The auditory brainstem is a barometer of rapid auditory learning

Skoe, Erika; Krizman, Jennifer; Spitzer, Emily R.; Kraus, Nina

doi:10.1016/j.neuroscience.2013.03.009

Cited by 75 publications

(71 citation statements)

References 91 publications

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“…At a phenomenological level, the adaptation evident in our data is consistent with the concept of perceptual learning (Skoe et al, 2013;de Souza et al, 2013). Perceptual learning is thought to reflect enhancement of perception due to synaptic plasticity (which follows practice) and hence our data may reflect rapid perceptual learning.…”

Section: Discussionsupporting

confidence: 89%

“…The breakpoint in performance at ϳ60 s is relatively close to the time-scale of long-term adaptation reported in these studies. This time scale is also consistent with recent studies of slowly ramped intensity increments (Simpson and Reiss, 2013;Simpson et al, 2013) and brainstem-mediated "rapid learning" (Skoe et al, 2013), suggesting a common role of long-term adaptation in humans. Ulanovsky et al's (2004) study in cats also demonstrated that cortical neurons adapt more quickly to high-probability sounds than to low-probability sounds, and that multiple timescales of "stimulus-specific" adaptation occurred concurrently.…”

Section: Neural Mechanismssupporting

confidence: 91%

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Selective Adaptation to “Oddball” Sounds by the Human Auditory System

et al. 2014

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Adaptation to both common and rare sounds has been independently reported in neurophysiological studies using probabilistic stimulus paradigms in small mammals. However, the apparent sensitivity of the mammalian auditory system to the statistics of incoming sound has not yet been generalized to task-related human auditory perception. Here, we show that human listeners selectively adapt to novel sounds within scenes unfolding over minutes. Listeners' performance in an auditory discrimination task remains steady for the most common elements within the scene but, after the first minute, performance improves for distinct and rare (oddball) sound elements, at the expense of rare sounds that are relatively less distinct. Our data provide the first evidence of enhanced coding of oddball sounds in a human auditory discrimination task and suggest the existence of an adaptive mechanism that tracks the long-term statistics of sounds and deploys coding resources accordingly.

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Section: Discussionsupporting

confidence: 89%

Section: Neural Mechanismssupporting

confidence: 91%

Selective Adaptation to “Oddball” Sounds by the Human Auditory System

et al. 2014

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“…Although these examples suggest that prior experience bootstraps future learning, the past can also impose constraints on learning, making it difficult to learn new sound contrasts, muscle movements, or rules that conflict with ingrained knowledge (Bialystok, Craik, Klein, & Viswanathan, 2004;Maye, Werker, & Gerken, 2002;Tahta, Wood, & Loewenthal, 1981). Here we show how this dependence on the past percolates into even the most basic neural mechanisms (Skoe, Krizman, Spitzer, & Kraus, 2013;Wen, Wang, Dean, & Delgutte, 2009;Dean, Harper, & McAlpine, 2005; Perez-Gonzalez, Malmierca, & Covey, 2005), like statistical learning.…”

Section: Introductionmentioning

confidence: 70%

“…In support of this proposition, neurons across the central auditory pathway, from the brainstem to the cortex, adjust their firing patterns based on the statistical properties of the soundscape (Antunes, Nelken, Covey, & Malmierca, et al, 2005;Perez-Gonzalez et al, 2005;Ulanovsky, Las, Farkas, & Nelken, 2004;Ulanovsky, Las, & Nelken, 2003). Moreover, we have recently shown that behavioral outcomes of statistical learning can be predicted from the brainstemʼs ability to lock onto patterns, suggesting that the auditory brainstem is part of the neural circuitry mediating rapid, online statistical learning (Skoe et al, 2013). We now address whether the brainstemʼs online sensitivity to sound statistics is absolute or historically biased.…”

