Age-related differences in the structural complexity of subcortical and ventricular structures

Accurate identification of individuals with subjective cognitive decline using 3D regional fractal dimensions on structural magnetic resonance imaging

BACKGROUND AND OBJECTIVE

Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD.

METHODS

This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions.

RESULTS

The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations.

CONCLUSION

Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

Brain age of rhesus macaques over the lifespan

Through the application of machine learning algorithms to neuroimaging data the brain age methodology was shown to provide a useful individual-level biological age prediction and identify key brain regions responsible for the prediction. In this study, we present the methodology of constructing a rhesus macaque brain age model using a machine learning algorithm and discuss the key predictive brain regions in comparison to the human brain, to shed light on cross-species primate similarities and differences. Structural information of the brain (e.g., parcellated volumes) from brain magnetic resonance imaging of 43 rhesus macaques were used to develop brain atlas-based features to build a brain age model that predicts biological age. The best-performing model used 22 selected features and achieved an R2 of 0.72. We also identified interpretable predictive brain features including Right Fronto-orbital Cortex, Right Frontal Pole, Right Inferior Lateral Parietal Cortex, and Bilateral Posterior Central Operculum. Our findings provide converging evidence of the parallel and comparable brain regions responsible for both non-human primates and human biological age prediction.

Structural brain morphometry differences and similarities between young patients with Crohn's disease in remission and healthy young and old controls

Introduction

Crohn's disease (CD), one of the main phenotypes of inflammatory bowel disease (IBD), can affect any part of the gastrointestinal tract. It can impact the function of gastrointestinal secretions, as well as increasing the intestinal permeability leading to an aberrant immunological response and subsequent intestinal inflammation. Studies have reported anatomical and functional brain changes in Crohn's Disease patients (CDs), possibly due to increased inflammatory markers and microglial cells that play key roles in communicating between the brain, gut, and systemic immune system. To date, no studies have demonstrated similarities between morphological brain changes seen in IBD and brain morphometry observed in older healthy controls..

Methods

For the present study, twelve young CDs in remission (M = 26.08 years, SD = 4.9 years, 7 male) were recruited from an IBD Clinic. Data from 12 young age-matched healthy controls (HCs) (24.5 years, SD = 3.6 years, 8 male) and 12 older HCs (59 years, SD = 8 years, 8 male), previously collected for a different study under a similar MR protocol, were analyzed as controls. T1 weighted images and structural image processing techniques were used to extract surface-based brain measures, to test our hypothesis that young CDs have different brain surface morphometry than their age-matched young HCs and furthermore, appear more similar to older HCs. The phonemic verbal fluency (VF) task (the Controlled Oral Word Association Test, COWAT) (Benton, 1976) was administered to test verbal cognitive ability and executive control.

Results/Discussion

On the whole, CDs had more brain regions with differences in brain morphometry measures when compared to the young HCs as compared to the old HCs, suggesting that CD has an effect on the brain that makes it appear more similar to old HCs. Additionally, our study demonstrates this atypical brain morphometry is associated with function on a cognitive task. These results suggest that even younger CDs may be showing some evidence of structural brain changes that demonstrate increased resemblance to older HC brains rather than their similarly aged healthy counterparts.

Changes in the volumes and asymmetry of subcortical structures in healthy individuals according to gender

In recent years, with the development of technology, three-dimensional software has entered our lives. Volumetric measurements made with Magnetic Resonance Imaging (MRI) are essential in the morphometry of the brain and subcortical structures. In this study, we aim to share the volume and asymmetry of the hippocampus, its sub-branches, and other subcortical structures and their interaction with age/sex using volBrain, a web-based automated software.1.5 T T1-weighted volumetric MRI, of 90 healthy individuals (51 females, 39 males) of both genders were included in our study. Pallidum, hippocampus, Cornu Ammonis1 (CA1), Cornu Ammonis2-3 (CA2-CA3), and Cornu Ammonis4-Dentate Gyrus (CA4-DG) measurements in females and males had a statistically higher mean in the right region (p < 0.05). In addition, females' hippocampus, CA1, CA2-CA3, and CA4-DG averages decreased more rapidly in the right region than in the left region. Subiculum measurement had a higher mean in the left region in both males and females (p < 0.05).The mean subiculum of males decreased more rapidly in the right region than in the left region. When the total values of the subcortical region in males and females were compared according to age categories, amygdala, pallidum, putamen, hippocampus, CA2-CA3, and subiculum values did not differ to gender in individuals aged 50 and over (p > 0.05). In individuals under 50 years old, the mean of females was statistically lower than the mean of males (p < 0.05).The Stratum radiatum (SR), Stratum lacunosum (SL), and Stratum molecuare (SM) asymmetry values of males in the examined subcortical regions had a higher mean than females (p = 0.039). In other regions, there was no statistically asymmetrical difference (p > 0.05). Studies evaluating the volumetric analysis and asymmetry of hippocampus subbranches and other subcortical structures in adults are very limited. As a result, the morphometry of the hippocampus subbranches and other subcortical structures was examined in detail. It was determined that the structures differed according to age, gender and body side.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Using fractal dimension analysis to assess the effects of normal aging and sex on subregional cortex alterations across the lifespan from a Chinese dataset

