Dataset Information

Cracking the language code: neural mechanisms underlying speech parsing.

ABSTRACT: 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.

SUBMITTER: McNealy K

PROVIDER: S-EPMC3713232 | biostudies-literature | 2006 Jul

REPOSITORIES: biostudies-literature

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Cracking the language code: neural mechanisms underlying speech parsing.

McNealy Kristin K Mazziotta John C JC Dapretto Mirella M

The Journal of neuroscience : the official journal of the Society for Neuroscience 20060701 29

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 reg ...[more]

PMID: 16855090

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Project description:Breathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD). COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI), we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL) medulla (pre-Bötzinger complex) and the caudal VL pons (parafacial group). fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in neurons can contribute to chaos in airflow and reproduces key experimental fMRI findings.

Dataset Information

Cracking the language code: neural mechanisms underlying speech parsing.

Publications

Cracking the language code: neural mechanisms underlying speech parsing.

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