The Impact of Math Anxiety on Working Memory: A Cortical Activations and Cortical Functional Connectivity EEG Study

AbstractThe relationship between anxiety and mathematics has often been investigated in the literature. Different forms of anxiety have been evaluated, with math anxiety (MA) and test anxiety (TA) consistently being associated with various aspects of mathematics. In this meta-analysis, we have evaluated the impact of these forms of anxiety, distinguishing between different types of mathematical tasks. In investigating this relationship, we have also included potential moderators, such as age, gender, working memory, type of task, and type of material. One hundred seventy-seven studies met the inclusion criteria, providing an overall sample of 906,311 participants. Results showed that both MA and TA had a significant impact on mathematics. Sociodemographic factors had modest moderating effects. Working memory (WM) also mediated the relationship between MA and TA with mathematics; however, this indirect effect was weak. Theoretical and educational implications, as well as future directions for research in this field, are discussed.

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Do Children With Developmental Language Disorder (DLD) Have Difficulties With Interference Control, Visuospatial Working Memory, and Selective Attention? Developmental Patterns and the Role of Severity and Persistence of DLD

Journal of Speech Language and Hearing Research ◽

10.1044/2020_jslhr-20-00012 ◽

2020 ◽

Vol 63 (9) ◽

pp. 3036-3050

Author(s):

Elma Blom ◽

Tessel Boerma

Keyword(s):

Working Memory ◽

Selective Attention ◽

Language Disorder ◽

Typically Developing ◽

Developmental Language Disorder ◽

Visuospatial Working Memory ◽

Interference Control ◽

Developmental Patterns ◽

Search Tasks ◽

The Impact

Purpose Many children with developmental language disorder (DLD) have weaknesses in executive functioning (EF), specifically in tasks testing interference control and working memory. It is unknown how EF develops in children with DLD, if EF abilities are related to DLD severity and persistence, and if EF weaknesses expand to selective attention. This study aimed to address these gaps. Method Data from 78 children with DLD and 39 typically developing (TD) children were collected at three times with 1-year intervals. At Time 1, the children were 5 or 6 years old. Flanker, Dot Matrix, and Sky Search tasks tested interference control, visuospatial working memory, and selective attention, respectively. DLD severity was based on children's language ability. DLD persistence was based on stability of the DLD diagnosis. Results Performance on all tasks improved in both groups. TD children outperformed children with DLD on interference control. No differences were found for visuospatial working memory and selective attention. An interference control gap between the DLD and TD groups emerged between Time 1 and Time 2. Severity and persistence of DLD were related to interference control and working memory; the impact on working memory was stronger. Selective attention was unrelated to DLD severity and persistence. Conclusions Age and DLD severity and persistence determine whether or not children with DLD show EF weaknesses. Interference control is most clearly impaired in children with DLD who are 6 years and older. Visuospatial working memory is impaired in children with severe and persistent DLD. Selective attention is spared.

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The Impact of the Working Memory Capacity on Counting Strategies

PsycEXTRA Dataset ◽

10.1037/e512682013-110 ◽

2007 ◽

Author(s):

Valerie Camos

Keyword(s):

Working Memory ◽

Working Memory Capacity ◽

Memory Capacity ◽

The Impact

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The impact of affective contexts on working memory capacity in healthy populations and in individuals with PTSD.

Emotion ◽

10.1037/emo0000072 ◽

2016 ◽

Vol 16 (1) ◽

pp. 16-23 ◽

Cited By ~ 16

Author(s):

Susanne Schweizer ◽

Tim Dalgleish

Keyword(s):

Working Memory ◽

Working Memory Capacity ◽

Memory Capacity ◽

The Impact

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How do working memory, general anxiety and math anxiety affect female students’ math performance?