Fractal dimension (FD) is used to quantify brain structural complexity and is more sensitive to morphological variability than other cortical measures. However, the effects of normal aging and sex on FD are not fully understood. In this study, age- and sex-related differences in FD were investigated in a sample of 448 adults age of 19–80 years from a Chinese dataset. The FD was estimated with the surface-based morphometry (SBM) approach, sex differences were analyzed on a vertex level, and correlations between FD and age were examined. Generalized additive models (GAMs) were used to characterize the trajectories of age-related changes in 68 regions based on the Desikan–Killiany atlas. The SBM results showed sex differences in the entire sample and 3 subgroups defined by age. GAM results demonstrated that the FD values of 51 regions were significantly correlated with age. The trajectories of changes can be classified into 4 main patterns. Our results indicate that sex differences in FD are evident across developmental stages. Age-related trajectories in FD are not homogeneous across the cerebral cortex. Our results extend previous findings and provide a foundation for future investigation of the underlying mechanism.

Longitudinal Effects of Combination Antiretroviral Therapy on Cognition and Neuroimaging Biomarkers in Treatment-Naïve People with HIV

BACKGROUND AND OBJECTIVES

While combination antiretroviral therapy (cART) has dramatically increased the life expectancy of people with HIV (PWH), nearly 50% develop HIV-associated neurocognitive disorders (HAND)¹. This may be due to previously uncontrolled HIV viral replication, immune activation maintained by residual viral replication² or activation from other sources^{3, 4}, or cART-associated neurotoxicity⁵. The aim of this study was to determine the effect of cART on cognition and neuroimaging biomarkers markers in people with HIV (PWH) before and after initiation of cART compared to HIV negative controls (HC) and HIV elite controllers (EC) who remain untreated.

METHODS

We recruited three groups of participants from the University of Rochester, McGovern Medical School and SUNY Upstate Medical University: 1) ART-treatment-naïve PWH; 2) age-matched HC; and 3) EC. Participants underwent brain MRI and clinical and neuropsychological assessments at baseline, one year, and two years. PWH were also assessed 12 weeks after initiating cART. Volumetric analysis and fractal dimensionality (FD) were calculated for cortical and subcortical regions. Mixed effect regressions examined the effect of group and imaging variables on cognition.

RESULTS

We enrolled 47 PWH, 58 HC, and 10 EC. At baseline, PWH had worse cognition and lower cortical volumes than HC. Cognition improved following initiation of cART and remained stable over time. Greater cortical thickness was associated with better cognition at baseline; greater FD of parietal, temporal and occipital lobes was associated with better cognition at baseline and longitudinally. At baseline, EC had worse cognition, lower cortical thickness and lower FD in all four lobes and caudate than PWH and HC. Greater cortical thickness, hippocampal volumes and FD of frontal, temporal and occipital lobes were associated with better cognition longitudinally.

CONCLUSIONS

Initiation of cART in PWH is associated with improvement in brain structure and cognition. However, significant differences persist over time compared to HC. Similar trends in EC suggest that results are due to HIV infection rather than treatment. Stronger associations between cognition and FD suggest this imaging metric may be a more sensitive marker of neuronal injury than cortical thickness and volumetric measures.

Scan Once, Analyse Many: Using Large Open-Access Neuroimaging Datasets to Understand the Brain

We are now in a time of readily available brain imaging data. Not only are researchers now sharing data more than ever before, but additionally large-scale data collecting initiatives are underway with the vision that many future researchers will use the data for secondary analyses. Here I provide an overview of available datasets and some example use cases. Example use cases include examining individual differences, more robust findings, reproducibility-both in public input data and availability as a replication sample, and methods development. I further discuss a variety of considerations associated with using existing data and the opportunities associated with large datasets. Suggestions for further readings on general neuroimaging and topic-specific discussions are also provided.

