Metabolic and functional connectivity provide unique and complementary insights into cognition-connectome relationships.

A major challenge in current cognitive neuroscience is how functional brain connectivity gives rise to human cognition. Functional magnetic resonance imaging (fMRI) describes brain connectivity based on cerebral oxygenation dynamics (hemodynamic connectivity), whereas [18F]-fluorodeoxyglucose functional positron emission tomography (FDG-fPET) describes brain connectivity based on cerebral glucose uptake (metabolic connectivity), each providing a unique characterization of the human brain. How these 2 modalities differ in their contribution to cognition and behavior is unclear. We used simultaneous resting-state FDG-fPET/fMRI to investigate how hemodynamic connectivity and metabolic connectivity relate to cognitive function by applying partial least squares analyses. Results revealed that although for both modalities the frontoparietal anatomical subdivisions related the strongest to cognition, using hemodynamic measures this network expressed executive functioning, episodic memory, and depression, whereas for metabolic measures this network exclusively expressed executive functioning. These findings demonstrate the unique advantages that simultaneous FDG-PET/fMRI has to provide a comprehensive understanding of the neural mechanisms that underpin cognition and highlights the importance of multimodality imaging in cognitive neuroscience research.

The association between sex hormones and the change in brain-predicted age difference in older women.

OBJECTIVE: The role of circulating sex hormones on structural brain ageing is yet to be established. This study explored whether concentrations of circulating sex hormones in older women are associated with the baseline and longitudinal changes in structural brain ageing, defined by the brain-predicted age difference (brain-PAD). DESIGN: Prospective cohort study using data from NEURO and Sex Hormones in Older Women; substudies of the ASPirin in Reducing Events in the Elderly clinical trial. PATIENTS: Community-dwelling older women (aged 70+ years). MEASUREMENTS: Oestrone, testosterone, dehydroepiandrosterone (DHEA), and sex-hormone binding globulin (SHBG) were quantified from plasma samples collected at baseline. T1-weighted magnetic resonance imaging was performed at baseline, 1 and 3 years. Brain age was derived from whole brain volume using a validated algorithm. RESULTS: The sample comprised of 207 women not taking medications known to influence sex hormone concentrations. A statistically higher baseline brain-PAD (older brain age relative to chronological age) was seen for women in the highest DHEA tertile compared with the lowest in the unadjusted analysis (p = .04). This was not significant when adjusted for chronological age, and potential confounding health and behavioural factors. Oestrone, testosterone and SHBG were not associated with brain-PAD cross-sectionally, nor were any of the examined sex hormones or SHBG associated with brain-PAD longitudinally. CONCLUSION: No strong evidence of an association between circulating sex hormones and brain-PAD. Given there is prior evidence to suggests sex hormones may be important for brain ageing, further studies of circulating sex hormones and brain health in postmenopausal women are warranted.

Neuroprotective Effects of Motherhood on Brain Function in Late Life: A Resting-State fMRI Study.

The maternal brain undergoes structural and functional plasticity during pregnancy and the postpartum period. Little is known about functional plasticity outside caregiving-specific contexts and whether changes persist across the lifespan. Structural neuroimaging studies suggest that parenthood may confer a protective effect against the aging process; however, it is unknown whether parenthood is associated with functional brain differences in late life. We examined the relationship between resting-state functional connectivity and number of children parented in 220 healthy older females (73.82 ± 3.53 years) and 252 healthy older males (73.95 ± 3.50 years). We compared the patterns of resting-state functional connectivity with 3 different models of age-related functional change to assess whether these effects may be functionally neuroprotective for the aging human parental brain. No relationship between functional connectivity and number of children was obtained for males. For females, we found widespread decreasing functional connectivity with increasing number of children parented, with increased segregation between networks, decreased connectivity between hemispheres, and decreased connectivity between anterior and posterior regions. The patterns of functional connectivity related to the number of children an older woman has parented were in the opposite direction to those usually associated with age-related cognitive decline, suggesting that motherhood may be beneficial for brain function in late life.

Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study.

Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain-glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of "connectivity," only across-subject "covariance." Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.

Estimation of simultaneous BOLD and dynamic FDG metabolic brain activations using a multimodality concatenated ICA (mcICA) method.

Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analysing the simultaneously acquired blood-oxygen-level dependant functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyse cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.

Factors associated with brain ageing - a systematic review.

