Processing Fat-Related Information in Individuals at Risk for Developing an Eating Disorder

The authors examined the effect that being at risk for developing an eating disorder has on the lexical processing of words related to fat and words not related to fat. Individuals (n = 17) at risk for developing an eating disorder were compared with controls (n = 31) using a lexical decision task in which fat-related words (e.g., large), unrelated words (e.g., fair), neutral words (e.g., post), and pseudowords (e.g., flirp) were given. The results revealed an expected Group x Stimuli interaction for reaction times indicating that at-risk individuals were significantly faster at processing fat-related words than words unrelated to fat. The authors discuss these results within the context of how fat-related stimuli are processed in at-risk individuals and how models of information processing can aid in the interpretation and understanding of eating disorders.     

The Relationship between Trauma and Financial and Physical Well-Being Among Cambodians in the United States

This study focused on the relationship between trauma and financial and physical well-being of Cambodian refugees in the United Sates. Trauma was defined by three variables: whether or not trauma had been experienced in Cambodia, the number of traumas experienced, and the number of years spent in refugee camps. It was hypothesized that these trauma variables would predict financial and physical health among Cambodians in the United States. A discriminant analysis showed significant relationships between the trauma variables and current employment status, and multiple regression analyses showed that trauma predicted income and physical health.     

Author Index

The association between family functioning and adolescent adjustment was examined in 429 Chinese adolescents via children's and parents' reports. The ratings obtained from the different sources indicated that family functioning was significantly related to measures of (a) adolescent psychological well-being (general psychiatric morbidity, life satisfaction, purpose in life, hopelessness, and self-esteem), (b) school adjustment (perceived academic performance and school conduct), and (c) problem behavior (smoking and abusing psychotropic drugs). The findings suggest that there is an intimate link between family functioning and the psychosocial adjustment, particularly the positive mental health, of Chinese adolescents.     

Predictive Pointing Movements and Saccades Toward a Moving Target

The authors investigated whether and, if so, how velocity information is used to control predictive manual pointing movements and saccades. Participants (N = 6) intercepted an occluded moving target as if it were still visible. They kept their eyes fixated while the target moved. The target traveled over a fixed distance and changed its velocity on the way. The presentation time of the final velocity was varied. Both the eye and the hand overshot the slow target and undershot the fast target, particularly when the duration of the final velocity was short. Thus, responses were biased in the direction of the target's initial velocity. The error seemed to arise because participants did not take their latency into account when aiming at the target. Instead, they strategically aimed farther ahead when the target was fast. Amplitude was also more related to the position of velocity change than to final velocity duration. Both findings suggest that target velocity is not extrapolated but that individuals add an increment to the position of velocity change.     

The Visuomotor Mental Rotation Task: Visuomotor Transformation Times Are Reduced for Small and Perceptually Familiar Angles

In the visuomotor mental rotation (VMR) task, participants point to a location that deviates from a visual cue by a predetermined angle. This task elicits longer reaction times (RT) relative to tasks wherein the visual cue is spatially compatible with the movement goal. The authors previously reported that visuomotor transformations are faster and more efficient when VMR responses elicit a degree of dimensional overlap (i.e., 0° and 5°) or when the transformation involves a perceptually familiar angle (i.e., 90° or 180°; K. A. Neely & M. Heath, 2010b). One caveat to this finding is that standard and VMR responses were completed in separate blocks of trials. Thus, between-task differences not only reflect the temporal demands of the visuomotor transformations, but also reflect the temporal cost of response inhibition. The goal of this study was to isolate the time cost of visuomotor transformations in the VMR task. The results demonstrated that visuomotor transformations are more efficient and effective when the response entails a degree of dimensional overlap between target and response (i.e., when the angular disparity between the responses is small) or when the transformation angle is perceptually familiar.     

Do temporal processes underlie left hemisphere dominance in speech perception?

