Self-report and behavioral data suggest that impulsivity may contribute to the development and maintenance of obesity. Neuroimaging studies implicate a widespread neural network in inhibitory control and suggest that impulsive individuals show hypoactivity in these regions during tasks requiring response inhibition. Yet, research has not directly tested whether body mass correlates inversely with activation of these regions during response inhibition tasks. The present study used functional magnetic resonance imaging (fMRI) to investigate neural activations during a food-specific go/no-go task in adolescent girls ranging from lean to obese. When required to inhibit prepotent responses to appetizing food, body mass index (BMI) correlated with response inhibition at both the behavioral and neural level, with more overweight adolescents showing greater behavioral evidence of impulsivity as well as reduced activation of frontal inhibitory regions, including superior frontal gyrus, middle frontal gyrus, ventrolateral prefrontal cortex, medial prefrontal cortex, and orbitofrontal cortex, than leaner individuals. As well, activation in food reward regions (e.g., temporal operculum/insula) in response to food images correlated positively with BMI. Results suggest that hypofunctioning of inhibitory control regions and increased response of food reward regions are related to elevated weight.

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 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.

Statistical learning allows learners to detect regularities in the environment and appears to emerge automatically as a consequence of experience. Statistical learning paradigms bear many similarities to those of artificial grammar learning and other types of implicit learning. However, whether learning effects in statistical learning tasks are driven by implicit knowledge has not been thoroughly examined. The present study addressed this gap by examining the role of implicit and explicit knowledge within the context of a typical auditory statistical learning paradigm. Learners were exposed to a continuous stream of repeating nonsense words. Learning was tested (a) directly via a forced-choice recognition test combined with a remember/know procedure and (b) indirectly through a novel reaction time (RT) test. Behavior and brain potentials revealed statistical learning effects with both tests. On the recognition test, accurate responses were associated with subjective feelings of stronger recollection, and learned nonsense words relative to nonword foils elicited an enhanced late positive potential indicative of explicit knowledge. On the RT test, both RTs and P300 amplitudes differed as a function of syllable position, reflecting facilitation attributable to statistical learning. Explicit stimulus recognition did not correlate with RT or P300 effects on the RT test. These results provide evidence that explicit knowledge is accrued during statistical learning, while bringing out the possibility that dissociable implicit representations are acquired in parallel. The commonly used recognition measure primarily reflects explicit knowledge, and thus may underestimate the total amount of knowledge produced by statistical learning. Indirect measures may be more sensitive indices of learning, capturing knowledge above and beyond what is reflected by recognition accuracy.

The vast majority of word meanings are learned simply by extracting them from context, rather than by rote memorization or explicit instruction. Although this skill is remarkable, little is known about the brain mechanisms involved. In the present study, ERPs were recorded as participants read stories in which pseudowords were presented multiple times, embedded in consistent, meaningful contexts (referred to as meaning condition, M+) or inconsistent, meaningless contexts (M−). Word learning was then assessed implicitly using a lexical decision task and explicitly through recall and recognition tasks. Overall, during story reading, M− words elicited a larger N400 than M+ words, suggesting that participants were better able to semantically integrate M+ words than M− words throughout the story. In addition, M+ words whose meanings were subsequently correctly recognized and recalled elicited a more positive ERP in a later time-window compared to M+ words whose meanings were incorrectly remembered, consistent with the idea that the late positive component (LPC) is an index of encoding processes. In the lexical decision task, no behavioral or electrophysiological evidence for implicit priming was found for M+ words. In contrast, during the explicit recognition task, M+ words showed a robust N400 effect. The N400 effect was dependent upon recognition performance, such that only correctly recognized M+ words elicited an N400. This pattern of results provides evidence that the explicit representations of word meanings can develop rapidly, while implicit representations may require more extensive exposure or more time to emerge.

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.