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The ability to make predictions is thought to facilitate language processing. During language comprehension such predictions appear to occur at multiple levels of linguistic representations (i.e. semantic, syntactic and lexical). The neural mechanisms that define the network sensitive to linguistic predictability have yet to be adequately defined. The purpose of the present study was to explore the neural network underlying predictability during the normal reading of connected text. Predictability values for different linguistic information were obtained from a pre-existing text corpus. Forty-one subjects underwent simultaneous eye-tracking and fMRI scans while reading these select paragraphs. Lexical, semantic, and syntactic predictability measures were then correlated with functional activation associated with fixation onset on the individual words. Activation patterns showed both positive and negative correlations to lexical, semantic, and syntactic predictabilities. Conjunction analysis revealed regions specific to or shared between each type of predictability. The regions associated with the different predictability measures were largely separate. Results suggest that most linguistic predictions are graded in nature, activating components of the existing language system. A number of regions were also found to be uniquely associated with full lexical predictability, most notably the anterior temporal lobe and the inferior posterior temporal cortex., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Obesity and maintaining a healthy diet have important implications for physical and mental health. One factor that may influence diet and obesity is inhibitory control. We tested how N2 and P3 amplitude, event-related potential (ERP) components that reflect inhibitory control, and functional magnetic resonance imaging (fMRI) activity in brain regions associated with inhibitory control differed toward high- and low-calorie food stimuli across BMI status. We also assessed the relationship between neural indices of food-related inhibitory control and laboratory and daily food intake. Fifty-four individuals (17 normal-weight; 18 overweight; 19 individuals with obesity) completed two food-based go/no-go tasks (one with high- and one with low-calorie foods as no-go stimuli), once during ERP data acquisition and once during fMRI data acquisition. After testing, participants were presented with an ad libitum weighed food buffet. Participants also recorded their food intake using the Automated Self-Administered 24-hour Dietary Recall (ASA24) system across four days. Individuals recruited more inhibitory control when withholding responses towards high-compared to low-calorie foods, although this effect was more consistent for N2 than P3 or fMRI assessments. BMI status did not influence food-related inhibitory control. A larger inhibitory response as measured by N2 amplitude was related to increased ASA24 food intake; P3 amplitude and fMRI region of interest activity did not predict ASA24 intake; neither method predicted food intake from the buffet. ERP and fMRI measurements show similar neural responses to food, although N2 amplitude may be somewhat more sensitive in detecting differences between food types and predicting self-reports of food intake., (Copyright © 2017 Elsevier Inc. All rights reserved.)