We investigated the independent contributions of second language (L2) age of acquisition (AoA) and social diversity of language use on intrinsic brain organization using seed-based resting-state ...functional connectivity among highly proficient French-English bilinguals. There were two key findings. First, earlier L2 AoA related to greater interhemispheric functional connectivity between homologous frontal brain regions, and to decreased reliance on proactive executive control in an AX-Continuous Performance Task completed outside the scanner. Second, greater diversity in social language use in daily life related to greater connectivity between the anterior cingulate cortex and the putamen bilaterally, and to increased reliance on proactive control in the same task. These findings suggest that early vs. late L2 AoA links to a specialized neural framework for processing two languages that may engage a specific type of executive control (e.g., reactive control). In contrast, higher vs. lower degrees of diversity in social language use link to a broadly distributed set of brain networks implicated in proactive control and context monitoring.
•Bilingual experience adaptively tunes neural networks involved in executive control.•Early L2 AoA relates to greater frontal interhemispheric functional connectivity.•Greater diversity of language use relates to greater subcortical connectivity.•Frontal and subcortical connectivity relate to proactive-reactive shifts in behavior.•Historical and ongoing language experience impact functional brain connectivity.
Anticorrelated relationships in spontaneous signal fluctuation have been previously observed in resting-state functional magnetic resonance imaging (fMRI). In particular, it was proposed that there ...exists two systems in the brain that are intrinsically organized into anticorrelated networks, the default mode network, which usually exhibits task-related deactivations, and the task-positive network, which usually exhibits task-related activations during tasks that demands external attention. However, it is currently under debate whether the anticorrelations observed in resting state fMRI were valid or were instead artificially introduced by global signal regression, a common preprocessing technique to remove physiological and other noise in resting-state fMRI signal. We examined positive and negative correlations in resting-state connectivity using two different preprocessing methods: a component base noise reduction method (CompCor, Behzadi et al., 2007), in which principal components from noise regions-of-interest were removed, and the global signal regression method. Robust anticorrelations between a default mode network seed region in the medial prefrontal cortex and regions of the task-positive network were observed under both methods. Specificity of the anticorrelations was similar between the two methods. Specificity and sensitivity for positive correlations were higher under CompCor compared to the global regression method. Our results suggest that anticorrelations observed in resting-state connectivity are not an artifact introduced by global signal regression and might have biological origins, and that the CompCor method can be used to examine valid anticorrelations during rest.
►Resting-state connectivity analysis without global signal regression. ►Principal components from noise regions-of-interest were regressed out (CompCor). ►Robust anticorrelations were observed under CompCor. ►Specificity was equal or higher under CompCor compared to global signal regression.
Salmonella enterica infections are transmitted not only by animal-derived foods but also by vegetables, fruits, and other plant products. To clarify links between Salmonella serotypes and specific ...foods, we examined the diversity and predominance of food commodities implicated in outbreaks of salmonellosis during 1998-2008. More than 80% of outbreaks caused by serotypes Enteritidis, Heidelberg, and Hadar were attributed to eggs or poultry, whereas >50% of outbreaks caused by serotypes Javiana, Litchfield, Mbandaka, Muenchen, Poona, and Senftenberg were attributed to plant commodities. Serotypes Typhimurium and Newport were associated with a wide variety of food commodities. Knowledge about these associations can help guide outbreak investigations and control measures.
Previous findings have been mixed regarding the relationship between maternal depressive symptoms and child cognitive development. The objective of this study was to systematically review relevant ...literature and to perform a meta-analysis.
Three electronic databases (PubMed, EMBASE, PsycINFO) were searched. Initial screening was conducted independently by two reviewers. Studies selected for detailed review were read in full and included based on a set of criteria. Data from selected studies were abstracted onto a standardized form. Meta-analysis using the inverse variance approach and random-effects models was conducted.
