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The relationship between executive function and second-language ability remains contentious in bilingual children; thus, the current study focused on this issue. In total, 371 Uyghur-Chinese bilingual children ranging from 3 to 6 years old were assessed by a battery of tasks measuring language ability (expressive vocabulary tests, receptive vocabulary tests, and phonological awareness of both their first-language and second-language) and executive function (working memory, inhibition, and switching). Our results indicated that age is a crucial moderator of the relationship between second-language ability and executive function. Specifically, executive function unilaterally predicted second-language ability in children who were 3-4 years old, whereas second-language ability and executive function bilaterally influenced each other in children who were 4-5 and 5-6 years old. These findings suggest that executive function and second-language ability have an intertwined and causal relationship among preschool children during development. The theoretical implications of these findings are discussed.

Animal neuroimaging studies can provide unique insights into brain structure and function, and can be leveraged to bridge the gap between animal and human neuroscience. In part, this power comes from the ability to combine mechanistic interventions with brain-wide neuroimaging. Due to their phylogenetic proximity to humans, nonhuman primate neuroimaging holds particular promise. Because nonhuman primate neuroimaging studies are often underpowered, there is a great need to share data amongst translational researchers. Data sharing efforts have been limited, however, by the lack of standardized tools and repositories through which nonhuman neuroimaging data can easily be archived and accessed. Here, we provide an extension of the Neurovault framework to enable sharing of statistical maps and related voxelwise neuroimaging data from other species and template-spaces. Neurovault, which was previously limited to human neuroimaging data, now allows researchers to easily upload and share nonhuman primate neuroimaging results. This promises to facilitate open, integrative, cross-species science while affording researchers the increased statistical power provided by data aggregation. In addition, the Neurovault code-base now enables the addition of other species and template-spaces. Together, these advances promise to bring neuroimaging data sharing to research in other species, for supplemental data, location-based atlases, and data that would otherwise be relegated to a "file-drawer". As increasing numbers of researchers share their nonhuman neuroimaging data on Neurovault, this resource will enable novel, large-scale, cross-species comparisons that were previously impossible.

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

The emergence of machine learning (ML) techniques has opened up new avenues for identifying biomarkers associated with schizophrenia (SCZ) using task‐related fMRI (t‐fMRI) designs. To evaluate the effectiveness of this approach, we conducted a comprehensive meta‐analysis of 31 t‐fMRI studies using a bivariate model. Our findings revealed a high overall sensitivity of 0.83 and specificity of 0.82 for t‐fMRI studies. Notably, neuropsychological domains modulated the classification performance, with selective attention demonstrating a significantly higher specificity than working memory (β = 0.98, z = 2.11, P = 0.04). Studies involving older, chronic patients with SCZ reported higher sensitivity (P <0.015) and specificity (P <0.001) than those involving younger, first‐episode patients or high‐risk individuals for psychosis. Additionally, we found that the severity of negative symptoms was positively associated with the specificity of the classification model (β = 7.19, z = 2.20, P = 0.03). Taken together, these results support the potential of using task‐based fMRI data in combination with machine learning techniques to identify biomarkers related to symptom outcomes in SCZ, providing a promising avenue for improving diagnostic accuracy and treatment efficacy. Future attempts to deploy ML classification should consider the factors of algorithm choice, data quality and quantity, as well as issues related to generalization. [ABSTRACT FROM AUTHOR]

Recognition memory deficits, even after short delays, are sometimes observed following hippocampal damage. One hypothesis links the hippocampus with processes in updating contextual memory representation. Here, we used fornix transection, which partially disconnects the hippocampal system, and compares the performance of fornix-transected monkeys with normal monkeys on two versions of a delayed-matching-to-position task with short delays. Spatial recognition memory was affected by fornix transection only when the temporal structure of the task changed across trials, while differences in motor control, motivation, perception, or short-term memory were not critical. We attributed the deficit to a compromised ability in tracking changes in task temporal structure.

Recognition memory deficits, even after short delays, are sometimes observed following hippocampal damage. One hypothesis links the hippocampus with processes in updating contextual memory representation. Here, we used fornix transection, which partially disconnects the hippocampal system, and compares the performance of fornix-transected monkeys with normal monkeys on two versions of a delayed-matching-to-position task with short delays. Spatial recognition memory was affected by fornix transection only when the temporal structure of the task changed across trials, while differences in motor control, motivation, perception, or short-term memory were not critical. We attributed the deficit to a compromised ability in tracking changes in task temporal structure.

The relationship between executive function and second‐language ability remains contentious in bilingual children; thus, the current study focused on this issue. In total, 371 Uyghur‐Chinese bilingual children ranging from 3 to 6 years old were assessed by a battery of tasks measuring language ability (expressive vocabulary tests, receptive vocabulary tests, and phonological awareness of both their first‐language and second‐language) and executive function (working memory, inhibition, and switching). Our results indicated that age is a crucial moderator of the relationship between second‐language ability and executive function. Specifically, executive function unilaterally predicted second‐language ability in children who were 3–4 years old, whereas second‐language ability and executive function bilaterally influenced each other in children who were 4–5 and 5–6 years old. These findings suggest that executive function and second‐language ability have an intertwined and causal relationship among preschool children during development. The theoretical implications of these findings are discussed. Research Highlights: A counterfactual model showed causality between executive function and second language ability in Uyghur‐Chinese bilingual children.Executive function unilaterally predicted second language ability in the 3‐ to 4‐year‐old age group.Executive function and second language ability bilaterally influenced each other in the 4‐ to 5 and 5‐ to 6‐year‐old age groups. [ABSTRACT FROM AUTHOR]