BACKGROUND: Brain age is a biomarker that predicts chronological age using neuroimaging features. Deviations of this predicted age from chronological age is considered a sign of age-related brain changes, or commonly referred to as brain ageing. The aim of this systematic review is to identify and synthesize the evidence for an association between lifestyle, health factors and diseases in adult populations, with brain ageing. METHODS: This systematic review was undertaken in accordance with the PRISMA guidelines. A systematic search of Embase and Medline was conducted to identify relevant articles using search terms relating to the prediction of age from neuroimaging data or brain ageing. The tables of two recent review papers on brain ageing were also examined to identify additional articles. Studies were limited to adult humans (aged 18 years and above), from clinical or general populations. Exposures and study design of all types were also considered eligible. RESULTS: A systematic search identified 52 studies, which examined brain ageing in clinical and community dwelling adults (mean age between 21 to 78 years, ~ 37% were female). Most research came from studies of individuals diagnosed with schizophrenia or Alzheimer's disease, or healthy populations that were assessed cognitively. From these studies, psychiatric and neurologic diseases were most commonly associated with accelerated brain ageing, though not all studies drew the same conclusions. Evidence for all other exposures is nascent, and relatively inconsistent. Heterogenous methodologies, or methods of outcome ascertainment, were partly accountable. CONCLUSION: This systematic review summarised the current evidence for an association between genetic, lifestyle, health, or diseases and brain ageing. Overall there is good evidence to suggest schizophrenia and Alzheimer's disease are associated with accelerated brain ageing. Evidence for all other exposures was mixed or limited. This was mostly due to a lack of independent replication, and inconsistency across studies that were primarily cross sectional in nature. Future research efforts should focus on replicating current findings, using prospective datasets. TRIAL REGISTRATION: A copy of the review protocol can be accessed through PROSPERO, registration number CRD42020142817 .

Analysis of continuous infusion functional PET (fPET) in the human brain.

Functional positron emission tomography (fPET) is a neuroimaging method involving continuous infusion of 18-F-fluorodeoxyglucose (FDG) radiotracer during the course of a PET examination. Compared with the conventional bolus administration of FDG in a static PET scan, which provides an average glucose uptake into the brain over an extended period of up to 30 â€‹min, fPET offers a significantly higher temporal resolution to study the dynamics of glucose uptake. Several earlier studies have applied fPET to investigate brain FDG uptake and study its relationship with functional magnetic resonance imaging (fMRI). However, due to the unique characteristics of fPET signals, modelling of the fPET signal is a complex task and poses challenges for accurate interpretation of the results from fPET experiments. This study applied independent component analysis (ICA) to analyse resting state fPET data, and to compare the performance of ICA and the general linear model (GLM) for estimation of brain activation in response to tasks. The fPET signal characteristics were compared using GLM and ICA methods to model fPET data from a visual activation experiment. Our aim was to evaluate GLM and ICA methods for analysing task fPET datasets, and to apply ICA methods to the analysis of resting state fPET datasets. Using both simulation and in-vivo experimental datasets, we show that both ICA and GLM methods can successfully identify task related brain activation. We report fPET metabolic resting state brain networks revealed by application of the fPET ICA method to a cohort of 28 healthy subjects. Functional PET provides a unique method to map dynamic changes of glucose uptake in the resting human brain and in response to extrinsic stimulation.

Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition.

Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentration of oxygenated and deoxygenated haemoglobin cause fluctuations in the MRI T2* signal. Since the BOLD signal detects changes in relative concentrations of oxy/deoxy-haemoglobin, individual differences in haemoglobin levels may influence the BOLD signal-to-noise ratio in a manner independent of the degree of neural activity. In this study, we examined whether group differences in haemoglobin may confound measures of functional connectivity. We investigated whether relationships between measures of functional connectivity and cognitive performance could be influenced by individual variability in haemoglobin. Finally, we mapped the neuroanatomical distribution of the influence of haemoglobin on functional connectivity to determine where group differences in functional connectivity are manifest. In a cohort of 518 healthy elderly subjects (259 men), each sex group was median-split into two groups with high and low haemoglobin concentration. Significant differences were obtained in functional connectivity between the high and low haemoglobin groups for both men and women (Cohen's d 0.17 and 0.03 for men and women respectively). The haemoglobin connectome in males showed a widespread systematic increase in functional connectivity correlation values, whilst the female connectome showed predominantly parietal and subcortical increases and temporo-parietal decreases. Despite the haemoglobin groups having no differences in cognitive measures, significant differences in the linear relationships between cognitive performance and functional connectivity were obtained for all 5 cognitive tests in males, and 4 out of 5 tests in females. Our findings confirm that individual variability in haemoglobin levels that give rise to group differences are an important confounding variable in BOLD-fMRI-based studies of functional connectivity. Controlling for haemoglobin variability as a potentially confounding variable is crucial to ensure the reproducibility of human brain connectome studies, especially in studies that compare groups of individuals, compare sexes, or examine connectivity-cognition relationships.