10.31234/osf.io/dbp7t ◽

2020 ◽

Author(s):

Nachshon Korem ◽

Orly Rubinsten

Keyword(s):

Working Memory ◽

Latent Variables ◽

Math Anxiety ◽

Verbal Working Memory ◽

Math Performance ◽

Equation Modeling ◽

Current Evidence ◽

Unique Contribution ◽

Shared Variance ◽

Numeric Information

Current evidence suggests that math anxiety and working memory govern math performance. However, these conclusions are largely based on simple correlations, without considering these variables as a network or examining correlations at the latent variables level. Thus, questions remain regarding the role of the unique and shared variance between math anxiety, working memory and math performance. The purpose of the current study was to (i) uncover the underlying relationships between the variables to understand the unique contribution of each element to the network; (ii) measure the shared variance and identify the interactions between affect and cognition that control math performance. Our analytical approach involved both network analysis approach and structural equation modeling, with a sample of 116 female students.Results show that math anxiety and working memory affect math performance by different mechanisms. Only working memory tests that included numeric information were correlated to math anxiety. Each of the various working memory tasks correlated differently to math performance: working memory as a single latent variable was a better predictor of math performance than visuospatial and verbal working memory as two separate latent variables. Overall, both working memory and math anxiety affect math performance. Working memory tasks that include numeric information can affect performance in math anxious individuals.

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Dissociating the Impact of Auditory Access and Language Access in Deaf Children’s Cognitive Development

The Oxford Handbook of Deaf Studies in Learning and Cognition ◽

10.1093/oxfordhb/9780190054045.013.19 ◽

2020 ◽

pp. 98-122

Author(s):

Matthew L. Hall

Keyword(s):

Working Memory ◽

Executive Function ◽

Cognitive Development ◽

Implicit Learning ◽

Educational Practice ◽

Verbal Working Memory ◽

Psychological Theory ◽

Future Research ◽

Language Access ◽

The Impact

Deaf and hard of hearing (DHH) children have been claimed to lag behind their hearing peers in various domains of cognitive development, especially in implicit learning, executive function, and working memory. Two major accounts of these deficits have been proposed: one based on a lack of auditory access, and one based on a lack of language access. This chapter reviews these theories in relation to the available evidence and concludes that there is little evidence of direct effects of diminished auditory access on cognitive development that could not also be explained by diminished language access. Specifically, reports of deficits in implicit learning are not broadly replicable. Some differences in executive function do stem from deafness itself but are not necessarily deficits. Where clinically relevant deficits in executive function are observed, they are inconsistent with the predictions of accounts based on auditory access, but consistent with accounts based on language access. Deaf–hearing differences on verbal working memory tasks may indicate problems with perception and/or language, rather than with working memory. Deaf–hearing differences on nonverbal tasks are more consistent with accounts based on language access, but much more study is needed in this area. The chapter concludes by considering the implications of these findings for psychological theory and for clinical/educational practice and by identifying high-priority targets for future research.

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043 Sleep Restriction Affects Memory in Healthy Adults: Preliminary Findings

SLEEP ◽

10.1093/sleep/zsab072.042 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A18-A19

Author(s):

Molly Zimmerman ◽

Christiane Hale ◽

Adam Brickman ◽

Lok-Kin Yeung ◽

Justin Cochran ◽

...

Keyword(s):

Working Memory ◽

Negative Impact ◽

Positive Impact ◽

Healthy Adults ◽

Task Demands ◽

Sleep Restriction ◽

Neuropsychological Function ◽

Wake Time ◽

Sleep Condition ◽

The Impact

Abstract Introduction Sleep loss has a range of detrimental effects on cognitive ability. However, few studies have examined the impact of sleep restriction on neuropsychological function using an experimental design. The goal of this study was to examine the extent to which maintained insufficient sleep affects cognition in healthy adults compared to habitual adequate sleep. Methods This study used a randomized, crossover, outpatient sleep restriction design. Adults who regularly slept at least 7 h/night, verified by 2 weeks of screening with actigraphy, completed 2 phases of 6 weeks each: habitual sleep (>7 h of sleep/night) or sleep restriction (habitual sleep minus 1.5 h) separated by a 6-week washout period. During the sleep restriction phase, participants were asked to delay their bedtime by 1.5 hours/night while maintaining their habitual wake time. Neuropsychological function was evaluated with the NIH Toolbox Cognition Battery at baseline (week 0) and endpoint (week 6) of each intervention phase. The NIH Toolbox evaluates a range of cognitive abilities, including attention, executive functioning, and working memory. General linear models with post hoc paired t-tests were used to assess demographically-adjusted test scores prior to and following each sleep condition. Results At the time of analyses, 16 participants were enrolled (age 34.5□14.5 years, 9 women), 10 of whom had completed study procedures. An interaction between sleep condition and testing session revealed that individuals performed worse on List Sorting, a working memory test, after sleep restriction but improved slightly after habitual sleep (p<0.001). While not statistically reliable, the pattern of test results was similar on the other tests of processing speed, executive function, and attention. Conclusion In these preliminary results from this randomized experimental study, we demonstrated that sleep restriction has a negative impact while stable habitual adequate sleep has a positive impact on working memory, or the ability to temporarily hold information in mind while executing task demands. This finding contributes to our understanding of the complex interplay between different aspects of sleep quality (i.e., both sleep restriction as well as the maintenance of stable sleep patterns) on cognition and underscores the importance of routine sleep screening as part of medical evaluations. Support (if any):

