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Respiration sustains metabolic activity in all organs, including the brain. Respiration protocols have been developed to manipulate mental states, including their use for therapeutic purposes, e.g., in anxiety disorders. In this systematic review, we discuss evidence that respiration may play a fundamental role in the coordination of neural activity, behavior, and emotion. The main findings are: (i) respiration affects the neural activity of a widespread variety of regions in the a brain; (in) respiration modulates different frequency ranges in the brain's dynamics; (iii) different respiration protocols (spontaneous, hyperventilation, slow or resonance respiration) yield different neural and mental effects; (iv) the effects of respiration on the brain are related to concurrent modulation of biochemical (oxygen delivery, pH) and physiological (cerebral blood flow, heart rate variability) variables. We conclude that respiration may be an integral rhythm of the brain's neural activity. This provides intimate connection of respiration with neuro-mental features like emotion. A respiratory-neuro-mental connection, in turn, holds the promise for a brain-based therapeutic usage of respiration in mental disorders.

Cognitive Reserve (CR) refers to the preservation of cognitive function in the face of age-or disease-related neuroanatomical decline. While bilingualism is known to contribute to CR, the extent to which, and what particular aspect of, second language experience contributes to CR are debated, and the underlying neural mechanism(s) unknown. Intrinsic functional connectivity reflects experience-dependent neuroplasticity that occurs across timescales ranging from minutes to decades, and may be a neural mechanism underlying CR. To test this hypothesis, we used voxel-based morphometry and resting-state functional connectivity analyses of MRI data to compare structural and functional brain integrity between bilingual and monolingual older adults, matched on cognitive performance using a rigorous propensity score matching technique, and across levels of second language proficiency measured as a continuous variable. Bilingualism, and degree of second language proficiency in particular, were associated with lower grey matter integrity in a hub of the default mode network – a region that is particularly vulnerable to decline in aging and dementia – but preserved functional network organization that resembled the young adult brain. Our findings confirm that lifelong bilingualism contributes to CR through experience-dependent maintenance of optimal functional network structure of the domain-general attentional control network across the lifespan.

Previous studies have reported bilingualism to be a proxy of cognitive reserve (CR) based on evidence that bilinguals express dementia symptoms ~ 4 years later than monolinguals yet present with greater neuropathology at time of diagnosis when clinical levels are similar. The current study provides new evidence supporting bilingualism's contribution to CR using a novel brain health matching paradigm. Forty cognitively normal bilinguals with diffusion-weighted magnetic resonance images recruited from the community were matched with monolinguals drawn from a pool of 165 individuals in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. White matter integrity was determined for all participants using fractional anisotropy, axial diffusivity, and radial diffusivity scores. Propensity scores were obtained using white matter measures, sex, age, and education as predictive covariates, and then used in one-to-one matching between language groups, creating a matched sample of 32 participants per group. Matched monolinguals had poorer clinical diagnoses than that predicted by chance from a theoretical null distribution, and poorer cognitive performances than matched bilinguals as measured by scores on the MMSE. The findings provide support for the interpretation that bilingualism acts as a proxy of CR such that monolinguals have poorer clinical and cognitive outcomes than bilinguals for similar levels of white matter integrity even before clinical symptoms appear.

A history of depression is a risk factor for dementia. Despite strong epidemiologic evidence, the pathways linking depression and dementia remain unclear. We assessed structural brain alterations in white and gray matter of frontal-executive and corticolimbic circuitries in five groups of older adults putatively at-risk for developing dementia- remitted depression (MDD), non-amnestic MCI (naMCI), MDD+naMCI, amnestic MCI (aMCI), and MDD+aMCI. We also examined two other groups: non-psychiatric (“healthy”) controls (HC) and individuals with Alzheimer’s dementia (AD). Magnetic resonance imaging (MRI) data were acquired on the same 3T scanner. Following quality control in these seven groups, from diffusion-weighted imaging (n = 300), we compared white matter fractional anisotropy (FA), mean diffusivity (MD), and from T1-weighted imaging (n = 333), subcortical volumes and cortical thickness in frontal-executive and corticolimbic regions of interest (ROIs). We also used exploratory graph theory analysis to compare topological properties of structural covariance networks and hub regions. We found main effects for diagnostic group in FA, MD, subcortical volume, and cortical thickness. These differences were largely due to greater deficits in the AD group and to a lesser extent aMCI compared with other groups. Graph theory analysis revealed differences in several global measures among several groups. Older individuals with remitted MDD and naMCI did not have the same white or gray matter changes in the frontal-executive and corticolimbic circuitries as those with aMCI or AD, suggesting distinct neural mechanisms in these disorders. Structural covariance global metrics suggested a potential difference in brain reserve among groups.

Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer′s disease at early stages. Predicting the exact stage of Alzheimer′s disease is challenging; however, complex deep learning techniques can manage this with precision. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer′s′ brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data. Our optimized architecture known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of 97%±0.0 and 99.55%±0.39 from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. The model was robust and repeatable, producing similar estimates across three runs (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer′s disease prediction.

Background: Neuroimaging findings in younger and older adults with major depressive disorder (MDD) are highly heterogeneous. It is unclear whether this heterogeneity is due to methodological limitations, lack of distinction between MDD and late-life depression (LLD), or clinical moderators. Methods: We identified all voxel-based and surface-based morphometry studies comparing younger adults with MDD or older adults with LLD to non-psychiatric control participants (updated search: Oct 27, 2020). We used both an Activation Likelihood Estimation (ALE) analysis and a novel coordinate-based network mapping to identify brain circuits affected in MDD and LLD. We then used meta-regressions to examine the impact of age of onset in older patients with LLD and treatment with antidepressants in younger patients with MDD. Results: We analysed 145 comparisons from 143 articles including 14,318 participants (MDD; 6,362; LDD: 535; controls: 7,421). Our ALE results confirmed previous findings implicating the bilateral parahippocampus (z RIGHT =5.2, z LEFT =4.3, p FWE

Mild cognitive impairment (MCI) of the amnestic type is considered to be a transitionary stage between healthy aging and Alzheimer’s disease (AD). Previous studies have demonstrated that intrinsic functional connectivity of the default network (DN) is altered in normal aging and AD and impacts both within and between network connectivity. While changes within the DN have been reported in MCI, it remains uncertain how interactions with other large-scale brain networks are altered in this prodromal stage of AD. We investigated within and between network connectivity in healthy older adults (HOAs) and older adults with MCI across three canonical brain networks: DN, dorsal attention network, and frontoparietal control network. We also assessed how patterns of functional connectivity among the three networks predicted cognitive status and age using multivariate partial least squares. A total of 91 MCI and 71 HOA restingstate scans were analyzed from the Alzheimer’s Disease Neuroimaging Initiative. There were three key findings. First, a circumscribed pattern of greater between network and interhemispheric connectivity was associated with higher cognitive status in HOAs. Second, for individuals with MCI, cognitive status was positively associated with a more distributed, less differentiated pattern of intrinsic functional connectivity across the three networks. Finally, greater within network functional connectivity was positively associated with cognitive status for HOAs irrespective of age, however this compensation-like effect diminished with increasing age for MCI participants. While reliable differences between healthy aging and MCI in the intrinsic network architecture of the brain are apparent, these differences emerge as shifting associations between network interactivity, cognitive functioning and age.

Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and dementia associated with Alzheimer's disease (AD). Early diagnosis of MCI and AD through artificial intelligence has captured considerable scholarly interest; researchers hope to develop therapies capable of slowing or halting these processes. We developed a state-of-the-art deep learning algorithm based on an optimized convolutional neural network (CNN) topology called MCADNNet that simultaneously recognizes MCI, AD, and normally aging brains in adults over the age of 75 years, using structural and functional magnetic resonance imaging (fMRI) data. Following highly detailed preprocessing, four-dimensional (4D) fMRI and 3D MRI were decomposed to create 2D images using a lossless transformation, which enables maximum preservation of data details. The samples were shuffled and subject-level training and testing datasets were completely independent. The optimized MCADNNet was trained and extracted invariant and hierarchical features through convolutional layers followed by multi-classification in the last layer using a softmax layer. A decision-making algorithm was also designed to stabilize the outcome of the trained models. To measure the performance of classification, the accuracy rates for various pipelines were calculated before and after applying the decision-making algorithm. Accuracy rates of 99.77% ± 0.36% and 97.5% ± 1.16% were achieved for MRI and fMRI pipelines, respectively, after applying the decision-making algorithm. In conclusion, a cutting-edge and optimized topology called MCADNNet was designed and preceded a preprocessing pipeline; this was followed by a decision-making step that yielded the highest performance achieved for simultaneous classification of the three cohorts examined.

