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Perceiving sequential dependencies in auditory streams.

ABSTRACT: This study examined the ability of human listeners to detect the presence and judge the strength of a statistical dependency among the elements comprising sequences of sounds. The statistical dependency was imposed by specifying transition matrices that determined the likelihood of occurrence of the sound elements. Markov chains were constructed from these transition matrices having states that were pure tones/noise bursts that varied along the stimulus dimensions of frequency and/or interaural time difference. Listeners reliably detected the presence of a statistical dependency in sequences of sounds varying along these stimulus dimensions. Furthermore, listeners were able to discriminate the relative strength of the dependency in pairs of successive sound sequences. Random variation along an irrelevant stimulus dimension had small but significant adverse effects on performance. A much greater decrement in performance was found when the sound sequences were concurrent. Likelihood ratios were computed based on the transition matrices to specify Ideal Observer performance for the experimental conditions. Preliminary modeling efforts were made based on degradations of Ideal Observer performance intended to represent human observer limitations. This experimental approach appears to be useful for examining auditory "stream" formation and maintenance over time based on the predictability of the constituent sound elements.

SUBMITTER: Kidd G

PROVIDER: S-EPMC3745531 | biostudies-other | 2013 Aug

REPOSITORIES: biostudies-other

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Project description:The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M?=?22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

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Perceiving sequential dependencies in auditory streams.

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