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The lateralization of neuronal processing underpinning hearing, speech, language, and music is widely studied, vigorously debated, and still not understood in a satisfactory manner. One set of hypotheses focuses on the temporal structure of perceptual experience and links auditory cortex asymmetries to underlying differences in neural populations with differential temporal sensitivity (e.g., ideas advanced by Zatorre et al. (2002) and Poeppel (2003). The Asymmetric Sampling in Time theory (AST) (Poeppel, 2003), builds on cytoarchitectonic differences between auditory cortices and predicts that modulation frequencies within the range of, roughly, the syllable rate, are more accurately tracked by the right hemisphere. To date, this conjecture is reasonably well supported, since – while there is some heterogeneity in the reported findings – the predicted asymmetrical entrainment has been observed in various experimental protocols. Here, we show that under specific processing demands, the rightward dominance disappears. We propose an enriched and modified version of the asymmetric sampling hypothesis in the context of speech. Recent work (Rimmele et al., 2018b) proposes two different mechanisms to underlie the auditory tracking of the speech envelope: one derived from the intrinsic oscillatory properties of auditory regions; the other induced by top-down signals coming from other non-auditory regions of the brain. We propose that under non-speech listening conditions, the intrinsic auditory mechanism dominates and thus, in line with AST, entrainment is rightward lateralized, as is widely observed. However, (i) depending on individual brain structural/functional differences, and/or (ii) in the context of specific speech listening conditions, the relative weight of the top-down mechanism can increase. In this scenario, the typically observed auditory sampling asymmetry (and its rightward dominance) diminishes or vanishes.
The ability to extract regularities from the environment is arguably an adaptive characteristic of intelligent systems. In the context of speech, statistical learning is thought to be an important mechanism for language acquisition. By considering individual differences in speech auditory-motor synchronization, an independent component analysis of fMRI data revealed that the neural substrates of statistical word form learning are not fully shared across individuals. While a network of auditory and superior pre/motor regions is universally activated in the process of learning, a fronto-parietal network is instead additionally and selectively engaged by some individuals, boosting their performance. Furthermore, interfering with the use of this network via articulatory suppression (producing irrelevant speech during learning) normalizes performance across the entire sample. Our work provides novel insights on language-related statistical learning and reconciles previous contrasting findings, while highlighting the need to factor in fundamental individual differences for a precise characterization of cognitive phenomena.