John A. E. Anderson

A Multivariate Analysis of Age-Related Differences in Default Mode and Task-Positive Networks across Multiple Cognitive Domains

We explored the effects of aging on 2 large-scale brain networks, the default mode network (DMN) and the task-positive network (TPN). During functional magnetic resonance imaging scanning, young and older participants carried out 4 visual tasks: detection, perceptual matching, attentional cueing, and working memory. Accuracy of performance was roughly matched at 80% across tasks and groups. Modulations of activity across conditions were assessed, as well as functional connectivity of both networks. Younger adults showed a broader engagement of the DMN and older adults a more extensive engagement of the TPN. Functional connectivity in the DMN was reduced in older adults, whereas the main pattern of TPN connectivity was equivalent in the 2 groups. Age-specific connectivity also was seen in TPN regions. Increased activity in TPN areas predicted worse accuracy on the tasks, but greater expression of a connectivity pattern associated with a right dorsolateral prefrontal TPN region, seen only in older adults, predicted better performance. These results provide further evidence for age-related differences in the DMN and new evidence of age differences in the TPN. Increased use of the TPN may reflect greater demand on cognitive control processes in older individuals that may be partially offset by alterations in prefrontal functional connectivity.

Distinct neural correlates for two types of inhibition in bilinguals: Response inhibition versus interference suppression

To examine the effects of bilingualism on cognitive control, we studied monolingual and bilingual young adults performing a flanker task with functional MRI. The trial types of primary interest for this report were incongruent and no-go trials, representing interference suppression and response inhibition, respectively. Response times were similar between groups. Brain data were analyzed using partial least squares (PLS) to identify brain regions where activity covaried across conditions. Monolinguals and bilinguals activated different sets of brain regions for congruent and incongruent trials, but showed activation in the same regions for no-go trials. During the incongruent trials, monolinguals activated the left temporal pole and left superior parietal regions. In contrast, an extensive network including bilateral frontal, temporal and subcortical regions was active in bilinguals during the incongruent trials and in both groups for the no-go trials. Correlations between brain activity and reaction time difference relative to neutral trials revealed that monolinguals and bilinguals showed increased activation in different brain regions to achieve less interference from incongruent flankers. Results indicate that bilingualism selectively affects neural correlates for suppressing interference, but not response inhibition. Moreover, the neural correlates associated with more efficient suppression of interference were different in bilinguals than in monolinguals, suggesting a bilingual-specific network for cognitive control.

Timing is everything: Age differences in the cognitive control network are modulated by time of day.

Behavioral evidence suggests that the attention-based ability to regulate distraction varies across the day in synchrony with a circadian arousal rhythm that changes across the life span. Using functional magnetic resonance imaging (fMRI), we assessed whether neural activity in an attention control network also varies across the day and with behavioral markers. We tested older adults in the morning or afternoon and younger adults tested in the afternoon using a 1-back task with superimposed distractors, followed by an implicit test for the distractors. Behavioral results replicated earlier findings with older adults tested in the morning better able to ignore distraction than those tested in the afternoon. Imaging results showed that time of testing modulates task-related fMRI signals in older adults and that age differences were reduced when older adults are tested at peak times of day. In particular, older adults tested in the morning activated similar cognitive control regions to those activated by young adults (rostral prefrontal and superior parietal cortex), whereas older adults tested in the afternoon were reliably different; furthermore, the degree to which participants were able to activate the control regions listed above correlated with the ability to suppress distracting information.

Neural correlates of cognitive processing in monolinguals and bilinguals

Here, we review the neural correlates of cognitive control associated with bilingualism. We demonstrate that lifelong practice managing two languages orchestrates global changes to both the structure and function of the brain. Compared with monolinguals, bilinguals generally show greater gray matter volume, especially in perceptual/motor regions, greater white matter integrity, and greater functional connectivity between gray matter regions. These changes complement electroencephalography findings showing that bilinguals devote neural resources earlier than monolinguals. Parallel functional findings emerge from the functional magnetic resonance imaging literature: bilinguals show reduced frontal activity, suggesting that they do not need to rely on top‐down mechanisms to the same extent as monolinguals. This shift for bilinguals to rely more on subcortical/posterior regions, which we term the bilingual anterior‐to‐posterior and subcortical shift (BAPSS), fits with results from cognitive aging studies and helps to explain why bilinguals experience cognitive decline at later stages of development than monolinguals.