It is not unusual to find it stated as a fact that the left hemisphere is specialized for the processing of rapid, or temporal aspects of sound, and that the dominance of the left hemisphere in the perception of speech can be a consequence of this specialization. In this review we explore the history of this claim and assess the weight of this assumption. We will demonstrate that instead of a supposed sensitivity of the left temporal lobe for the acoustic properties of speech, it is the right temporal lobe which shows a marked preference for certain properties of sounds, for example longer durations, or variations in pitch. We finish by outlining some alternative factors that contribute to the left lateralization of speech perception.     

Pediatric traumatic brain injury: Language outcomes and their relationship to the arcuate fasciculus

Pediatric traumatic brain injury (TBI) may result in long-lasting language impairments alongside dysarthria, a motor-speech disorder. Whether this co-morbidity is due to the functional links between speech and language networks, or to widespread damage affecting both motor and language tracts, remains unknown.     

Predicting language: MEG evidence for lexical preactivation

It is widely assumed that prediction plays a substantial role in language processing. However, despite numerous studies demonstrating that contextual information facilitates both syntactic and lexical–semantic processing, there exists no direct evidence pertaining to the neural correlates of the prediction process itself. Using magnetoencephalography (MEG), this study found that brain activity was modulated by whether or not a specific noun could be predicted, given a picture prime. Specifically, before the noun was presented, predictive contexts triggered enhanced activation in left mid-temporal cortex (implicated in lexical access), ventro-medial prefrontal cortex (previously associated with top-down processing), and visual cortex (hypothesized to index the preactivation of predicted form features), successively. This finding suggests that predictive language processing recruits a top-down network where predicted words are activated at different levels of representation, from more ‘abstract’ lexical–semantic representations in temporal cortex, all the way down to visual word form features. The same brain regions that exhibited enhanced activation for predictive contexts before the onset of the noun showed effects of congruence during the target word. To our knowledge, this study is one of the first to directly investigate the anticipatory stage of predictive language processing.     

Developmental intelligence: From empirical to hidden constructs

This article answers some of the criticisms and suggestions of the three commentaries. We showed, in agreement with Coyle, that (i) variability is indeed distinct from speed, (ii) they both additively reflect processing efficiency and (iii) that they differentially relate to WM and gf during development. In agreement with Kail, we showed that developmental intelligence and psychometric intelligence are (i) related but distinct, they additively contribute to school learning and (iii) their role varies with developmental phase. Finally, in agreement with Pascual-Leone, we proposed a number of higher level hidden constructs to account for the data patterns observed between empirical constructs, such as speed, variability, WM, and reasoning.     

Intelligence is differentially related to neural effort in the task-positive and the task-negative brain network

Previous studies on individual differences in intelligence and brain activation during cognitive processing focused on brain regions where activation increases with task demands (task-positive network, TPN). Our study additionally considers brain regions where activation decreases with task demands (task-negative network, TNN) and compares effects of intelligence on neural effort in the TPN and the TNN. In a sample of 52 healthy subjects, functional magnetic resonance imaging was used to determine changes in neural effort associated with the processing of a working memory task. The task comprised three conditions of increasing difficulty: (a) maintenance, (b) manipulation, and (c) updating of a four-letter memory set. Neural effort was defined as signal increase in the TPN and signal decrease in the TNN, respectively. In both functional networks, TPN and TNN, neural effort increased with task difficulty. However, intelligence, as assessed with Raven's Matrices, was differentially associated with neural effort in the TPN and TNN. In the TPN, we observed a positive association, while we observed a negative association in the TNN. In terms of neural efficiency (i.e., task performance in relation to neural effort expended on task processing), more intelligent subjects (as compared to less intelligent subjects) displayed lower neural efficiency in the TPN, while they displayed higher neural efficiency in the TNN. The results illustrate the importance of differentiating between TPN and TNN when interpreting correlations between intelligence and fMRI measures of brain activation. Importantly, this implies the risk of misinterpreting whole brain correlations when ignoring the functional differences between TPN and TNN.