Syllables in Sync Form a Link: Neural Phase-locking Reflects Word Knowledge during Language Learning

Language is composed of small building blocks, which combine to form larger meaningful structures. To understand language, we must process, track, and concatenate these building blocks into larger linguistic units as speech unfolds over time. An influential idea is that phase-locking of neural oscillations across different levels of linguistic structure provides a mechanism for this process. Building on this framework, the goal of the current study was to determine whether neural phase-locking occurs more robustly to novel linguistic items that are successfully learned and encoded into memory, compared to items that are not learned. Participants listened to a continuous speech stream composed of repeating nonsense words while their EEG was recorded and then performed a recognition test on the component words. Neural phase-locking to individual words during the learning period strongly predicted the strength of subsequent word knowledge, suggesting that neural phase-locking indexes the subjective perception of specific linguistic items during real-time language learning. These findings support neural oscillatory models of language, demonstrating that words that are successfully perceived as functional units are tracked by oscillatory activity at the matching word rate. In contrast, words that are not learned are processed merely as a sequence of unrelated syllables and thus not tracked by corresponding word-rate oscillations

Rapid Statistical Learning Supporting Word Extraction From Continuous Speech.

The identification of words in continuous speech, known as speech segmentation, is a critical early step in language acquisition. This process is partially supported by statistical learning, the ability to extract patterns from the environment. Given that speech segmentation represents a potential bottleneck for language acquisition, patterns in speech may be extracted very rapidly, without extensive exposure. This hypothesis was examined by exposing participants to continuous speech streams composed of novel repeating nonsense words. Learning was measured on-line using a reaction time task. After merely one exposure to an embedded novel word, learners demonstrated significant learning effects, as revealed by faster responses to predictable than to unpredictable syllables. These results demonstrate that learners gained sensitivity to the statistical structure of unfamiliar speech on a very rapid timescale. This ability may play an essential role in early stages of language acquisition, allowing learners to rapidly identify word candidates and break in to an unfamiliar language

Key Success Factors of Innovation in Multinational Agrifood Prospector Companies

The Wageningen Innovation Assessment Tool (WIAT) assesses a company’s drivers and barriers to innovation and benchmarks the critical success and failure factors of its innovation projects with data of agrifood prospector companies around the world. The present paper discusses its application in 12 multinational agrifood prospector companies in the Netherlands and France. It is concluded that WIAT by uncovering the tacit knowledge of the innovation project team creates opportunities for substantial improvement of the innovation process, and that agrifood companies should specifically pay attention to market and product related up-front activities.innovation, assessment tool, agrifood prospector companies, Agribusiness, Agricultural and Food Policy, International Relations/Trade,

The human brain processes syntax in the absence of conscious awareness.

Syntax is the core computational component of language. A longstanding idea about syntactic processing is that it is generally not available to conscious access, operating autonomously and automatically. However, there is little direct neurocognitive evidence on this issue. By measuring event-related potentials while human observers performed a novel cross-modal distraction task, we demonstrated that syntactic violations that were not consciously detected nonetheless produced a characteristic early neural response pattern, and also significantly delayed reaction times to a concurrent task. This early neural response was distinct from later neural activity that was observed only to syntactic violations that were consciously detected. These findings provide direct evidence that the human brain reacts to violations of syntax even when these violations are not consciously detected, indicating that even highly complex computational processes such as syntactic processing can occur outside the narrow window of conscious awareness

Statistical Learning Across Visual and Auditory Modalities

Our ability to learn language is accomplished by using structural patterns found in everyday language. We use these structural patterns in language through a process of Statistical Learning (SL) to implicitly predict sequences in speech and visual input. Our research explored how SL predicts patterns of auditory and visual learning in adults (N = 40; M = 27.1 years) to provide a more complete picture of SL. For the auditory task, participants were tested on whether they learned a novel language that they passively listened to for 6 minutes. Implicit and explicit learning were assessed after the exposure phase. For the visual task, participants were tasked with rapidly indicating a target’s spatial location, which would appear in one of four circles. Reaction time and accuracy were assessed to determine whether implicit and explicit SL occurred. Results demonstrated that implicit SL occurred in both modalities; however, no explicit learning occurred in the visual task and no correlations were found between these tasks. These results hint to an underlying difference in auditory and visual SL. This data may support the hypothesis that SL is modality specific and is not governed by a more general processing capacity. These results provide behavioural data on the role of SL across modalities, which can inform theories of the neurocognitive underpinnings of language and reading acquisition. To better understand the role that SL has on reading and language abilities, future research should look at visual and auditory SL in children with reading and language impairments

Online neural monitoring of statistical learning.

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning

Sleep-based memory processing facilitates grammatical generalization: Evidence from targeted memory reactivation.

Generalization-the ability to abstract regularities from specific examples and apply them to novel instances-is an essential component of language acquisition. Generalization not only depends on exposure to input during wake, but may also improve offline during sleep. Here we examined whether targeted memory reactivation during sleep can influence grammatical generalization. Participants gradually acquired the grammatical rules of an artificial language through an interactive learning procedure. Then, phrases from the language (experimental group) or stimuli from an unrelated task (control group) were covertly presented during an afternoon nap. Compared to control participants, participants re-exposed to the language during sleep showed larger gains in grammatical generalization. Sleep cues produced a bias, not necessarily a pure gain, suggesting that the capacity for memory replay during sleep is limited. We conclude that grammatical generalization was biased by auditory cueing during sleep, and by extension, that sleep likely influences grammatical generalization in general

Rhythmically modulating neural entrainment during exposure to regularities influences statistical learning

The ability to discover regularities in the environment, such as syllable patterns in speech, is known as statistical learning. Previous studies have shown that statistical learning is accompanied by neural entrainment, in which neural activity temporally aligns with repeating patterns over time. However, it is unclear whether these rhythmic neural dynamics play a functional role in statistical learning, or whether they largely reflect the downstream consequences of learning, such as the enhanced perception of learned words in speech. To better understand this issue, we manipulated participants’ neural entrainment during statistical learning using continuous rhythmic visual stimulation. Participants were exposed to a speech stream of repeating nonsense words while viewing either (1) a visual stimulus with a “congruent” rhythm that aligned with the word structure, (2) a visual stimulus with an incongruent rhythm, or (3) a static visual stimulus. Statistical learning was subsequently measured using both an explicit and implicit test. Participants in the congruent condition showed a significant increase in neural entrainment over auditory regions at the relevant word frequency, over and above effects of passive volume conduction, indicating that visual stimulation successfully altered neural entrainment within relevant neural substrates. Critically, during the subsequent implicit test, participants in the congruent condition showed an enhanced ability to predict upcoming syllables and stronger neural phase synchronization to component words, suggesting that they had gained greater sensitivity to the statistical structure of the speech stream relative to the incongruent and static groups. This learning benefit could not be attributed to strategic processes, as participants were largely unaware of the contingencies between the visual stimulation and embedded words. These results indicate that manipulating neural entrainment during exposure to regularities influences statistical learning outcomes, suggesting that neural entrainment may functionally contribute to statistical learning. Our findings encourage future studies using non-invasive brain stimulation methods to further understand the role of entrainment in statistical learning