Literature DB >> 23354998

Prior experience with negative spectral correlations promotes information integration during auditory category learning.

Mathias Scharinger1, Molly J Henry, Jonas Obleser.   

Abstract

Complex sounds vary along a number of acoustic dimensions. These dimensions may exhibit correlations that are familiar to listeners due to their frequent occurrence in natural sounds-namely, speech. However, the precise mechanisms that enable the integration of these dimensions are not well understood. In this study, we examined the categorization of novel auditory stimuli that differed in the correlations of their acoustic dimensions, using decision bound theory. Decision bound theory assumes that stimuli are categorized on the basis of either a single dimension (rule based) or the combination of more than one dimension (information integration) and provides tools for assessing successful integration across multiple acoustic dimensions. In two experiments, we manipulated the stimulus distributions such that in Experiment 1, optimal categorization could be accomplished by either a rule-based or an information integration strategy, while in Experiment 2, optimal categorization was possible only by using an information integration strategy. In both experiments, the pattern of results demonstrated that unidimensional strategies were strongly preferred. Listeners focused on the acoustic dimension most closely related to pitch, suggesting that pitch-based categorization was given preference over timbre-based categorization. Importantly, in Experiment 2, listeners also relied on a two-dimensional information integration strategy, if there was immediate feedback. Furthermore, this strategy was used more often for distributions defined by a negative spectral correlation between stimulus dimensions, as compared with distributions with a positive correlation. These results suggest that prior experience with such correlations might shape short-term auditory category learning.

Mesh:

Year:  2013        PMID: 23354998     DOI: 10.3758/s13421-013-0294-9

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  47 in total

1.  Learning nonlinearly separable categories by inference and classification.

Authors:  Takashi Yamauchi; Bradley C Love; Arthur B Markman
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2002-05       Impact factor: 3.051

2.  Generalizing a neuropsychological model of visual categorization to auditory categorization of vowels.

Authors:  W Todd Maddox; Michelle R Molis; Randy L Diehl
Journal:  Percept Psychophys       Date:  2002-05

3.  Category number impacts rule-based but not information-integration category learning: further evidence for dissociable category-learning systems.

Authors:  W Todd Maddox; J Vincent Filoteo; Kelli D Hejl; A David Ing
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2004-01       Impact factor: 3.051

4.  The role of similarity in the development of categorization.

Authors:  Vladimir M. Sloutsky
Journal:  Trends Cogn Sci       Date:  2003-06       Impact factor: 20.229

Review 5.  The neurobiology of category learning.

Authors:  F Gregory Ashby; Brian J Spiering
Journal:  Behav Cogn Neurosci Rev       Date:  2004-06

6.  Dimensions in data: testing psychological models using state-trace analysis.

Authors:  Ben R Newell; John C Dunn
Journal:  Trends Cogn Sci       Date:  2008-07-05       Impact factor: 20.229

7.  Integrality in the perception of tongue root position and voice quality in vowels.

Authors:  J Kingston; N A Macmillan; L W Dickey; R Thorburn; C Bartels
Journal:  J Acoust Soc Am       Date:  1997-03       Impact factor: 1.840

8.  Integrality of nasalization and F1 in vowels in isolation and before oral and nasal consonants: a detection-theoretic application of the Garner paradigm.

Authors:  J Kingston; N A Macmillan
Journal:  J Acoust Soc Am       Date:  1995-02       Impact factor: 1.840

9.  Working memory does not dissociate between different perceptual categorization tasks.

Authors:  Stephan Lewandowsky; Lee-Xieng Yang; Ben R Newell; Michael L Kalish
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2012-07       Impact factor: 3.051

10.  A neuropsychological theory of multiple systems in category learning.

Authors:  F G Ashby; L A Alfonso-Reese; A U Turken; E M Waldron
Journal:  Psychol Rev       Date:  1998-07       Impact factor: 8.934

View more
  7 in total

1.  Perceptual dimensions influence auditory category learning.

Authors:  Casey L Roark; Lori L Holt
Journal:  Atten Percept Psychophys       Date:  2019-05       Impact factor: 2.199

2.  Auditory information-integration category learning in young children and adults.

Authors:  Casey L Roark; Lori L Holt
Journal:  J Exp Child Psychol       Date:  2019-08-17

3.  Comparing perceptual category learning across modalities in the same individuals.

Authors:  Casey L Roark; Giorgio Paulon; Abhra Sarkar; Bharath Chandrasekaran
Journal:  Psychon Bull Rev       Date:  2021-02-02

4.  Simultaneous EEG-fMRI brain signatures of auditory cue utilization.

Authors:  Mathias Scharinger; Björn Herrmann; Till Nierhaus; Jonas Obleser
Journal:  Front Neurosci       Date:  2014-06-04       Impact factor: 4.677

5.  Do Infants Really Learn Phonetic Categories?

Authors:  Naomi H Feldman; Sharon Goldwater; Emmanuel Dupoux; Thomas Schatz
Journal:  Open Mind (Camb)       Date:  2021-11-01

Review 6.  How learning to abstract shapes neural sound representations.

Authors:  Anke Ley; Jean Vroomen; Elia Formisano
Journal:  Front Neurosci       Date:  2014-06-03       Impact factor: 4.677

7.  Characterizing the impact of category uncertainty on human auditory categorization behavior.

Authors:  Adam M Gifford; Yale E Cohen; Alan A Stocker
Journal:  PLoS Comput Biol       Date:  2014-07-17       Impact factor: 4.475

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.