Auditory Cortical Plasticity in Learning to Discriminate Modulation Rate

Wassenhove, Virginie van; Nagarajan, Srikantan S.

doi:10.1523/jneurosci.4844-06.2007

Cited by 79 publications

(69 citation statements)

References 49 publications

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“…Other studies demonstrated growing evidence that the adult auditory cortex is a dynamic and adaptive processing center. This has been shown in auditory perceptual learning studies, in which long-lasting neuronal changes were observed in the auditory cortex of animals [45,46] and human beings [47,48] after intensive auditory training.…”

Section: Advances In Clinical Audiologymentioning

confidence: 52%

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Suppression of Otoacoustic Emissions Evoked by White Noise and Speech Stimuli

Andrade¹,

Peixoto²,

Carnaúba³

et al. 2017

Advances in Clinical Audiology

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Introduction: Suppressing otoacoustic emissions is one of the objectives, noninvasive methods that can be used to assess the eferent auditory system. When the ascending reticular activating system is stimulated, the cortex becomes more alert. The system reacts beter to an important stimulus than an unimportant one.Objective: Assess the efect of suppressing otoacoustic emissions by transitory stimulus in the presence of diferent auditory stimuli in normal listeners. Methods:This cross-sectional, observational analytical study. The sample was composed of eight participants. The following procedures were adopted: recording otoacoustic emissions, suppression with white noise, suppression with white noise and pure tone, auditory training, new recording of suppression with white noise and pure tone, suppression using a speech patern, suppression using a reversed speech patern, suppression using familiar speech, and suppression using reversed familiar speech and suppression singing "happy birthday" in a familiar voice.Results: There was a signiicant diference between the otoacoustic emission values, mainly at frequencies of 1000 and 1500 Hz. Conclusion:Individuals submited to the efects of suppression exhibit more efective results at frequencies of 1000 and 1500 Hz. Furthermore, it was found that the eferent activity of the auditory system is more eicient when it involves the use of the speech spectrum.

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Section: Advances In Clinical Audiologymentioning

confidence: 52%

“…Furthermore, postraining results were not statistically signiicant, possibly due to the short duration. Data in the literature suggest the need for more robust training that can guarantee beter learning on the test, in order to be able to observe diferences [34,[45][46][47][48].…”

Section: Personal Experience Regarding the Present Studymentioning

confidence: 99%

Suppression of Otoacoustic Emissions Evoked by White Noise and Speech Stimuli

Andrade¹,

Peixoto²,

Carnaúba³

et al. 2017

Advances in Clinical Audiology

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“…Data from humans indicate no perceptual generalization and knowledge transfer across sounds from different perceptual classes and, therefore, no performance benefit in discrimination when switching the sounds between the classes in a discrimination task (3,5,20,27). This interpretation explains why we did not see a beneficial effect when switching from the easy PT to the hard AM discrimination task (Fig.…”

Section: Discussionmentioning

confidence: 73%

“…1A). Because the stimulus classes in the two tasks were different, human studies suggest that the benefit (hard-to-easy effect) was not based on knowledge of or generalization across stimuli (3,5,20,27) but rather was based on implicitly learned information integration (30,31). Integration of information about the stimuli, the procedural context, and the acquired cognitive skills in the shuttle-box seems to be the key for understanding the curves of discrimination performance of our mice in Fig.…”

Section: Discussionmentioning

confidence: 89%

“…The shuttle-box seems to be the appropriate learning apparatus because it has been used successfully in simple learning and stimulus detection tasks in mice (12-15) and in complex auditory discrimination and memory tasks in another rodent species, the Mongolian gerbil (7,8,(16)(17)(18)(19). Hence, we designed our present study (i) to test the usefulness of the shuttle-box discrimination learning for simple and complex auditory learning tasks in mice; (ii) to investigate complex auditory learning and discrimination performance in mice to see whether mouse data may be generalized, at least to gerbils; and (iii) to test for stimulus generalization and knowledge transfer across different stimulus classes, experiments that have not been done in the auditory domain in mammals other than humans (3,20).A foot shock-motivated go/no-go shuttle-box paradigm was used to train mice for discrimination either of two pure tones of different frequencies (PT) or two different modulation frequencies of an amplitude-modulated tone (AM). The carrier frequency of the AM was either the same as one of the frequencies or different from both of the frequencies used in the PT discrimination task.…”

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confidence: 99%

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Auditory discrimination learning and knowledge transfer in mice depends on task difficulty

Kurt

Ehret

2010

Proc. Natl. Acad. Sci. U.S.A.