Simultaneous task-based BOLD-fMRI and [18-F] FDG functional PET for measurement of neuronal metabolism in the human visual cortex.

Studies of task-evoked brain activity are the cornerstone of cognitive neuroscience, and unravel the spatial and temporal brain dynamics of cognition in health and disease. Blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI) is one of the most common methods of studying brain function in humans. BOLD-fMRI indirectly infers neuronal activity from regional changes in blood oxygenation and is not a quantitative metric of brain function. Regional variation in glucose metabolism, measured using [18-F] fluorodeoxyglucose positron emission tomography (FDG-PET), provides a more direct and interpretable measure of neuronal activity. However, while the temporal resolution of BOLD-fMRI is in the order of seconds, standard FDG-PET protocols provide a static snapshot of glucose metabolism. Here, we develop a novel experimental design for measurement of task-evoked changes in regional blood oxygenation and glucose metabolism with high temporal resolution. Over a 90-min simultaneous BOLD-fMRI/FDG-PET scan, [18F] FDG was constantly infused to 10 healthy volunteers, who viewed a flickering checkerboard presented in a hierarchical block design. Dynamic task-related changes in blood oxygenation and glucose metabolism were examined with temporal resolution of 2.5sec and 1-min, respectively. Task-related, temporally coherent brain networks of haemodynamic and metabolic connectivity were jointly coupled in the visual cortex, as expected. Results demonstrate that the hierarchical block design, together with the infusion FDG-PET technique, enabled both modalities to track task-related neural responses with high temporal resolution. The simultaneous MR-PET approach has the potential to provide unique insights into the dynamic haemodynamic and metabolic interactions that underlie cognition in health and disease.

Longitudinal evaluation of iron concentration and atrophy in the dentate nuclei in friedreich ataxia.

BACKGROUND: Friedreich ataxia is a recessively inherited, progressive neurological disease characterized by impaired mitochondrial iron metabolism. The dentate nuclei of the cerebellum are characteristic sites of neurodegeneration in the disease, but little is known of the longitudinal progression of abnormalities in these structures. METHODS: Using in vivo magnetic resonance imaging, including quantitative susceptibility mapping, we investigated changes in iron concentration and volume in the dentate nuclei in individuals with Friedreich ataxia (n = 20) and healthy controls (n = 18) over a 2-year period. RESULTS: The longitudinal rate of iron concentration was significantly elevated bilaterally in participants with Friedreich ataxia relative to healthy controls. Atrophy rates did not differ significantly between groups. Change in iron concentration and atrophy both correlated with baseline disease severity or duration, indicating sensitivity of these measures to disease stage. Specifically, atrophy was maximal in individuals early in the disease course, whereas the rate of iron concentration increased with disease progression. CONCLUSIONS: Progressive dentate nucleus abnormalities are evident in vivo in Friedreich ataxia, and the rates of change of iron concentration and atrophy in these structures are sensitive to the disease stage. The findings are consistent with an increased rate of iron concentration and atrophy early in the disease, followed by iron accumulation and stable volume in later stages. This pattern suggests that iron dysregulation persists after loss of the vulnerable neurons in the dentate. The significant changes observed over a 2-year period highlight the utility of quantitative susceptibility mapping as a longitudinal biomarker and staging tool. © 2019 International Parkinson and Movement Disorder Society.

Combining images and anatomical knowledge to improve automated vein segmentation in MRI.

PURPOSE: To improve the accuracy of automated vein segmentation by combining susceptibility-weighted images (SWI), quantitative susceptibility maps (QSM), and a vein atlas to produce a resultant image called a composite vein image (CV image). METHOD: An atlas was constructed in common space from manually traced MRI images from ten volunteers. The composite vein image was derived for each subject as a weighted sum of three inputs; an SWI image, a QSM image and the vein atlas. The weights for each input and each anatomical location, called template priors, were derived by assessing the accuracy of each input over an independent data set. The accuracy of vein segmentations derived automatically from each of the CV image, SWI, and QSM image sets was assessed by comparison with manual tracings. Three different automated vein segmentation techniques were used, and ten performance metrics evaluated. RESULTS: Vein segmentations using the CV image were comprehensively better than those derived from SWI or QSM images (mean Cohen's d = 1.1). Sixty permutations of performance metric, benchmark image, and automated segmentation technique were evaluated. Vein identification improvements that were both large and significant (Cohen's d > 0.80, p < 0.05) were found in 77% of the permutations, compared to no improvement in 5%. CONCLUSION: The accuracy of automated vein segmentations derived from the composite vein image was overwhelmingly superior to segmentations derived from SWI or QSM alone.