Evidence suggests that bilingualism may contribute to neuroplasticity and cognitive reserve, allowing individuals to resist cognitive decline associated with Alzheimer’s disease progression, although the idea remains controversial. Here, we argue that the reason for the discrepancy stems from conflating incidence rates of dementia and the age at which the symptoms first appear, as well as statistical and methodological issues in the study designs. To clarify the issues, we conducted a comprehensive meta-analysis on the available literature regarding bilingualism and Alzheimer’s disease, including both retrospective and prospective studies, as well as age of onset and incidence rates. Results revealed a moderate effect size for the protective effect of bilingualism on age of onset of symptoms of Alzheimer’s disease (Cohen’s d = 0.32), and weaker evidence that bilingualism prevents the occurrence of disease incidence itself (Cohen’s d = 0.10). Moreover, our results cannot be explained by SES, education, or publication bias. We conclude with a discussion on how bilingualism contributes to cognitive reserve and protects against Alzheimer’s disease and recommend that future studies report both age of onset as well as incidence rates when possible.

Postmortem studies reveal that individuals with major neuropsychiatric disorders such as schizophrenia and autism spectrum disorder have gray matter microstructural abnormalities. These include abnormalities in neuropil organization, expression of proteins supporting neuritic and synaptic integrity, and myelination. Genetic and postmortem studies suggest that these changes may be causally linked to the pathogenesis of these disorders. Advances in diffusion-weighted magnetic resonance image (dMRI) acquisition techniques and biophysical modeling allow for the quantification of gray matter microstructure in vivo. While several biophysical models for imaging microstructural properties are available, one in particular, neurite orientation dispersion and density imaging (NODDI), holds great promise for clinical applications. NODDI can be applied to both gray and white matter and requires only a single extra shell beyond a standard dMRI acquisition. Since its development only a few years ago, the NODDI algorithm has been used to characterize gray matter microstructure in schizophrenia, Alzheimer’s disease, healthy aging, and development. These investigations have shown that microstructural findings in vivo, using NODDI, align with postmortem findings. Not only do NODDI and other advanced dMRI-based modeling methods provide a window into the brain previously only available postmortem, but they may be more sensitive to certain brain changes than conventional magnetic resonance imaging approaches. This opens up exciting new possibilities for clinicians to more rapidly detect disease signatures and allows earlier intervention in the course of the disease. Given that neurites and gray matter microstructure have the capacity to rapidly remodel, these novel dMRI-based methods represent an opportunity to noninvasively monitor neuroplastic changes posttherapy within much shorter time scales.

Evaluation of the cognitive level of older adults, including decisions about meeting clinical thresholds for dementia, is typically based on behavioral levels of performance. However, individuals with high cognitive reserve will outperform the levels typically associated with their brain structure, providing inaccurate assessments of their status. We define cognitive reserve as the relation between brain integrity and cognitive level, and use the case of bilingualism as a source of cognitive reserve to illustrate how information from only one can distort the interpretation of the individual’s cognitive status.

Building on our earlier analysis of the factorial structure of bilingualism for young adults obtained from the Language and Social Background Questionnaire (LSBQ; Anderson, Mak, Keyvani Chahi & Bialystok, 2018), we analyzed responses from 675 children and 125 older adults to a similar questionnaire. Three factors accounting for 74% of the variance emerged in the analysis of children's responses: Adult Language in the Home, Non-English use for Media, Non-English use with Siblings. There were also three factors that explained the responses of older adults that accounted for 79% of the variance: Non-English Use, Non-English Proficiency, and English Proficiency. Therefore, bilingual experience is captured by different factors at different points in the lifespan. These results are discussed in conjunction with the earlier results from young adults and the implications for understanding bilingualism across the lifespan.

This study compared brain and behavioral outcomes for monolingual and bilingual older adults who reported no cognitive or memory problems on three types of memory that typically decline in older age, namely, working memory (measured by n-back), item, and associative recognition. The results showed that bilinguals were faster on the two-back working memory task than monolinguals but used a set of frontostriatal regions less than monolinguals. There was no group difference on an item/associative recognition task. In brain structure, gray matter volume and white matter integrity (fractional anisotropy) were generally lower in bilinguals than in monolinguals, but bilinguals had better white matter integrity than monolinguals in the bilateral superior corona radiata and better gray matter density in the left inferior temporal gyrus. These regions may help preserve bilinguals’ executive functions despite generally more significant atrophy throughout the brain than monolinguals in that these structures contribute to efficient communication between executive frontal regions and subcortical motor regions, and perceptual pathways. Reliable negative correlations between brain structure and age were only observed in bilinguals, and to the extent that bilinguals (but not monolinguals) had better brain structure, their performance was enhanced. Collectively, the findings provide evidence for reserve in bilingual older adults.