Changes of cerebral cortical structure and cognitive dysfunction in "healthy hemisphere" after stroke: a study about cortical complexity and sulcus patterns in bilateral ischemic adult moyamoya disease

Background

Moyamoya disease (MMD) is an uncommon cerebrovascular disease which leads to progressive stenosis and occlusion of the bilateral internal carotid artery and main intracerebral arteries. Concerns are always on how the hemisphere with infarction affects cognitive function, while little attention is paid to the role that the non-infarcted hemisphere plays. Therefore, we aimed to detect cortical indexes, especially cortical complexity in the left or right hemisphere separately in patients with MMD after stroke.

Methods

28 patients with MMD (14 males, 14 females) and 14 healthy controls were included in this study. All participants underwent cognitive tests and magnetic resonance imaging (MRI) scan. The preprocessing of three-dimensional T1 weighted images were performed by standard surface-based morphometry. Surface-based morphometry statistical analysis was carried out with a threshold of False Discovery Rate (FDR) P < 0.05 and fractal dimension (FD) was used to provide a quantitative description of cerebral cortical complexity.

Results

Widespread cognitive dysfunctions were found in MMD patient with stroke. Extensive FD reduction in the left hemisphere with right-sided infarction, mainly in the superior temporal, inferior frontal, and insula, while the post central gyrus, superior parietal, and inferior parietal gyrus also showed a wide range of significant differences (FDR corrected P < 0.05). Meanwhile, FD changes in the right hemisphere with left-sided infarction are restricted to the precuneus and cingulate isthmus (FDR corrected P < 0.05).

Conclusions

Extensive cognitive impairment was reconfirmed in Moyamoya disease with stroke, while wild and asymmetrical decrease of cortical complexity is observed on both sides. These differences could be relative to unbalanced cognitive dysfunction, and may be the result of a long-term chronic ischemia and compensatory of the contralateral hemisphere to the infarction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12868-021-00672-x.

Beyond volumetry: Considering age-related changes in brain shape complexity using fractal dimensionality

Gray matter volume for cortical, subcortical, and ventricles all vary with age. However, these volumetric changes do not happen on their own, there are also age-related changes in cortical folding and other measures of brain shape. Fractal dimensionality has emerged as a more sensitive measure of brain structure, capturing both volumetric and shape-related differences. For subcortical structures it is readily apparent that segmented structures do not differ in volume in isolation-adjacent regions must also vary in shape. Fractal dimensionality here also appears to be more sensitive to these age-related differences than volume. Given these differences in structure are quite prominent in structure, caution should be used when examining comparisons across age in brain function measures, as standard normalisation methods are not robust enough to adjust for these inter-individual differences in cortical structure.

Structural complexity is negatively associated with brain activity: a novel multimodal test of compensation theories of aging

Fractal dimensionality (FD) measures the complexity within the folds and ridges of cortical and subcortical structures. We tested the degree that FD might provide a new perspective on the atrophy-compensation hypothesis: age or disease-related atrophy causes a compensatory neural response in the form of increased brain activity in the prefrontal cortex to maintain cognition. Brain structural and functional data were collected from 63 middle-aged and older adults and 18 young-adult controls. Two distinct patterns of FD were found that separated cortical from subcortical structures. Subcortical FD was more strongly negatively correlated with age than cortical FD, and cortical FD was negatively associated with brain activity during memory retrieval in medial and lateral parietal cortices uniquely in middle-aged and older adults. Multivariate analyses revealed that the lower FD/higher brain activity pattern was associated with poorer cognition-patterns not present in young adults, consistent with compensation. Bayesian analyses provide further evidence against the modal interpretation of the atrophy-compensation hypothesis in the prefrontal cortex-a key principle found in some neurocognitive theories of aging.

Age-related differences in myeloarchitecture measured at 7 T

We have used the magnetisation transfer (MT) MRI measure as a primary measure of myelination in both the gray matter (GM) of the 78 cortical automated anatomical labeling (AAL) regions of the brain, and the underlying white matter in each region, in a cohort of healthy adults (aged 19-62 year old). The results revealed a significant quadratic trend in myelination with age, with average global myelination peaking at 42.9 year old in gray matter, and at 41.7 year old in white matter. We also explored the possibility of using the Nuclear Overhauser Enhancement (NOE) effect, which is acquired in a similar method to MT, as an additional measure of myelination. We found that the MT and NOE signals were strongly correlated in the brain and that the NOE effects displayed similar (albeit weaker) parabolic trends with age. We also investigated differences in cortical thickness with age, and confirmed a previous result of a linear decline of 4.5 ± 1.2 μm/y.