Section: Introductionmentioning

confidence: 97%

Prior Experience Biases Subcortical Sensitivity to Sound Patterns

Skoe¹,

Krizman²,

Spitzer³

et al. 2015

Journal of Cognitive Neuroscience

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To make sense of our ever-changing world, our brains search out patterns. This drive can be so strong that the brain imposes patterns when there are none. The opposite can also occur: The brain can overlook patterns because they do not conform to expectations. In this study, we examined this neural sensitivity to patterns within the auditory brainstem, an evolutionarily ancient part of the brain that can be fine-tuned by experience and is integral to an array of cognitive functions. We have recently shown that this auditory hub is sensitive to patterns embedded within a novel sound stream, and we established a link between neural sensitivity and behavioral indices of learning [Skoe, E., Krizman, J., Spitzer, E., & Kraus, N. The auditory brainstem is a barometer of rapid auditory learning. Neuroscience, 243, 104-114, 2013]. We now ask whether this sensitivity to stimulus statistics is biased by prior experience and the expectations arising from this experience. To address this question, we recorded complex auditory brainstem responses (cABRs) to two patterned sound sequences formed from a set of eight repeating tones. For both patterned sequences, the eight tones were presented such that the transitional probability (TP) between neighboring tones was either 33% (low predictability) or 100% (high predictability). Although both sequences were novel to the healthy young adult listener and had similar TP distributions, one was perceived to be more musical than the other. For the more musical sequence, participants performed above chance when tested on their recognition of the most predictable two-tone combinations within the sequence (TP of 100%); in this case, the cABR differed from a baseline condition where the sound sequence had no predictable structure. In contrast, for the less musical sequence, learning was at chance, suggesting that listeners were "deaf" to the highly predictable repeating two-tone combinations in the sequence. For this condition, the cABR also did not differ from baseline. From this, we posit that the brainstem acts as a Bayesian sound processor, such that it factors in prior knowledge about the environment to index the probability of particular events within ever-changing sensory conditions.

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“…Although auditory perceptual learning in humans occurs across time-scales ranging from minutes (Hawkey et al, 2004;Alain et al, 2007;Skoe et al, 2013) to many hours (e.g., Leek and Watson, 1984;Ortiz and Wright, 2009;Banai et al, 2010) of practice, the perceptual learning of speech has been most commonly investigated with brief training regimens (e.g., Dupoux and Green, 1997;Davis et al, 2005;Bradlow and Bent, 2008). This focus on the outcomes of short-term experience implies a tacit assumption that there is little to gain (for example, in terms of generalization) from prolonged practice.…”

Section: Introductionmentioning

confidence: 99%

The effects of training length on the perceptual learning of time-compressed speech and its generalization

Banai

Lavner

2014

The Journal of the Acoustical Society of America

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Brief exposure to time-compressed speech yields both learning and generalization. Whether such learning continues over the course of multi-session training and if so whether it is more or less specific than exposure-induced learning is not clear, because the outcomes of intensive practice with time-compressed speech have rarely been reported. The goal here was to determine whether prolonged training on time-compressed speech yields additional learning and generalization beyond that induced by brief exposure. Listeners practiced the semantic verification of time-compressed sentences for one or three training sessions. Identification of trained and untrained tokens was subsequently compared between listeners who trained for one or three sessions, listeners who were briefly exposed to 20 time-compressed sentences and naive listeners. Trained listeners outperformed the other groups of listeners on the trained condition, but only the group that was trained for three sessions outperformed the other groups when tested with untrained tokens. These findings suggest that although learning of distorted speech can occur rapidly, more stable learning and generalization might be achieved with longer, multi-session practice. It is suggested that the findings are consistent with the framework proposed by the Reverse Hierarchy Theory of perceptual learning.

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The auditory brainstem is a barometer of rapid auditory learning

Cited by 75 publications

References 91 publications

Selective Adaptation to “Oddball” Sounds by the Human Auditory System

Selective Adaptation to “Oddball” Sounds by the Human Auditory System

Prior Experience Biases Subcortical Sensitivity to Sound Patterns

The effects of training length on the perceptual learning of time-compressed speech and its generalization

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