Cracking the Language Code: Neural Mechanisms Underlying Speech Parsing

Department of Psychiatry and Biobehavioural Sciences, University of California, Los Angeles, Los Ángeles, California, United States
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 08/2006; 26(29):7629-39. DOI: 10.1523/JNEUROSCI.5501-05.2006
Source: PubMed


Word segmentation, detecting word boundaries in continuous speech, is a critical aspect of language learning. Previous research in infants and adults demonstrated that a stream of speech can be readily segmented based solely on the statistical and speech cues afforded by the input. Using functional magnetic resonance imaging (fMRI), the neural substrate of word segmentation was examined on-line as participants listened to three streams of concatenated syllables, containing either statistical regularities alone, statistical regularities and speech cues, or no cues. Despite the participants' inability to explicitly detect differences between the speech streams, neural activity differed significantly across conditions, with left-lateralized signal increases in temporal cortices observed only when participants listened to streams containing statistical regularities, particularly the stream containing speech cues. In a second fMRI study, designed to verify that word segmentation had implicitly taken place, participants listened to trisyllabic combinations that occurred with different frequencies in the streams of speech they just heard ("words," 45 times; "partwords," 15 times; "nonwords," once). Reliably greater activity in left inferior and middle frontal gyri was observed when comparing words with partwords and, to a lesser extent, when comparing partwords with nonwords. Activity in these regions, taken to index the implicit detection of word boundaries, was positively correlated with participants' rapid auditory processing skills. These findings provide a neural signature of on-line word segmentation in the mature brain and an initial model with which to study developmental changes in the neural architecture involved in processing speech cues during language learning.

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    • "A second point in favor of this possibility is that the level of the explicit knowledge produced by statistical learning is typically rather impoverished . Some studies find that performance on explicit recognition measures does not reliably exceed chance (Sanders et al. 2002; McNealy et al. 2006; Turk-Browne et al. 2008), and the upper range of average performance rarely exceeds 70%– 75% accuracy (e.g., Saffran et al. 1996b, 1997, 1999). Even when overall group-level recognition accuracy is relatively high, explicit knowledge often varies considerably between individual participants. "
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    ABSTRACT: Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly.
    Learning &amp Memory 11/2015; 22(11):544-556. DOI:10.1101/lm.037986.114 · 3.66 Impact Factor
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    • "Thus, a faster N400 increase in musicians points to a faster ability to take advantage of the statistical structure of the stream to segment the words. Interestingly, the superior temporal plane seems to be sensitive to the statistical regularities of the input [55] and metabolic activity within this region is positively related to participants' ability to recognize words during the behavioural test of a similar artificial language learning experiment [56]. Importantly, at the structural level, musicians show larger planum temporale than nonmusicians [57], [58]. "
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    ABSTRACT: The musician's brain is considered as a good model of brain plasticity as musical training is known to modify auditory perception and related cortical organization. Here, we show that music-related modifications can also extend beyond motor and auditory processing and generalize (transfer) to speech processing. Previous studies have shown that adults and newborns can segment a continuous stream of linguistic and non-linguistic stimuli based only on probabilities of occurrence between adjacent syllables, tones or timbres. The paradigm classically used in these studies consists of a passive exposure phase followed by a testing phase. By using both behavioural and electrophysiological measures, we recently showed that adult musicians and musically trained children outperform nonmusicians in the test following brief exposure to an artificial sung language. However, the behavioural test does not allow for studying the learning process per se but rather the result of the learning. In the present study, we analyze the electrophysiological learning curves that are the ongoing brain dynamics recorded as the learning is taking place. While musicians show an inverted U shaped learning curve, nonmusicians show a linear learning curve. Analyses of Event-Related Potentials (ERPs) allow for a greater understanding of how and when musical training can improve speech segmentation. These results bring evidence of enhanced neural sensitivity to statistical regularities in musicians and support the hypothesis of positive transfer of training effect from music to sound stream segmentation in general.
    PLoS ONE 07/2014; 9(7):e101340. DOI:10.1371/journal.pone.0101340 · 3.23 Impact Factor
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    • "Because these responses were found for spatial sequences in the visual domain, the authors suggested that these areas, commonly associated with language processing, might in fact mediate a domain-general process involved in coding input entropy . However, in a related study [McNealy et al., 2006], where auditory streams of nonsense syllables were manipulated to study the neural mechanisms underlying online word segmentation, lateral temporal regions exhibited lower activity for random syllable streams than for structured streams consisting of repeated combinations of fixed syllable triplets (in absence of other language cues, such as syllable stress). In this latter study, stimuli were much shorter in duration (less than 300 ms) and there was no explicit task associated with listening. "
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    Human Brain Mapping 04/2014; 35(4). DOI:10.1002/hbm.22238 · 5.97 Impact Factor
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