Cortical Complexity in Anorexia Nervosa: A Fractal Dimension Analysis

Fractal Dimension (FD) has shown to be a promising means to describe the morphology of cortical structures across different neurologic and psychiatric conditions, displaying a good sensitivity in capturing atrophy processes. In this study, we aimed at exploring the morphology of cortical areas by means of FD in 58 female patients with Anorexia Nervosa (AN) (38 currently underweight and 20 fully recovered) and 38 healthy controls (HC). All participants underwent high-resolution MRI. Surface extraction was completed using FreeSurfer, FD was computed using the calcFD toolbox. The whole cortex mean FD value was lower in acute AN patients compared to HC (p < 0.001). Recovered AN patients did not show differences in the global FD when compared to HC. However, some brain areas showed higher FD in patients than controls, while others showed the opposite pattern. Parietal regions showed lower FD in both AN groups. In acute AN patients, the FD correlated with age (p < 0.001), body mass index (p = 0.019) and duration of illness (p = 0.011). FD seems to represent a feasible method to explore cortical complexity in patients with AN since it demonstrated to be sensitive to the effects of both severity and duration of malnutrition.

Reduced Cortical Complexity in Cirrhotic Patients with Minimal Hepatic Encephalopathy

Purpose

Gray matter volume loss, regional cortical thinning, and local gyrification index alteration have been documented in minimal hepatic encephalopathy (MHE). Fractal dimension (FD), another morphological parameter, has been widely used to describe structural complexity alterations in neurological or psychiatric disease. Here, we conducted the first study to investigate FD alterations in MHE.

Methods and Materials

We performed high-resolution structural magnetic resonance imaging on cirrhotic patients with MHE (n = 20) and healthy controls (n = 21). We evaluated their cognitive performance using the psychometric hepatic encephalopathy score (PHES). The regional FD value was calculated by Computational Anatomy Toolbox (CAT12) and compared between groups. We further estimated the association between patients' cognitive performance and FD values.

Results

MHE patients presented significantly decreased FD values in the left precuneus, left supramarginal gyrus, right caudal anterior cingulate cortex, right isthmus cingulate cortex, right insula, bilateral pericalcarine cortex, and bilateral paracentral cortex compared to normal controls. In addition, the FD values in the right isthmus cingulate cortex and right insula were shown to be positively correlated with patients' cognitive performance.

Conclusion

Aberrant cortical complexity is an additional characteristic of MHE, and FD analysis may provide novel insight into the neurobiological basis of cognitive dysfunction in MHE.

Differential longitudinal changes in structural complexity and volumetric measures in community-dwelling older individuals

Fractal geometry provides a method of analyzing natural and especially biological morphologies. To investigate the relationship between the complexity measure, which is indexed as fractal dimensionality (FD), and the traditional Euclidean metrics, such as the volume and thickness, of the brain in older age, we analyzed 483 MRI scans of 161 community-dwelling, nondemented individuals aged 70-90 years at the baseline and their 2-year and 6-year follow-ups. We quantified changes in neuroimaging metrics in cortical lobes and subcortical structures and investigated the effects of age, sex, hemisphere, and education on FD. We also analyzed the mediating effects of these metrics for further investigation. FD showed significant age-related decline in all structures, and its trajectory was best modeled quadratically in the bilateral frontal, parietal, and occipital lobes, as well as in the bilateral caudate, putamen, hippocampus, amygdala, and accumbens. FD showed specific mediating effects on aging and cognitive decline in some regions. Our findings suggest that FD is reliable yet shows a different pattern of decline compared with volumetric measures.