Standardized neuropsychological tests are routinely used as diagnostic criteria in aging populations and are an important piece of evidence for the identification of clinical pathology and neurodegenerative conditions such as Alzheimer's disease. Tests include such measures as the Mini Mental Status Exam, Delis-Kaplan Executive Function System, Montreal Cognitive Assessment, and others. These tests cover a range of functions including working memory, verbal fluency, prospective memory, and task switching. Interpretation of test results is based on comparison of the participant's score to standard scores that have been normed on a population database. However, a growing body of research has shown that the skills underlying these tests may be significantly different in monolingual and bilingual older adults, especially for those experiencing cognitive impairment, yet the standardized test scores do not account for such differences. Therefore, results of neuropsychological tests may be different for bilingual populations than for monolinguals, and those differences may be misinterpreted. The issue is important because the consequences of these interpretative errors may be over- or under-diagnosis of cognitive impairment. The present study examined the neuropsychological test scores of monolingual and bilingual older adults who were experiencing healthy aging or cognitive impairment to establish patterns in these scores that can more accurately guide the interpretation for bilingual older adults by considering group differences in the underlying abilities.

Using implicit tests, older adults have been found to retain conceptual knowledge of previously seen task-irrelevant information. While younger adults typically do not show the same effect, evidence from one study [Gopie, N., Craik, F. I. M., & Hasher, L. (2011). A double dissociation of implicit and explicit memory in younger and older adults. Psychological Science, 22, 634–640. doi:10.1177/0956797611403321] suggests otherwise. In that study, young adults showed greater explicit than implicit memory for previous distractors on a word fragment completion task. This was interpreted as evidence for maintaining access to previous conceptual knowledge of the distractors. Here, we report two failures to replicate that original finding, followed by a third study designed to test directly whether young adults use conceptual-level information that was previously irrelevant. Our findings agree with others that young adults show weak to no evidence of conceptual knowledge of previously irrelevant information.

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.

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.

Testing older adults in the morning generally improves behavioral performance relative to afternoon testing. Morning testing is also associated with brain activity similar to that of young adults. Here, we used graph theory to explore how time of day (TOD) affects the organization of brain networks in older adults across rest and task states. We used nodes from the automated anatomical labeling atlas to construct participant-specific correlation matrices of fMRI data obtained during 1-back tasks with interference and rest. We computed pairwise group differences for key graph metrics, including small-worldness and modularity. We found that older adults tested in the morning and young adults did not differ on any graph metric. Both of these groups differed from older adults tested in the afternoon during the tasks—but not rest. Specifically, the latter group had lower modularity and small-worldness (indices of more efficient network organization). Across all groups, higher modularity and small-worldness strongly correlated with reduced distractibility on an implicit priming task. Increasingly, TOD is seen as important for interpreting and reproducing neuroimaging results. Our study emphasizes how TOD affects brain network organization and executive control in older adults.

We investigated sex differences in the association between a measure of physical health, cardiorespiratory fitness (CRF), and brain function using resting-state functional connectivity fMRI. We examined these sex differences in the default, frontoparietal control, and cingulo-opercular networks, assemblies of functionally connected brain regions known to be impacted by both age and fitness level. Healthy older adults ( n = 49; 29 women) were scanned to obtain measures of intrinsic connectivity within and across these 3 networks. We calculated global efficiency (a measure of network integration) and local efficiency (a measure of network specialization) using graph theoretical methods. Across all three networks combined, local efficiency was positively associated with CRF, and this was more robust in male versus female older adults. Furthermore, global efficiency was negatively associated with CRF, but only in males. Our findings suggest that in older adults, associations between brain network integrity and physical health are sex-dependent. These results underscore the importance of considering sex differences when examining associations between fitness and brain function in older adulthood. NEW & NOTEWORTHY We examined the association between cardiorespiratory fitness and resting state functional connectivity in several brain networks known to be impacted by age and fitness level. We found significant associations between fitness and measures of network integration and network specialization, but in a sex-dependent manner, highlighting the interplay between sex differences, fitness, and aging brain health. Our findings underscore the importance of considering sex differences when examining associations between fitness and brain function in older adulthood.

