Working memory and processing speed abilities are related to habituation and change detection in school-aged children: An ERP study

High cognitive performance is related to efficient brain processing while accomplishing complex cognitive tasks. This efficiency is observed through a rapid engagement of the brain regions and the cognitive processes required for task accomplishment. However, it is unclear if this efficiency is also present in basic sensory processes such as habituation and change detection. We recorded EEG with 85 healthy children (51 males) aged between 4 and 13 years old, while they listened to an auditory oddball paradigm. Cognitive functioning was evaluated using the Weschler Intelligence Scales for Children Fifth Edition and the Weschler Preschool & Primary School for Intelligence Fourth Edition. Auditory evoked potentials (AEPs) analyses and repeated measure analysis of covariance as well as regression models were performed. The analysis revealed that P1 and N1 repetition effects were observed across levels of cognitive functioning. Further, working memory abilities were related to repetition suppression on the auditory P2 component amplitude, while faster processing speed was related to repetition enhancement on the N2 component amplitude. Also, Late Discriminative Negativity (LDN) amplitude, a neural correlate of change detection, increased with working memory abilities. Our results confirm that efficient repetition suppression (i.e. greater reduction in amplitudes with greater levels of cognitive functioning) and more sensitive change detection (greater amplitude changes of the LDN) are related to the level of cognitive functioning in healthy children. More specifically, working memory and processing speed abilities are the cognitive domains related to efficient sensory habituation and change detection.

A Psychometric Network Analysis of CHC Intelligence Measures: Implications for Research, Theory, and Interpretation of Broad CHC Scores "Beyond g"

For over a century, the structure of intelligence has been dominated by factor analytic methods that presume tests are indicators of latent entities (e.g., general intelligence or g). Recently, psychometric network methods and theories (e.g., process overlap theory; dynamic mutualism) have provided alternatives to g-centric factor models. However, few studies have investigated contemporary cognitive measures using network methods. We apply a Gaussian graphical network model to the age 9-19 standardization sample of the Woodcock-Johnson Tests of Cognitive Ability-Fourth Edition. Results support the primary broad abilities from the Cattell-Horn-Carroll (CHC) theory and suggest that the working memory-attentional control complex may be central to understanding a CHC network model of intelligence. Supplementary multidimensional scaling analyses indicate the existence of possible higher-order dimensions (PPIK; triadic theory; System I-II cognitive processing) as well as separate learning and retrieval aspects of long-term memory. Overall, the network approach offers a viable alternative to factor models with a g-centric bias (i.e., bifactor models) that have led to erroneous conclusions regarding the utility of broad CHC scores in test interpretation beyond the full-scale IQ, g.

Multidimensional Scaling of Cognitive Ability and Academic Achievement Scores

Multidimensional scaling (MDS) was used as an alternate multivariate procedure for investigating intelligence and academic achievement test score correlations. Correlation coefficients among Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5) and Wechsler Individual Achievement Test, Third Edition (WIAT-III) validity sample scores and among Kaufman Assessment Battery for Children, Second Edition (KABC-II) and Kaufman Test of Educational Achievement, Second Edition (KTEA-2) co-norming sample scores were analyzed using multidimensional scaling (MDS). Three-dimensional MDS configurations were the best fit for interpretation in both datasets. Subtests were more clearly organized by CHC ability and academic domain instead of complexity. Auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions were visible in all models. Results were mostly similar across different grade levels. Additional analysis with WISC-V and WIAT-III tests showed that content (verbal, numeric, figural) and response process facets (verbal, manual, paper-pencil) were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically based validity evidence regarding content and response mode processes.

Age and Gender Invariance in the Taiwan Wechsler Intelligence Scale for Children, Fifth Edition: Higher Order Five-Factor Model

This study investigated the factorial invariance of the Taiwan Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) across age and gender. A higher order five-factor model was tested on a nationally representative sample of 1,034 children aged 6–16 years. The results demonstrated full factorial invariance for Taiwan children of different ages and gender. The WISC-V subtests demonstrated the same underlying theoretical latent constructs, strength of relations among factors and subtests, validity of each first-order factor, and communalities, regardless of age and gender, which supported the same interpretive approach of the WISC-V. These results accord with findings in the United States, indicating a full factorial invariance of the WISC-V five-factor structure across ages and gender.

Latent Feature Extraction for Process Data via Multidimensional Scaling

Computer-based interactive items have become prevalent in recent educational assessments. In such items, detailed human-computer interactive process, known as response process, is recorded in a log file. The recorded response processes provide great opportunities to understand individuals' problem solving processes. However, difficulties exist in analyzing these data as they are high-dimensional sequences in a nonstandard format. This paper aims at extracting useful information from response processes. In particular, we consider an exploratory analysis that extracts latent variables from process data through a multidimensional scaling framework. A dissimilarity measure is described to quantify the discrepancy between two response processes. The proposed method is applied to both simulated data and real process data from 14 PSTRE items in PIAAC 2012. A prediction procedure is used to examine the information contained in the extracted latent variables. We find that the extracted latent variables preserve a substantial amount of information in the process and have reasonable interpretability. We also empirically prove that process data contains more information than classic binary item responses in terms of out-of-sample prediction of many variables.

Use of translated and adapted versions of the WISC-V: Caveat emptor

The Wechsler Intelligence Scale for Children (WISC) is the most widely used intelligence test in the world. Now in its fifth edition, the WISC-V has been translated and adapted for use in nearly a dozen countries. Despite its popularity, numerous concerns have been raised about some of the procedures used to develop and validate translated and adapted versions of the test around the world. The purpose of this article is to survey the most salient of those methodological and statistical limitations. In particular, empirical data are presented that call into question the equating procedures used to validate the WISC-V Spanish, suggesting cautious use of that instrument. It is believed that the issues raised in the present article will be instructive for school psychologists engaged in the clinical assessment of intelligence with the WISC-V Spanish and with other translated and adapted versions around the world.

Digit Span Subscale Scores May Be Insufficiently Reliable for Clinical Interpretation: Distinguishing Between Stratified Coefficient Alpha and Omega Hierarchical

The Digit Span subscale (Digit Span Forward, Backward, and Sequencing combined composite) internal inconsistency reliability has been reported at .93, based on a coefficient known as stratified coefficient alpha. With accessible examples, we demonstrate that stratified coefficient alpha can deviate substantially from a model-based internal consistency reliability that represents an underlying dimension, that is, omega hierarchical. Next, we simulated item-level Digit Span subscale data to correspond very closely to the Wechsler Adult Intelligence Scale-fourth edition normative sample. Based on omega hierarchical, we estimated the internal consistency reliability associated with the Digit Span subscale scores at .74. In light of the results, clinicians are cautioned against interpreting Digit Span subscale scores. Instead, interpretations should probably be restricted to the Digit Span Forward, Digit Span Backward, and Digit Span Sequencing test scores. Finally, we offer suggestions for improvement to achieve higher levels of Digit Span subscale score reliability.