Longitudinal Task-Related Functional Connectivity Changes Predict Reading Development

Longitudinal studies suggest developmentally dependent changes in lexical processing during reading development, implying a change in inter-regional functional connectivity over this period. The current study used functional magnetic resonance imaging (fMRI) to explore developmental changes in functional connectivity across multiple runs of a rhyming judgment task in young readers (8–14 years) over an average 2.5-year span. Changes in functional segregation are correlated with and predict changes in the skill with which typically developing children learn to apply the alphabetic principle, as measured by pseudoword decoding. This indicates a developmental shift in the proportion of specialized functional clusters is associated with changes in reading skill and suggests a dependency of reading development on changes of particular neural pathways, specifically decreases in transitivity is indicative of greater network integration. This work provides evidence that characteristics of these pathways, quantified using graph-theoretic metrics, can be used to predict individual differences in reading development

A meta-analytic review of multisensory imagery identifies the neural correlates of modality-specific and modality-general imagery

The relationship between imagery and mental representations induced through perception has been the subject of philosophical discussion since antiquity and of vigorous scientific debate in the last century. The relatively recent advent of functional neuroimaging has allowed neuroscientists to look for brain-based evidence for or against the argument that perceptual processes underlie mental imagery. Recent investigations of imagery in many new domains and the parallel development of new meta-analytic techniques now afford us a clearer picture of the relationship between the neural processes underlying imagery and perception, and indeed between imagery and other cognitive processes. This meta-analysis surveyed 65 studies investigating modality-specific imagery in auditory, tactile, motor, gustatory, olfactory, and three visual sub-domains: form, color and motion. Activation likelihood estimate (ALE) analyses of activation foci reported within- and across sensorimotor modalities were conducted. The results indicate that modality-specific imagery activations generally overlap with—but are not confined to—corresponding somatosensory processing and motor execution areas, and suggest that there is a core network of brain regions recruited during imagery, regardless of task. These findings have important implications for investigations of imagery and theories of cognitive processes, such as perceptually-based representational systems

Cross-modal integration in the brain is related to phonological awareness only in typical readers, not in those with reading difficulty

Fluent reading requires successfully mapping between visual orthographic and auditory phonological representations and is thus an intrinsically cross-modal process, though reading difficulty has often been characterized as a phonological deficit. However, recent evidence suggests that orthographic information influences phonological processing in typical developing (TD) readers, but that this effect may be blunted in those with reading difficulty (RD), suggesting that the core deficit underlying reading difficulties may be a failure to integrate orthographic and phonological information. Twenty-six (13 TD and 13 RD) children between 8 and 13 years of age participated in a functional magnetic resonance imaging (fMRI) experiment designed to assess the role of phonemic awareness in cross-modal processing. Participants completed a rhyme judgment task for word pairs presented unimodally (auditory only) and cross-modally (auditory followed by visual). For typically developing children, correlations between elision and neural activation were found for the cross-modal but not unimodal task, whereas in children with RD, no correlation was found. The results suggest that elision taps both phonemic awareness and cross-modal integration in typically developing readers, and that these processes are decoupled in children with reading difficulty

Distinctive Features Hold a Privileged Status in the Computation of Word Meaning: Implications for Theories of Semantic Memory

The authors present data from 2 feature verification experiments designed to determine whether distinctive features have a privileged status in the computation of word meaning. They use an attractor-based connectionist model of semantic memory to derive predictions for the experiments. Contrary to central predictions of the conceptual structure account, but consistent with their own model, the authors present empirical evidence that distinctive features of both living and nonliving things do indeed have a privileged role in the computation of word meaning. The authors explain the mechanism through which these effects are produced in their model by presenting an analysis of the weight structure developed in the network during training

Semantic Similarity Priming Without Hierarchical Category Structure

In an attractor model of semantic memory, semantic similarity is determined by degree of featural overlap. In contrast, in spreading activation theory, two concepts are similar if they share features or if they are linked to the same superordinate category node. We present an attractor network model of computing word meaning and use it to simulate the data of McRae and Boisvert (in press), who found that short SOA semantic similarity priming directly depends on degree of featural overlap. The two accounts of semantic similarity are then contrasted in a human experiment. In support of attractor networks, priming effects were determined by featural overlap, and no evidence was found for priming through a purported superordinate node. It is concluded that lexical concepts are not represented as static nodes in a hierarchical system

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

An attractor network was trained to compute from word form to semantic representations that were based on subject-generated features. The model was driven largely by higher-order semantic structure. The network simu-lated two recent experiments that employed items included in its training set (McRae and Boisvert, 1998). In Simulation 1, short stimulus onset asyn-chrony priming was demonstrated for semantically similar items. Simulation 2 reproduced subtle effects obtained by varying degree of similarity. Two predictions from the model were then tested on human subjects. In Simula-tion 3 and Experiment 1, the items from Simulation 1 were reversed, and both the network and subjects showed minimally different priming effects in the two directions. In Experiment 2, consistent with attractor networks but con-trary to a key aspect of hierarchical spreading activation accounts priming was determined by featural similarity rather than shared superordinate cat-egory. It is concluded that semantic-similarity priming is due to featural overlap that is a natural consequence of distributed representations of word meaning. I

Data Descriptor: A longitudinal neuroimaging dataset on multisensory lexical processing in school-aged children

This dataset descriptor details the open access dataset entitled “Longitudinal Brain Correlates of Multisensory Lexical Processing in Children” hosted on OpenNeuro.org. This dataset examines reading development through a longitudinal multimodal neuroimaging and behavioral approach, including diffusion-weighted and T1-weighted structural magnetic resonance imaging (MRI), task based functional MRI, and a battery of psycho-educational assessments and parental questionnaires. Neuroimaging, psycho-educational testing, and functional task behavioral data was collected from 188 typically developing children when they were approximately 10.5 years old (session T1). Seventy children returned approximately 2.5 years later (session T2), of which all completed longitudinal follow-ups of psycho-educational testing, and 49 completed neuroimaging and functional tasks. At session T1 participants completed auditory, visual, and audio-visual word and pseudo-word rhyming judgment tasks in the scanner. At session T2 participants completed visual word and pseudo-word rhyming fMRI tasks in the scanner

Dyslexia on a continuum: A complex network approach.

We investigated the efficacy of graph-theoretic metrics of task-related functional brain connectivity in predicting reading difficulty and explored the hypothesis that task conditions emphasizing audiovisual integration would be especially diagnostic of reading difficulty. An fMRI study was conducted in which 24 children (8 to 14 years old) who were previously diagnosed with dyslexia completed a rhyming judgment task under three presentation modality conditions. Regression analyses found that characteristic connectivity metrics of the reading network showed a presentation modality dependent relationship with reading difficulty: Children with more segregated reading networks and those that used fewer of the available connections were those with the least severe reading difficulty. These results are consistent with the hypothesis that a lack of coordinated processing between the neural regions involved in phonological and orthographic processing contributes towards reading difficulty

Feature–Feature Causal Relations and Statistical Co-Occurrences in Object Concepts

Influences of feature–feature statistical co-occurrences and causal relations have been found in some circumstances, but not others. We hypothesized that detecting an influence of these knowledge types hinges crucially on the congruence between the task and type of knowledge. We show that both knowledge types influence tasks that tap feature relatedness. Detailed descriptions of causal theories were collected, and co-occurrence statistics were based on feature production norms. Regression analyses tested the influences of these knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs spanning a range of correlational strength. Both knowledge types influenced both tasks, demonstrating that causal theories and statistical co-occurrences between features influence conceptual computations