Particle Swarm Optimization for Positioning the Coil of Transcranial Magnetic Stimulation

The distribution of the induced electric field (E-field) during transcranial magnetic stimulation (TMS) depends on the individual anatomical structure of the brain as well as coil positioning. Inappropriate stimulation may degrade the efficacy of TMS or even induce adverse effects. Therefore, optimizing the E-field according to individual anatomy and clinical need has become a research focus. In this paper, particle swarm optimization (PSO) was applied for the first time to the positioning of TMS coils with anatomical head models. We discuss the parameters of the PSO algorithm, which were optimized to achieve a reasonable convergence time suitable for in-time treatment planning. The optimizer improved the distribution of the induced E-field strength at the dedicated cortical region, with a mean value of 48.31% compared with that from the conventional treatment position. The optimization terminated after 4–11 iterations for 13 head models. The applicability and performance of the optimizer for a large population are discussed in terms of cortical complexity. This study could benefit not only clinics but also research on brain modulation.

Of fractal and Fourier: A measure for local shape complexity for neurological applications

BACKGROUND

Local shape complexity can be biologically meaningful as a marker of disease, trauma, or change in brain structure over time. Fractal dimensionality (FD) is currently the dominant measure of local shape complexity used in neuroimaging but its limitations are not well understood.

NEW METHOD

Elliptical Fourier harmonic power requirement (HPR) may provide complementary information to FD. We benchmarked the performance of FD and HPR on a series of simulated shapes, systematically manipulating aspects of local shape complexity, and a series of clinical contours (glioma tumour cores and stroke lesions from the BRATS and ATLAS datasets). HPR was calculated as the point of 99.9% harmonic power. FD was calculated at six resolutions (8 × 8, 16 × 16, 32 × 32, 64 × 64, 128 × 128, and 256 × 256), by using an approach which computationally indexes the complexity of the shape boundary (i.e. the number of cells defining the contour) relative to the total grid size.

RESULTS AND COMPARISON WITH EXISTING METHODS

PR and FD were moderately positively correlated (r ≈ 0.2 to 0.8 depending on shape properties), and both were sensitive to the frequency and amplitude of local complexity. FD was most biased by rotation, while HPR was more biased by global shape features such as deep invaginations. FD indicated an aggregate measure of complexity across the whole contour, while HPR indicated the point of highest complexity.

CONCLUSIONS

The HPR index provides conceptually distinct local complexity information from the current FD standard. Future research will benefit from using these complementary measures.

Shape-related characteristics of age-related differences in subcortical structures

OBJECTIVES

With an increasing aging population, it is important to understand biological markers of aging. Subcortical volume is known to differ with age; additionally considering shape-related characteristics may provide a better index of age-related differences. Fractal dimensionality is more sensitive to age-related differences, but is borne out of mathematical principles, rather than neurobiological relevance. We considered four distinct measures of shape and how they relate to aging and fractal dimensionality: surface-to-volume ratio, sphericity, long-axis curvature, and surface texture.

METHODS

Structural MRIs from a combined sample of over 600 healthy adults were used to measure age-related differences in the structure of the thalamus, putamen, caudate, and hippocampus. For each, volume and fractal dimensionality were calculated, as well as four distinct shape measures. These measures were examined for their utility in explaining age-related variability in brain structure.

RESULTS

The four shape measures were able to account for 80%-90% of the variance in fractal dimensionality. Of the distinct shape measures, surface-to-volume ratio was the most sensitive biomarker.

CONCLUSION

Though volume is often used to characterize inter-individual differences in subcortical structures, our results demonstrate that additional measures can be useful complements. Our results indicate that shape characteristics are useful biological markers of aging.

Robust estimation of sulcal morphology

While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here we developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test–retest reliability of the approach. This toolbox is now made freely available as supplemental to this paper: https://cmadan.github.io/calcSulc/.

Age differences in head motion and estimates of cortical morphology

Cortical morphology is known to differ with age, as measured by cortical thickness, fractal dimensionality, and gyrification. However, head motion during MRI scanning has been shown to influence estimates of cortical thickness as well as increase with age. Studies have also found task-related differences in head motion and relationships between body–mass index (BMI) and head motion. Here I replicated these prior findings, as well as several others, within a large, open-access dataset (Centre for Ageing and Neuroscience, CamCAN). This is a larger dataset than these results have been demonstrated previously, within a sample size of more than 600 adults across the adult lifespan. While replicating prior findings is important, demonstrating these key findings concurrently also provides an opportunity for additional related analyses: critically, I test for the influence of head motion on cortical fractal dimensionality and gyrification; effects were statistically significant in some cases, but small in magnitude.