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Structural and functional brain-wide alterations in A350V Iqsec2 mutant mice displaying autistic-like behavior

Translational Psychiatry ◽

10.1038/s41398-021-01289-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Daniela Lichtman ◽

Eyal Bergmann ◽

Alexandra Kavushansky ◽

Nadav Cohen ◽

Nina S. Levy ◽

...

Keyword(s):

Social Behavior ◽

Functional Connectivity ◽

Mouse Model ◽

Ampa Receptor ◽

Social Preference ◽

Autism Spectrum ◽

Receptor Trafficking ◽

Anterior Cingulate ◽

The Impact ◽

Ampa Receptor Trafficking

AbstractIQSEC2 is an X-linked gene that is associated with autism spectrum disorder (ASD), intellectual disability, and epilepsy. IQSEC2 is a postsynaptic density protein, localized on excitatory synapses as part of the NMDA receptor complex and is suggested to play a role in AMPA receptor trafficking and mediation of long-term depression. Here, we present brain-wide structural volumetric and functional connectivity characterization in a novel mouse model with a missense mutation in the IQ domain of IQSEC2 (A350V). Using high-resolution structural and functional MRI, we show that animals with the A350V mutation display increased whole-brain volume which was further found to be specific to the cerebral cortex and hippocampus. Moreover, using a data-driven approach we identify putative alterations in structure–function relations of the frontal, auditory, and visual networks in A350V mice. Examination of these alterations revealed an increase in functional connectivity between the anterior cingulate cortex and the dorsomedial striatum. We also show that corticostriatal functional connectivity is correlated with individual variability in social behavior only in A350V mice, as assessed using the three-chamber social preference test. Our results at the systems-level bridge the impact of previously reported changes in AMPA receptor trafficking to network-level disruption and impaired social behavior. Further, the A350V mouse model recapitulates similarly reported brain-wide changes in other ASD mouse models, with substantially different cellular-level pathologies that nonetheless result in similar brain-wide alterations, suggesting that novel therapeutic approaches in ASD that result in systems-level rescue will be relevant to IQSEC2 mutations.

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A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

Brain Informatics ◽

10.1186/s40708-021-00129-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Federico Calesella ◽

Alberto Testolin ◽

Michele De Filippo De Grazia ◽

Marco Zorzi

Keyword(s):

Feature Extraction ◽

Functional Connectivity ◽

Dimensionality Reduction ◽

Verbal Memory ◽

Resting State ◽

Component Analysis ◽

Model Complexity ◽

Stroke Patients ◽

Prediction Ability ◽

The Impact

AbstractMultivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. However, the high dimensionality of neuroimaging data increases the risk of overfitting, calling for the use of dimensionality reduction methods to build robust predictive models. In this work, we assess the ability of four well-known dimensionality reduction techniques to extract relevant features from resting state functional connectivity matrices of stroke patients, which are then used to build a predictive model of the associated deficits based on cross-validated regularized regression. In particular, we investigated the prediction ability over different neuropsychological scores referring to language, verbal memory, and spatial memory domains. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) were the two best methods at extracting representative features, followed by Dictionary Learning (DL) and Non-Negative Matrix Factorization (NNMF). Consistent with these results, features extracted by PCA and ICA were found to be the best predictors of the neuropsychological scores across all the considered cognitive domains. For each feature extraction method, we also examined the impact of the regularization method, model complexity (in terms of number of features that entered in the model) and quality of the maps that display predictive edges in the resting state networks. We conclude that PCA-based models, especially when combined with L1 (LASSO) regularization, provide optimal balance between prediction accuracy, model complexity, and interpretability.

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