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      Brain dynamics that correlate with effects of learning on auditory distance perception

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          Abstract

          Accuracy in auditory distance perception can improve with practice and varies for sounds differing in familiarity. Here, listeners were trained to judge the distances of English, Bengali, and backwards speech sources pre-recorded at near (2-m) and far (30-m) distances. Listeners' accuracy was tested before and after training. Improvements from pre-test to post-test were greater for forward speech, demonstrating a learning advantage for forward speech sounds. Independent component (IC) processes identified in electroencephalographic (EEG) data collected during pre- and post-testing revealed three clusters of ICs across subjects with stimulus-locked spectral perturbations related to learning and accuracy. One cluster exhibited a transient stimulus-locked increase in 4–8 Hz power (theta event-related synchronization; ERS) that was smaller after training and largest for backwards speech. For a left temporal cluster, 8–12 Hz decreases in power (alpha event-related desynchronization; ERD) were greatest for English speech and less prominent after training. In contrast, a cluster of IC processes centered at or near anterior portions of the medial frontal cortex showed learning-related enhancement of sustained increases in 10–16 Hz power (upper-alpha/low-beta ERS). The degree of this enhancement was positively correlated with the degree of behavioral improvements. Results suggest that neural dynamics in non-auditory cortical areas support distance judgments. Further, frontal cortical networks associated with attentional and/or working memory processes appear to play a role in perceptual learning for source distance.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Rhythms of the Brain

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              Mining event-related brain dynamics.

              This article provides a new, more comprehensive view of event-related brain dynamics founded on an information-based approach to modeling electroencephalographic (EEG) dynamics. Most EEG research focuses either on peaks 'evoked' in average event-related potentials (ERPs) or on changes 'induced' in the EEG power spectrum by experimental events. Although these measures are nearly complementary, they do not fully model the event-related dynamics in the data, and cannot isolate the signals of the contributing cortical areas. We propose that many ERPs and other EEG features are better viewed as time/frequency perturbations of underlying field potential processes. The new approach combines independent component analysis (ICA), time/frequency analysis, and trial-by-trial visualization that measures EEG source dynamics without requiring an explicit head model.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                09 December 2014
                2014
                : 8
                : 396
                Affiliations
                [1] 1711th Human Performance Wing, U. S. Air Force Research Laboratory Wright-Patterson Air Force Base, OH, USA
                [2] 2Department of Psychology, University at Buffalo, The State University of New York Buffalo, NY, USA
                [3] 3Biological Psychology and Neuroergonomics, Berlin Institute of Technology Berlin, Germany
                [4] 4Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego San Diego, CA, USA
                Author notes

                Edited by: Guillaume Andeol, Institut de Recherche Biomédicale des Armées, France

                Reviewed by: Ross K. Maddox, University of Washington, USA; Jyrki Ahveninen, Massachusetts General Hospital, USA

                *Correspondence: Matthew G. Wisniewski, 711th Human Performance Wing, U.S. Air Force Research Laboratory, Building 441, Area B, Wright Patterson Air Force Base, OH 45433, USA e-mail: matt.g.wisniewski@ 123456gmail.com

                This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Neuroscience.

                Article
                10.3389/fnins.2014.00396
                4260497
                25538550
                d562e2ab-83dc-4da7-9f02-c7efe04f6072
                Copyright © 2014 Wisniewski, Mercado, Church, Gramann and Makeig.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 May 2014
                : 18 November 2014
                Page count
                Figures: 8, Tables: 1, Equations: 0, References: 70, Pages: 15, Words: 11909
                Categories
                Psychology
                Original Research Article

                Neurosciences
                electroencephalography (eeg),perceptual learning,familiarity,independent component analysis (ica),ranging,event-related spectral perturbation (ersp)

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