The effect of regular rhythm on the perception of linguistic and non-linguistic auditory input.

Regular distribution of auditory stimuli over time can facilitate perception and attention. However, such effects have to date only been observed in separate studies using either linguistic or non-linguistic materials. This has made it difficult to compare the effects of rhythmic regularity on attention across domains.

An evolutionary account of intermodality differences in statistical learning.

The cognitive mechanisms underlying statistical learning are engaged for the purposes of speech processing and language acquisition. However, these mechanisms are shared by a wide variety of species that do not possess the language faculty. Moreover, statistical learning operates across domains, including nonlinguistic material.

The role of metacognition in recognition of the content of statistical learning.

Despite theoretical debate on the extent to which statistical learning is incidental or modulated by explicit instructions and conscious awareness of the content of statistical learning, no study has ever investigated the metacognition of statistical learning. We used an artificial language-learning paradigm and a segmentation task that required splitting a continuous stream of syllables into discrete recurrent constituents. During this task, statistical learning potentially produces knowledge of discrete constituents as well as about statistical regularities that are embodied in familiarization input.

Neural bases of learning and recognition of statistical regularities.

Statistical learning is a set of cognitive mechanisms allowing for extracting regularities from the environment and segmenting continuous sensory input into discrete units. The current study used functional magnetic resonance imaging (fMRI) (N = 25) in conjunction with an artificial language learning paradigm to provide new insight into the neural mechanisms of statistical learning, considering both the online process of extracting statistical regularities and the subsequent offline recognition of learned patterns. Notably, prior fMRI studies on statistical learning have not contrasted neural activation during the learning and recognition experimental phases.

Electrophysiology of statistical learning: Exploring the online learning process and offline learning product.

A continuous stream of syllables is segmented into discrete constituents based on the transitional probabilities (TPs) between adjacent syllables by means of statistical learning. However, we still do not know whether people attend to high TPs between frequently co-occurring syllables and cluster them together as parts of the discrete constituents or attend to low TPs aligned with the edges between the constituents and extract them as whole units. Earlier studies on TP-based segmentation also have not distinguished between the segmentation process (how people segment continuous speech) and the learning product (what is learnt by means of statistical learning mechanisms).

Speech Rhythm Convergence as a Social Coalition Signal.

Patterns of nonverbal and verbal behavior of interlocutors become more similar as communication progresses. Rhythm entrainment promotes prosocial behavior and signals social bonding and cooperation. Yet, it is unknown if the convergence of rhythm in human speech is perceived and is used to make pragmatic inferences regarding the cooperative urge of the interactors.

Regularity in speech rhythm as a social coalition signal.

Regular rhythm facilitates audiomotor entrainment and synchronization in motor behavior and vocalizations between individuals. As rhythm entrainment between interacting agents is correlated with higher levels of cooperation and prosocial affiliative behavior, humans can potentially map regular speech rhythm onto higher cooperation and friendliness between interacting individuals. We tested this hypothesis at two rhythmic levels: pulse (recurrent acoustic events) and meter (hierarchical structuring of pulses based on their relative salience).