DeepAD: Alzheimer′s Disease Classification via Deep Convolutional Neural Networks using MRI and fMRI

To extract patterns from neuroimaging data, various statistical methods and machine learning algorithms have been explored for the diagnosis of Alzheimer’s disease among older adults in both clinical and research applications; however, distinguishing between Alzheimer’s and healthy brain data has been challenging in older adults (age > 75) due to highly similar patterns of brain atrophy and image intensities. Recently, cutting-edge deep learning technologies have rapidly expanded into numerous fields, including medical image analysis. This paper outlines state-of-the-art deep learning-based pipelines employed to distinguish Alzheimer’s magnetic resonance imaging (MRI) and functional MRI (fMRI) from normal healthy control data for a given age group. Using these pipelines, which were executed on a GPU-based high-performance computing platform, the data were strictly and carefully preprocessed. Next, scale- and shift-invariant low- to high-level features were obtained from a high volume of training images using convolutional neural network (CNN) architecture. In this study, fMRI data were used for the first time in deep learning applications for the purposes of medical image analysis and Alzheimer’s disease prediction. These proposed and implemented pipelines, which demonstrate a significant improvement in classification output over other studies, resulted in high and reproducible accuracy rates of 99.9% and 98.84% for the fMRI and MRI pipelines, respectively. Additionally, for clinical purposes, subject-level classification was performed, resulting in an average accuracy rate of 94.32% and 97.88% for the fMRI and MRI pipelines, respectively. Finally, a decision making algorithm designed for the subject-level classification improved the rate to 97.77% for fMRI and 100% for MRI pipelines.

The language and social background questionnaire: Assessing degree of bilingualism in a diverse population

Research examining the cognitive consequences of bilingualism has expanded rapidly in recent years and has revealed effects on aspects of cognition across the lifespan. However, these effects are difficult to find in studies investigating young adults. One problem is that there is no standard definition of bilingualism or means of evaluating degree of bilingualism in individual participants, making it difficult to directly compare the results of different studies. Here, we describe an instrument developed to assess degree of bilingualism for young adults who live in diverse communities in which English is the official language. We demonstrate the reliability and validity of the instrument in analyses based on 408 participants. The relevant factors for describing degree of bilingualism are: (1) the extent of non-English language proficiency and use at home, and (2) non-English language use socially. We then use the bilingualism scores obtained from the instrument to demonstrate their association with: (1) performance on executive function tasks, and (2) previous classifications of participants into categories of monolinguals and bilinguals.

Laterality effects in functional connectivity of the angular gyrus during rest and episodic retrieval.

INTRODUCTION The angular gyrus (AG) is consistently reported in neuroimaging studies of episodic memory retrieval and is a fundamental node within the default mode network (DMN). Its specific contribution to episodic memory is debated, with some suggesting it is important for the subjective experience of episodic recollection, rather than retrieval of objective episodic details. Across studies of episodic retrieval, the left AG is recruited more reliably than the right. We explored functional connectivity of the right and left AG with the DMN during rest and retrieval to assess whether connectivity could provide insight into the nature of this laterality effect. METHODS Using data from the publically available 1000 Functional Connectome Project, 8min of resting fMRI data from 180 healthy young adults were analysed. Whole-brain functional connectivity at rest was measured using a seed-based Partial Least Squares (seed-PLS) approach (McIntosh and Lobaugh, 2004) with bilateral AG seeds. A subsequent analysis used 6-min of rest and 6-min of unconstrained, silent retrieval of autobiographical events from a new sample of 20 younger adults. Analysis of this dataset took a more targeted approach to functional connectivity analysis, consisting of univariate pairwise correlations restricted to nodes of the DMN. RESULTS The seed-PLS analysis resulted in two Latent Variables that together explained ~86% of the shared cross-block covariance. The first LV revealed a common network consistent with the DMN and engaging the AG bilaterally, whereas the second LV revealed a less robust, yet significant, laterality effect in connectivity - the left AG was more strongly connected to the DMN. Univariate analyses of the second sample again revealed better connectivity between the left AG and the DMN at rest. However, during retrieval the left AG was more strongly connected than the right to non-medial temporal (MTL) nodes of the DMN, and MTL nodes were more strongly connected to the right AG. DISCUSSION The multivariate analysis of resting connectivity revealed that the left and right AG show similar connectivity with the DMN. Only after accounting for this commonality were we able to detect a left laterality effect in DMN connectivity. Further probing with univariate connectivity analyses during retrieval demonstrates that the left preference we observe is restricted to the non-MTL regions of the DMN, whereas the right AG shows significantly better connectivity with the MTL. These data suggest bilateral involvement of the AG during retrieval, despite the focus on the left AG in the literature. Furthermore, the results suggest that the contribution of the left AG to retrieval may be separable from that of the MTL, consistent with a role for the left AG in the subjective aspects of recollection in memory, whereas the MTL and the right AG may contribute to objective recollection of specific memory details.

