Brain Dynamics Sustaining Rapid Rule Extraction from Speech

Abstract

Abstract■ Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (20-40 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (4-8 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions. ■

Words and possible words in early language acquisition

“…Namely, assuming that the statistical computations needed in order to check HF part-words against the statistical information available have a fixed cost, the difference may indicate that the identification of possible words after exposure to a segmented stream is a relatively fast process with respect to those statistical computations, thus inducing low looking times for rule-words in Experiment 1, whereas the identification of items not consistent with the familiarization after exposure to a continuous stream (hence, only possible by means of statistical computation), involves additional cognitive efforts. Indeed, in adults the identification of possible words after exposure to a segmented stream is a very rapid process, requiring at most 2 min of familiarization, whereas the consolidation of the statistical information required to identify the actual strings appearing in the stream requires much longer exposure (Bonatti, 2008;De Diego-Balaguer et al, 2011;Endress & Bonatti, 2007;Peña et al, 2002). Further research is needed to explore the plausibility of this interpretation.…”

“…Words and possible words may be acquired by different learning strategies that respond to different aspects and different doses of the available experience. Recent adult neuroimaging evidence supports this conclusion, suggesting that the circuits involved in the projection of lexical rules and in the acquisition of lexical elements are different (De Diego Balaguer, Toro, Rodriguez-Fornells, & Bachoud-Levi, 2007;De Diego-Balaguer, Fuentemilla, & Rodriguez-Fornells, 2011;Mueller, Bahlmann, & Friederici, 2008).…”

BLISS: an Artificial Language for Learnability Studies

“…The relation between function and content words have been of interest to cognitive neuroscientists [14]. The grammar also contains a recursive construction, which might be used in experiments to investigate the effect of hierarchical structures in language processing [16,17].…”

“…It contains function words, inflectional suffixes, and some embedding structure. These grammatical features were introduced to enable experiments to investigate the ability for abstract pattern acquisition [13,6], the special role of function words [14], the role of suffixes [15], and especially hierarchical structures [16,17] in humans.…”

Emergence in the central nervous system

“…According to de Diego-Balaguer et al 2011, data indicate that there are two major strategies, found in good and poor learners. The former infer rules from the data, while the latter primarily use memorization of specific examples.…”