On a daily basis, we constantly deal with changing environmental cues and perceptual conflicts and as such, our brains must flexibly adapt to current demands in order to act appropriately. Brains become more efficient and are able to switch states more readily by increasing the complexity of their neural networks. However, it is unclear how brain signal complexity relates to behavior in young adults performing cognitively demanding executive function tasks. Here we used multiscale entropy analysis and multivariate statistics on EEG data while participants performed a bivalency effect task-switching paradigm to show that brain signal complexity in young adults increases as task demands increase, that increases in brain signal complexity are associated with both speed gains and losses depending on scalp location, and that more difficult tasks are associated with more circumscribed complexity across the scalp. Overall, these findings highlight a critical role for brain signal complexity in predicting behavior on an executive function task among young adults.

Neuroimaging studies have reported overlapping neural circuits for cognitive control when engaging in tasks that involve verbal and nonverbal stimuli in young adult bilinguals. However, no study to date has examined the neural basis of verbal and nonverbal task switching in both monolinguals and bilinguals due to the inherent challenge of testing verbal task switching with monolinguals. Therefore, it is not clear whether the finding for overlapping networks is unique to bilingualism or indicative of general cognitive control. To address this question, the current study compared functional neural activation for young adults who were bilingual speakers of English and French or monolingual English speakers who had limited French learning experience (“functional monolinguals”) on verbal and nonverbal task switching. Analyses showed common variance explaining general cognitive control in task switching across verbal and nonverbal domains for both groups, in line with the explanation that task switching involves general cognitive control, as well as unique brain regions recruited by monolinguals and bilinguals. Specifically, beyond the processing common to the tasks, monolinguals also recruited distinct networks for each of verbal and nonverbal switching but bilinguals used a common shared network. Thus, the domain-general aspect of switching is different for monolinguals and bilinguals.

The dynamic process of memory consolidation involves a reorganization of brain regions that support a memory trace over time, but exactly how the network reorganizes as the memory changes remains unclear. We present novel converging evidence from studies of animals (rats) and humans for the time-dependent reorganization and transformation of different types of memory as measured both by behavior and brain activation. We find that context-specific memories in rats, and naturalistic episodic memories in humans, lose precision over time and activity in the hippocampus decreases. If, however, the retrieved memories retain contextual or perceptual detail, the hippocampus is engaged similarly at recent and remote timepoints. As the interval between the timepoint increases, the medial prefrontal cortex is engaged increasingly during memory retrieval, regardless of the context or the amount of retrieved detail. Moreover, these hippocampal-frontal shifts are accompanied by corresponding changes in a network of cortical structures mediating perceptually-detailed as well as less precise, schematic memories. These findings provide cross-species evidence for the crucial interplay between hippocampus and neocortex that reflects changes in memory representation over time and underlies systems consolidation.

Bilingualism can delay the onset of dementia symptoms and has thus been characterized as a mechanism for cognitive or brain reserve, although the origin of this reserve is unknown. Studies with young adults generally show that bilingualism is associated with a strengthening of white matter, but there is conflicting evidence for how bilingualism affects white matter in older age. Given that bilingualism has been shown to help stave off the symptoms of dementia by up to four years, it is crucial that we clarify the mechanism underlying this reserve. The current study uses diffusion tensor imaging (DTI) to compare monolinguals and bilinguals while carefully controlling for potential confounds (e.g., I.Q., MMSE, and demographic variables). We show that group differences in Fractional Anisotropy (FA) and Radial Diffusivity (RD) arise from multivariable interactions not adequately controlled for by sequential bivariate testing. After matching and statistically controlling for confounds, bilinguals still had greater axial diffusivity (AD) in the left superior longitudinal fasciculus than monolingual peers, supporting a neural reserve account for healthy older bilinguals.