Age is reflected in the Fractal Dimensionality of MRI Diffusion Based Tractography

Fractal analysis is a widely used tool to analyze the geometrical complexity of biological structures. The geometry of natural objects such as plants, clouds, cellular structures, blood vessel, and many others cannot be described sufficiently with Euclidian geometric properties, but can be represented by a parameter called the fractal dimension. Here we show that a specific estimate of fractal dimension, the correlation dimension, is able to describe changes in the structural complexity of the human brain, based on data from magnetic resonance diffusion imaging. White matter nerve fiber bundles, represented by tractograms, were analyzed with regards to geometrical complexity, using fractal geometry. The well-known age-related change of white matter tissue was used to verify changes by means of fractal dimension. Structural changes in the brain were successfully be observed and quantified by fractal dimension and compared with changes in fractional anisotropy.

The Association of Aging and Aerobic Fitness With Memory

The present study examined the differential effects of aging and fitness on memory. Ninety-five young adults (YA) and 81 older adults (OA) performed the Mnemonic Similarity Task (MST) to assess high-interference memory and general recognition memory. Age-related differences in high-interference memory were observed across the lifespan, with performance progressively worsening from young to old. In contrast, age-related differences in general recognition memory were not observed until after 60 years of age. Furthermore, OA with higher aerobic fitness had better high-interference memory, suggesting that exercise may be an important lifestyle factor influencing this aspect of memory. Overall, these findings suggest different trajectories of decline for high-interference and general recognition memory, with a selective role for physical activity in promoting high-interference memory.

Predicting age from cortical structure across the lifespan

Despite interindividual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. This study assessed how accurately an individual's age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from one region to 1000 regions. The age prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated nonlinear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology.

Test-retest reliability of brain morphology estimates

Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.

Selective vulnerabilities and biomarkers in neurocognitive aging

As the world's population continues to age, an understanding of the aging brain becomes increasingly crucial. This review focuses on several recent ideas and findings in the study of neurocognitive aging, specifically focusing on episodic memory, and discusses how they can be considered and used to guide us moving forward. Topics include dysfunction in neural circuits, the roles of neurogenesis and inhibitory signaling, vulnerability in the entorhinal cortex, individual differences, and comorbidities. These avenues of study provide a brief overview of promising themes in the field and together provide a snapshot of what we believe will be important emerging topics in selective vulnerabilities in the aging brain.

Mindcontrol: A web application for brain segmentation quality control

Tissue classification plays a crucial role in the investigation of normal neural development, brain-behavior relationships, and the disease mechanisms of many psychiatric and neurological illnesses. Ensuring the accuracy of tissue classification is important for quality research and, in particular, the translation of imaging biomarkers to clinical practice. Assessment with the human eye is vital to correct various errors inherent to all currently available segmentation algorithms. Manual quality assurance becomes methodologically difficult at a large scale - a problem of increasing importance as the number of data sets is on the rise. To make this process more efficient, we have developed Mindcontrol, an open-source web application for the collaborative quality control of neuroimaging processing outputs. The Mindcontrol platform consists of a dashboard to organize data, descriptive visualizations to explore the data, an imaging viewer, and an in-browser annotation and editing toolbox for data curation and quality control. Mindcontrol is flexible and can be configured for the outputs of any software package in any data organization structure. Example configurations for three large, open-source datasets are presented: the 1000 Functional Connectomes Project (FCP), the Consortium for Reliability and Reproducibility (CoRR), and the Autism Brain Imaging Data Exchange (ABIDE) Collection. These demo applications link descriptive quality control metrics, regional brain volumes, and thickness scalars to a 3D imaging viewer and editing module, resulting in an easy-to-implement quality control protocol that can be scaled for any size and complexity of study.

Curcuma longa L. extract improves the cortical neural connectivity during the aging process

Turmeric or Curcuma is a natural product that has anti-inflammatory, antioxidant and anti-apoptotic pharmacological properties. It can be used in the control of the aging process that involves oxidative stress, inflammation, and apoptosis. Aging is a physiological process that affects higher cortical and cognitive functions with a reduction in learning and memory, limited judgment and deficits in emotional control and social behavior. Moreover, aging is a major risk factor for the appearance of several disorders such as cerebrovascular disease, diabetes mellitus, and hypertension. At the brain level, the aging process alters the synaptic intercommunication by a reduction in the dendritic arbor as well as the number of the dendritic spine in the pyramidal neurons of the prefrontal cortex, hippocampus and basolateral amygdala, consequently reducing the size of these regions. The present review discusses the synaptic changes caused by the aging process and the neuroprotective role the Curcuma has through its anti-inflammatory, antioxidant and anti-apoptotic actions