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Mice reproduce interesting effects in auditory discrimination learning and knowledge transfer discussed in human studies: (i) the advantage in the transfer from a hard to an easy task by benefits from transfer of procedural knowledge and information-integration learning, and (ii) the disadvantage in the transfer from easy to hard tasks by inability to generalize across perceptually different classes of stimuli together with initially unsuccessful attempts to transfer cognitive skills from one task to the other. House mice (NMRI strain) were trained in a shuttle-box stimulus discrimination task. They had to discriminate either between two pure tones of different frequencies (PT) or between two different modulation frequencies of an amplitude-modulated tone (AM). Then transfer of knowledge between these two tasks was tested. Mice rapidly learned PT discrimination within two to three training sessions (easy task). AM discrimination learning took longer and did not reach the high performance level of PT discrimination (hard task). No knowledge transfer was detected in animals first trained with the easy (PT) followed by the hard (AM) discrimination task. Mice benefited, however, from knowledge transfer when the AM discrimination was followed by the PT discrimination. When the task changed, confusion of conditioned stimuli occurred if the carrier frequency of the AM was the same as one of the frequencies in the PT task. These results show a hard-to-easy effect when possible knowledge transfer is tested between qualitatively different stimulus classes. The data establish mice as promising animal model for research on genetics of auditory perception and learning.cognitive skill learning | go/no-go paradigm | hard-to-easy effect | shuttlebox | stimulus generalization C omplex forms of auditory learning, such as generalization of stimuli within and across physical categories or transfer of knowledge from one stimulus discrimination task to another, are known from humans (1-6) but rarely have been investigated in other mammals (5,7,8). Research in mammalian models is important, however, for an in-depth understanding of neural mechanisms and the genetics of learning abilities and performances. The mouse (Mus musculus), with its great potential for studying genetic effects on auditory perception, learning, and motor performance, is an ideal candidate species for investigations of auditory learning, because in normal-hearing mice many hearing abilities and functions of processing sounds in the auditory system are already known (9-11). What is missing is an automated and reliable learning paradigm for mice that can be adapted to a variety of learning tasks (e.g., detection, discrimination, generalization, transfer learning), showing that learning rules derived from human studies apply to mice. The shuttle-box seems to be the appropriate learning apparatus because it has been used successfully in simple learning and stimulus detection tasks in mice (12-15) and in complex auditory discrimination and memory tasks in another rode...

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Perceptual Learning

Green

Banai

Lü

et al. 2018

Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience

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Perceptual learning refers to a long‐term change in the ability to extract perceptual information from the environment that arises via experience or practice. In this chapter, we first explore many examples of perceptual learning in relatively simple as well as in more complex tasks. Furthermore, we do so across sensory modalities (vision, audition, touch, taste, smell) with the goal of highlighting the commonalities seen in perceptual learning across systems that are typically considered separately. We then consider the most substantial issues in the domain, including the question of learning specificity (i.e., when do improvements on one task transfer to new unpracticed tasks?), the conditions under which learning occurs, the neural basis of perceptual learning, computational models of perceptual learning, and potential real‐world applications of perceptual learning. We conclude with future directions; although the field has clearly made tremendous progress over the past century or more, there remain critical gaps in our knowledge that preclude our ability to fully harness perceptual learning to make a real‐world impact.

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Auditory Cortical Plasticity in Learning to Discriminate Modulation Rate

Cited by 79 publications

References 49 publications

Suppression of Otoacoustic Emissions Evoked by White Noise and Speech Stimuli

Suppression of Otoacoustic Emissions Evoked by White Noise and Speech Stimuli

Auditory discrimination learning and knowledge transfer in mice depends on task difficulty

Perceptual Learning

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