Age differences in the neural correlates of distraction regulation: a network interaction approach

Older adults show decrements in the ability to ignore or suppress distraction relative to younger adults. However, age differences in the neural correlates of distraction control and the role of large-scale network interaction in regulating distractors are scarcely examined. In the current study, we investigated age differences in how the anticorrelation between an externally oriented dorsal attention network (DAN) and an internally focused default mode network (DMN) is related to inhibiting distractors presented during a 1-back working memory task. For both young and older adults, the extent of DAN-DMN anticorrelation predicted reduced distractibility. Activation in a common set of frontal and insular control regions during the task was, however, associated with opposite patterns of network interaction and distractibility in the age groups. For older adults, recruitment of these regions was associated with greater DAN-DMN anticorrelation and less distractibility (better performance). For younger adults, it was associated with decreased DAN-DMN anticorrelation and more distractibility (worse performance). Our findings demonstrate the age-dependent relationship between DAN-DMN interaction patterns and engagement of control regions during an externally oriented distraction control task. This suggests that engagement of those regions may play a compensatory role for older adults but may be indicative of less efficient neural control mechanisms in younger adults.

Point-of-care wound visioning technology: Reproducibility and accuracy of a wound measurement app

Background Current wound assessment practices are lacking on several measures. For example, the most common method for measuring wound size is using a ruler, which has been demonstrated to be crude and inaccurate. An increase in periwound temperature is a classic sign of infection but skin temperature is not always measured during wound assessments. To address this, we have developed a smartphone application that enables non-contact wound surface area and temperature measurements. Here we evaluate the inter-rater reliability and accuracy of this novel point-of-care wound assessment tool. Methods and findings The wounds of 87 patients were measured using the Swift Wound app and a ruler. The skin surface temperature of 37 patients was also measured using an infrared FLIR™ camera integrated with the Swift Wound app and using the clinically accepted reference thermometer Exergen DermaTemp 1001. Accuracy measurements were determined by assessing differences in surface area measurements of 15 plastic wounds between a digital planimeter of known accuracy and the Swift Wound app. To evaluate the impact of training on the reproducibility of the Swift Wound app measurements, three novice raters with no wound care training, measured the length, width and area of 12 plastic model wounds using the app. High inter-rater reliabilities (ICC = 0.97–1.00) and high accuracies were obtained using the Swift Wound app across raters of different levels of training in wound care. The ruler method also yielded reliable wound measurements (ICC = 0.92–0.97), albeit lower than that of the Swift Wound app. Furthermore, there was no statistical difference between the temperature differences measured using the infrared camera and the clinically tested reference thermometer. Conclusions The Swift Wound app provides highly reliable and accurate wound measurements. The FLIR™ infrared camera integrated into the Swift Wound app provides skin temperature readings equivalent to the clinically tested reference thermometer. Thus, the Swift Wound app has the advantage of being a non-contact, easy-to-use wound measurement tool that allows clinicians to image, measure, and track wound size and temperature from one visit to the next. In addition, this tool may also be used by patients and their caregivers for home monitoring.

Bilinguals have more complex EEG brain signals in occipital regions than monolinguals

Abstract Brain signal complexity increases with development and is associated with better cognitive outcomes in older age. Research has also shown that bilinguals are able to stave off cognitive decline for longer periods of time than monolinguals, but no studies to date have examined whether bilinguals have more complex brain signals than monolinguals. Here we explored the hypothesis that bilingualism leads to greater brain signal complexity by examining multiscale entropy (MSE) in monolingual and bilingual young adults while EEG was recorded during a task‐switching paradigm. Results revealed that bilinguals had greater brain signal complexity than monolinguals in occipital regions. Furthermore, bilinguals performed better with increasing occipital brain signal complexity, whereas monolinguals relied on coupling with frontal regions to demonstrate gains in performance. These findings are discussed in terms of how a lifetime of experience with a second language leads to more automatic and efficient processing of stimuli and how these adaptations could contribute to the prevention of cognitive decline in older age. HighlightsBrain signal complexity varies with age and disease and reflects cognitive level.Multiscale entropy (MSE) derived from EEG measures indexes signal complexity.Higher complexity is associated with higher cognitive level.Young adult monolinguals and bilinguals performed similarly on a switching task.Bilinguals showed higher MSE than monolinguals in occipital electrodes.