Physical activity surveillance in parks using direct observation.

INTRODUCTION: Primary features of observational public health surveillance instruments are that they are valid, can reliably estimate physical activity behaviors, and are useful across diverse geographic settings and seasons by different users. Previous studies have reported the validity and reliability of Systematic Observation of Play and Recreation in Communities (SOPARC) to estimate park and user characteristics. The purpose of this investigation was to establish the use of SOPARC as a surveillance instrument and to situate the findings from the study in the context of the previous literature. METHODS: We collected data by using SOPARC for more than 3 years in 4 locations: Philadelphia, Pennsylvania; Columbus, Ohio; Chapel Hill/Durham, North Carolina; and Albuquerque, New Mexico during spring, summer, and autumn. RESULTS: We observed a total of 35,990 park users with an overall observer reliability of 94% (range, 85%-99%) conducted on 15% of the observations. We monitored the proportion of park users engaging in moderate-to-vigorous physical activity (MVPA) and found marginal differences in MVPA by both city and season. Park users visited parks significantly more on weekend days than weekdays and visitation rates tended to be lower during summer than spring. CONCLUSION: SOPARC is a highly reliable observation instrument that can be used to collect data across diverse geographic settings and seasons by different users and has potential as a surveillance system.

Dual attention based fusion network for MCI Conversion Prediction.

Alzheimer's disease (AD) severely impacts the lives of many patients and their families. Predicting the progression of the disease from the early stage of mild cognitive impairment (MCI) is of substantial value for treatment, medical research and clinical trials. In this paper, we propose a novel dual attention network to classify progressive MCI (pMCI) and stable MCI (sMCI) using both magnetic resonance imaging (MRI) and neurocognitive metadata. A 3D CNN ShuffleNet V2 model is used as the network backbone to extract MRI image features. Then, neurocognitive metadata is used to guide the spatial attention mechanism to steer the model to focus attention on the most discriminative regions of the brain. In contrast to traditional fusion methods, we propose a ViT based self attention fusion mechanism to fuse the neurocognitive metadata with the 3D CNN feature maps. The experimental results show that our proposed model achieves an accuracy, AUC, and sensitivity of 81.34%, 0.874, and 0.85 respectively using 5-fold cross validation evaluation. A comprehensive experimental study shows our proposed approach significantly outperforms all previous methods for MCI progression classification. In addition, an ablation study shows both fusion methods contribute to the high final performance.

Participation and physical activity in organized recess tied to physical education in elementary schools: An interventional study.

Maintaining physical activity habits is important for long-term health benefits. Many children do not achieve the World Health Organization (WHO) benchmark of 60 min Moderate-to-Vigorous Physical Activity (MVPA) daily. Comprehensive school physical activity programs (CSPAP) target all opportunities at school for children to be physically active. The purpose of this intervention study was to investigate boys' and girls' voluntary participation and MVPA in physical activity recess sessions during and after these were connected with the content of physical education. 147 (55 girls, 92 boys; mean age = 8 years) second grade children from seven different schools received a 10-lesson parkour unit in physical education and were concurrently offered five parkour recess sessions. After the parkour unit in physical education (i.e., maintenance) another five parkour sessions in which children could voluntarily participate were organized. Systematic observation tools were used to assess children's MVPA. Overall participation in parkour recess was 64% for both boys and girls. Participation decreased from intervention to maintenance phase for both boys (75% vs 54%; p < .001) and girls (80% vs 49%; p < .001). MVPA was higher for boys compared to girls in parkour recess (64% vs 58%; p = .002) and traditional recess (49% vs 39%; p = .006), but not in physical education (40% vs 37%). One aspect of physical activity promotion is to connect recess activities with the content taught in physical education, which could contribute up to 20% of the daily recommended MVPA. Positive effects maintained when the connection between physical education and recess stopped.

Class activation attention transfer neural networks for MCI conversion prediction.

Accurate prediction of the trajectory of Alzheimer's disease (AD) from an early stage is of substantial value for treatment and planning to delay the onset of AD. We propose a novel attention transfer method to train a 3D convolutional neural network to predict which patients with mild cognitive impairment (MCI) will progress to AD within 3 years. A model is first trained on a separate but related source task (task we are transferring information from) to automatically learn regions of interest (ROI) from a given image. Next we train a model to simultaneously classify progressive MCI (pMCI) and stable MCI (sMCI) (the target task we want to solve) and the ROIs learned from the source task. The predicted ROIs are then used to focus the model's attention on certain areas of the brain when classifying pMCI versus sMCI. Thus, in contrast to traditional transfer learning, we transfer attention maps instead of transferring model weights from a source task to the target classification task. Our Method outperformed all methods tested including traditional transfer learning and methods that used expert knowledge to define ROI. Furthermore, the attention map transferred from the source task highlights known Alzheimer's pathology.