The objectives of this study were to provide an assessment of photographic documentation of the wound from the patients' perspective and to evaluate whether this could improve patients' understanding of and involvement in their wound care. Our results revealed that most patients visiting the wound care clinic have difficult-to-see wounds (86%). Only 20% of patients monitor their wounds and instead rely on clinic or nurse visits to track the healing progress. There was a significant association between patients' ability to see their wound and their subsequent memory of the wound's appearance. This was especially true for patients who had recently begun visiting the wound care clinic. This relationship was not present in patients who had visited the clinic for 3 or more years. Patients reported that the inability to see their wounds resulted in feeling a loss of autonomy. The majority of patients reported that photographing their wounds would help them to track the wound progress (81%) and would afford them more involvement in their own care (58%). This study provides a current representation of wound photography from the patients' perspective and reveals that it can motivate patients to become more involved in the management of their wounds - particularly for patients with difficult-to-see wounds.

1AbstractTo 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.

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.

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, 8 min 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.

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.

We assessed age differences in the ability to resolve competition for figural status in stationary displays using small, enclosed, symmetrical silhouettes that participants classified as depicting "novel" or "familiar" shapes. The silhouettes were biased such that the inside was perceived as the shaped figure, and the outside was perceived as a shapeless ground. The critical manipulation was whether a portion of a meaningful object was suggested on the outside of the border of some of the novel silhouettes but not others (M+Ground and M-Ground novel silhouettes, respectively). This manipulation was intended to induce greater inhibitory competition for figural status from the groundside in M+Ground silhouettes than M-Ground silhouettes. In previous studies, young adults classified M+Ground silhouettes as "novel" faster than M-Ground silhouettes (Trujillo, Allen, Schnyer, & Peterson, 2010), suggesting that young adults may recruit more inhibition to resolve figure-ground when there is more competition. We replicated this effect with young adults in the present study, but older adults showed the opposite pattern and were less accurate in classifying M+Ground than M-Ground silhouettes. These results extend the evidence for inhibitory deficits in older adults to figure assignment in stationary displays. The (M+Ground - M-Ground) RT differences were evident in observers' longest responses, consistent with the hypothesis that inhibitory deficits are evident when the need for inhibition is substantial.

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.

We examined the influence of emotional valence and type of item to be remembered on brain activity during recognition, using faces and scenes. We used multivariate analyses of event-related fMRI data to identify whole-brain patterns, or networks of activity. Participants demonstrated better recognition for scenes vs faces and for negative vs neutral and positive items. Activity was increased in extrastriate cortex and inferior frontal gyri for emotional scenes, relative to neutral scenes and all face types. Increased activity in these regions also was seen for negative faces relative to positive faces. Correct recognition of negative faces and scenes (hits vs correct rejections) was associated with increased activity in amygdala, hippocampus, extrastriate, frontal and parietal cortices. Activity specific to correctly recognized emotional faces, but not scenes, was found in sensorimotor areas and rostral prefrontal cortex. These results suggest that emotional valence and type of visual stimulus both modulate brain activity at recognition, and influence multiple networks mediating visual, memory and emotion processing. The contextual information in emotional scenes may facilitate memory via additional visual processing, whereas memory for emotional faces may rely more on cognitive control mediated by rostrolateral prefrontal regions.

verthepast2decades,significantadvancesinmagneticresonance imaging (MRI) techniques have opened anentirely new field of evaluating regions of neural activitybased on focal metabolic changes. Nuclear medicine studieswithsingle-photonemissiontomographyandpositronemis-sion tomography, over many years, have shown that areas ofbrain activity have increased blood flow, and the ability tomeasure increases in oxygen concentration allows detectionof these regions of activity. Correlating imaging with specificneural activity is referred to as brain mapping. The ability toobserve brain function with MRI during specific tasks andmore recently in the resting state is called functional mag-netic resonance imaging (fMRI).fMRI reveals short-term physiological changes associatedwith active brain functioning, and in this way, fMRI canidentifythedifferentpartsofthebrainwhereparticularmen-tal processes occur and can characterize the patterns of acti-vation associated with those processes. This is a dynamiccomplementary modality to the static structural informationobtainedfromconventionalMRI.fMRIhasanincreasingrolein preoperative planning with delineation of eloquent brainareas in relation to intracranial pathologies. Furthermore,fMRIhasprovidedabetterunderstandingoftheneuralbasisfor major psychiatric disorders, neurologic disorders, andsubstance abuse. Numerous functional studies have identi-fiedneuralprocessingdifferencesoralterationsinfunctionalconnectivity on MRI between patient groups and healthyindividuals, such as regarding Alzheimer’s disease.

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.