The univariate analysis of 14 studies revealed that maternal depressive symptoms are related to lower cognitive scores among children aged ⩽56 months (Cohen's d = -0.25, 95% CI -0.39 to -0.12). The synthesis of studies controlling for confounding variables showed that the mean cognitive score for children 6-8 weeks post-partum whose mothers had high depressive symptoms during the first few weeks postpartum was approximately 4.2 units lower on the Mental Developmental Index (MDI) of the Bayley Scales of Infant and Toddler Development (BSID) compared with children with non-symptomatic mothers (B̂ = -4.17, 95% CI -8.01 to -0.32).
The results indicated that maternal depressive symptoms are related to lower cognitive scores in early infancy, after adjusting for confounding factors. An integrated approach for supporting child cognitive development may include program efforts that promote maternal mental health in addition to family economic wellbeing, responsive caregiving, and child nutrition.
Recent years have witnessed an increasing interest in deploying state-of-the-art augmented reality (AR) head-mounted displays (HMDs) for agri-food applications. The benefits of AR HMDs to agri-food ...industry stakeholders (e.g., food suppliers, retail/food service) have received growing attention and recognition. AR HMDs enable users to make healthier dietary choices, experience novel changes in their perception of taste, enhance the cooking and food shopping experience, improve productivity at work and enhance the implementation of precision farming. Therefore, although development costs are still high, the case for integration of AR in food chains appears to be compelling. This review will present the most recent developments of AR HMDs for agri-food relevant applications. The summarized applications can be clustered into different themes: (1) dietary and food nutrition assessment; (2) food sensory science; (3) changing the eating environment; (4) retail food chain applications; (5) enhancing the cooking experience; (6) food-related training and learning; and (7) food production and precision farming. Limitations of current practices will be highlighted, along with some proposed applications.
Currently, strawberry harvesting relies heavily on human labour and subjective assessments of ripeness, resulting in inconsistent post-harvest quality. Therefore, the aim of this work is to automate ...this process and provide a more accurate and efficient way of assessing ripeness. We explored a unique combination of YOLOv7 object detection and augmented reality technology to detect and visualise the ripeness of strawberries. Our results showed that the proposed YOLOv7 object detection model, which employed transfer learning, fine-tuning and multi-scale training, accurately identified the level of ripeness of each strawberry with an mAP of 0.89 and an F1 score of 0.92. The tiny models have an average detection time of 18 ms per frame at a resolution of 1280 × 720 using a high-performance computer, thereby enabling real-time detection in the field. Our findings distinctly establish the superior performance of YOLOv7 when compared to other cutting-edge methodologies. We also suggest using Microsoft HoloLens 2 to overlay predicted ripeness labels onto each strawberry in the real world, providing a visual representation of the ripeness level. Despite some challenges, this work highlights the potential of augmented reality to assist farmers in harvesting support, which could have significant implications for current agricultural practices.
We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional ...connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice.
Information that is encoded in relation to the self has been shown to be better remembered, yet reports have disagreed on whether the memory benefit from self-referential encoding extends to source ...memory (the context in which information was learned). In this study, we investigated the self-referential effect on source memory in recollection and familiarity-based memory. Using a Remember/Know paradigm, we compared source memory accuracy under self-referential encoding and semantic encoding. Two types of source information were included, a "peripheral" source which was not inherent to the encoding activity, and a source information about the encoding context. We observed the facilitation in item memory from self-referential encoding compared to semantic encoding in recollection but not in familiarity-based memory. The self-referential benefit to source accuracy was observed in recollection memory, with source memory for the encoding context being stronger in the self-referential condition. No significant self-referential effect was observed with regards to peripheral source information (information not required for the participant to focus on), suggesting not all source information benefit from self-referential encoding. Self-referential encoding also resulted in a higher ratio of "Remember/Know" responses rate than semantically encoded items, denoting stronger recollection. These results suggest self-referential encoding creates a richer, more detailed memory trace which can be recollected later on.
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