The Role of Content Knowledge in Influencing Student Physical Activity, On-Task Behavior, and Skill Performance.

Purpose: The purpose of this study was to compare the impact of interventions aimed at improving teacher's content knowledge on students' MVPA, on-task behavior, and skill performance. Differences between treatment and comparison groups were further examined by skill level and gender. Method: We conducted a retroactive analysis of teacher and student data from two randomly controlled trials and one well-controlled quasi-experimental trial measuring MVPA, student performance in badminton, and on-task behavior in lessons. We used descriptive and ANOVA analyses to determine our results. Results: The data show statistically significant effects for student performance and MVPA, and statistically significant effects for on-task performance between groups. Effect sizes for student performance exceed 1SD. MVPA for two of the three studies exceeded the 50% of the lesson criterion. Data are reported for high, average and low skilled students for each variable. Conclusions: This is the first study to examine three important outcomes of physical education, namely skill performance, MVPA, and on-task behavior in one investigation. Our results show that multiple objectives in physical education can be achieved. A strength of the study is that we did not sample any of our variables. The data represent a complete picture of every trial, and continuous interval recording for MVPA and on-task variables occurring in each lesson.

The maternal brain is more flexible and responsive at rest: effective connectivity of the parental caregiving network in postpartum mothers.

The field of neuroscience has largely overlooked the impact of motherhood on brain function outside the context of responses to infant stimuli. Here, we apply spectral dynamic causal modelling (spDCM) to resting-state fMRI data to investigate differences in brain function between a group of 40 first-time mothers at 1-year postpartum and 39 age- and education-matched women who have never been pregnant. Using spDCM, we investigate the directionality (top-down vs. bottom-up) and valence (inhibition vs excitation) of functional connections between six key left hemisphere brain regions implicated in motherhood: the dorsomedial prefrontal cortex, ventromedial prefrontal cortex, posterior cingulate cortex, parahippocampal gyrus, amygdala, and nucleus accumbens. We show a selective modulation of inhibitory pathways related to differences between (1) mothers and non-mothers, (2) the interactions between group and cognitive performance and (3) group and social cognition, and (4) differences related to maternal caregiving behaviour. Across analyses, we show consistent disinhibition between cognitive and affective regions suggesting more efficient, flexible, and responsive behaviour, subserving cognitive performance, social cognition, and maternal caregiving. Together our results support the interpretation of these key regions as constituting a parental caregiving network. The nucleus accumbens and the parahippocampal gyrus emerging as 'hub' regions of this network, highlighting the global importance of the affective limbic network for maternal caregiving, social cognition, and cognitive performance in the postpartum period.

Brain susceptibility imaging provides valuable in vivo insights into cerebellar diseases, but biological interpretations remain elusive.

This scientific commentary relates to: 'Quantitative susceptibility mapping reveals alterations of dentate nuclei in common types of degenerative cerebellar ataxias' by Deistung et al. (https://doi.org/10.1093/braincomms/fcab306).

Evidence of Subjective, But Not Objective, Cognitive Deficit in New Mothers at 1-Year Postpartum.

Background: The experience and even existence of cognitive deficits in the postpartum period is uncertain, with only a few scientific studies, reporting inconsistent results. Methods: In this study, we investigate cognition in 86 women (43 first-time mothers 1 year postpartum and 43 non-mothers). Results: Mothers and non-mothers showed no significant differences on measures of objective cognition (verbal memory, working memory, and processing speed or theory of mind). Despite the absence of objective differences, mothers self-reported significantly worse subjective memory than non-mothers. To interpret the difference between objective and subjective measures of memory, we investigated relationships between subjective memory, objective memory, and wellbeing. Mothers, but not non-mothers, showed a positive correlation between subjective and objective measures of memory, indicating mothers are "in-tune" with their memory performance. Mothers also demonstrated a positive relationship between subjective memory and wellbeing (sleep, anxiety, and depression), where better wellbeing correlated with higher subjective memory. This relationship was not apparent in non-mothers. The results suggest that poorer sleep, higher anxiety, and higher depression are related to reports of poorer self-reported memory in mothers. Conclusion: Our results add to our growing understanding of maternal cognition at 1 year postpartum, with no evidence of cognitive differences between mothers and non-mothers.