thresholds were increased in back space relative to front space, where visual calibration information is unavailable, suggests that an internal representation of source location was used for the bisection task.

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          Most cited references27

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          Sound localization by human listeners.

          In keeping with our promise earlier in this review, we summarize here the process by which we believe spatial cues are used for localizing a sound source in a free-field listening situation. We believe it entails two parallel processes: 1. The azimuth of the source is determined using differences in interaural time or interaural intensity, whichever is present. Wightman and colleagues (1989) believe the low-frequency temporal information is dominant if both are present. 2. The elevation of the source is determined from spectral shape cues. The received sound spectrum, as modified by the pinna, is in effect compared with a stored set of directional transfer functions. These are actually the spectra of a nearly flat source heard at various elevations. The elevation that corresponds to the best-matching transfer function is selected as the locus of the sound. Pinnae are similar enough between people that certain general rules (e.g. Blauert's boosted bands or Butler's covert peaks) can describe this process. Head motion is probably not a critical part of the localization process, except in cases where time permits a very detailed assessment of location, in which case one tries to localize the source by turning the head toward the putative location. Sound localization is only moderately more precise when the listener points directly toward the source. The process is not analogous to localizing a visual source on the fovea of the retina. Thus, head motion provides only a moderate increase in localization accuracy. Finally, current evidence does not support the view that auditory motion perception is anything more than detection of changes in static location over time.
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            On the Minimum Audible Angle

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              Plasticity in the developing brain: implications for rehabilitation.

              Neuronal plasticity allows the central nervous system to learn skills and remember information, to reorganize neuronal networks in response to environmental stimulation, and to recover from brain and spinal cord injuries. Neuronal plasticity is enhanced in the developing brain and it is usually adaptive and beneficial but can also be maladaptive and responsible for neurological disorders in some situations. Basic mechanisms that are involved in plasticity include neurogenesis, programmed cell death, and activity-dependent synaptic plasticity. Repetitive stimulation of synapses can cause long-term potentiation or long-term depression of neurotransmission. These changes are associated with physical changes in dendritic spines and neuronal circuits. Overproduction of synapses during postnatal development in children contributes to enhanced plasticity by providing an excess of synapses that are pruned during early adolescence. Clinical examples of adaptive neuronal plasticity include reorganization of cortical maps of the fingers in response to practice playing a stringed instrument and constraint-induced movement therapy to improve hemiparesis caused by stroke or cerebral palsy. These forms of plasticity are associated with structural and functional changes in the brain that can be detected with magnetic resonance imaging, positron emission tomography, or transcranial magnetic stimulation (TMS). TMS and other forms of brain stimulation are also being used experimentally to enhance brain plasticity and recovery of function. Plasticity is also influenced by genetic factors such as mutations in brain-derived neuronal growth factor. Understanding brain plasticity provides a basis for developing better therapies to improve outcome from acquired brain injuries. (c) 2009 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                elenaaggiusvella@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 April 2020
                14 April 2020
                2020
                : 10
                : 6279
                Affiliations
                [1 ]ISNI 0000 0004 1764 2907, GRID grid.25786.3e, Unit for Visually Impaired People (U-VIP), Center for Human Technologies, Fondazione Istituto Italiano di Tecnologia, ; Genoa, Italy
                [2 ]ISNI 0000 0001 2151 3065, GRID grid.5606.5, Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS) Department, , University of Genoa, ; Genoa, Italy
                [3 ]ISNI 0000 0001 2299 5510, GRID grid.5115.0, Vision and Eye Research Institute, School of Medicine, , Anglia Ruskin University, ; Cambridge, United Kingdom
                [4 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Psychology, , University of Cambridge, ; Cambridge, United Kingdom
                [5 ]ISNI 0000 0001 2299 5510, GRID grid.5115.0, School of Computing and Information Science, , Anglia Ruskin University, ; Cambridge, United Kingdom
                Author information
                http://orcid.org/0000-0001-8943-7652
                http://orcid.org/0000-0002-5121-7512
                http://orcid.org/0000-0002-7097-4500
                http://orcid.org/0000-0001-7071-0671
                Article
                62983
                10.1038/s41598-020-62983-z
                7156409
                32286362
                0612e5d8-7b5a-46eb-b750-5e6796189cc6
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 October 2018
                : 11 March 2020
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                © The Author(s) 2020

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                perception,human behaviour
                Uncategorized
                perception, human behaviour

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