Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer's disease

Temporal tau asymmetry spectrum influences divergent behavior and language patterns in Alzheimer's disease

Understanding the psychiatric symptoms of Alzheimer s disease (AD) is crucial for advancing precision medicine and therapeutic strategies. The relationship between AD behavioral symptoms and asymmetry in spatial tau PET patterns is not well-known. Braak tau progression implicates the temporal lobes early. However, the clinical and pathological implications of temporal tau laterality remain unexplored. This cross-sectional study investigated the correlation between temporal tau PET asymmetry and behavior assessed using the neuropsychiatric inventory and composite scores for memory, executive function, and language, using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In the entire cohort, continuous right and left temporal tau contributions to behavior and cognition were evaluated, controlling for age, sex, education, and tau burden on the contralateral side. Additionally, a temporal tau laterality index was calculated to define "asymmetry-extreme" groups (individuals with laterality indices greater than two standard deviations from the mean). 695 individuals (age = 73.9 ± 7.6 years, 372 (53.5 %) females) were included, comprising 281 (40%) cognitively unimpaired (CU) amyloid negative, 185 (27%) CU amyloid positive, and 229 (33%) impaired (CI) amyloid positive participants. In the full cohort analysis, right temporal tau was associated with worse behavior (B = 8.14, p-value = 0.007), and left temporal tau was associated with worse language (B = 1.4, p-value < 0.001). Categorization into asymmetry-extreme groups revealed 20 right- and 27 left-asymmetric participants. Within these extreme groups, there was additional heterogeneity along the anterior-posterior dimension. Asymmetrical tau burden is associated with distinct behavioral and cognitive profiles. Wide multi-cultural implementation of social cognition measures is needed to understand right-sided asymmetry in AD.

Investigation of hemispheric asymmetry in Alzheimer's disease patients during resting state revealed BY fNIRS

Alzheimer's disease (AD) is characterized by the gradual deterioration of brain structures and changes in hemispheric asymmetry. Meanwhile, healthy aging is associated with a decrease in functional hemispheric asymmetry. In this study, functional connectivity analysis was used to compare the functional hemispheric asymmetry in eyes-open resting-state fNIRS data of 16 healthy elderly controls (mean age: 60.4 years, MMSE (Mini-Mental State Examination): 27.3 ± 2.52) and 14 Alzheimer's patients (mean age: 73.8 years, MMSE: 22 ± 4.32). Increased interhemispheric functional connectivity was found in the premotor cortex, supplementary motor cortex, primary motor cortex, inferior parietal cortex, primary somatosensory cortex, and supramarginal gyrus in the control group compared to the AD group. The study revealed that the control group had stronger interhemispheric connectivity, leading to a more significant decrease in hemispheric asymmetry than the AD group. The results show that there is a difference in interhemispheric functional connections at rest between the Alzheimer's group and the control group, suggesting that functional hemispheric asymmetry continues in Alzheimer's patients.

Cognitive deficits and cortical volume loss in COVID-19-related hyposmia

BACKGROUND AND PURPOSE

Studies have found that up to 73% of COVID-19 patients experience hyposmia. It is unclear if the loss of smell in COVID-19 is due to damage to the peripheral or central mechanisms. This study aimed to explore the impacts of COVID-19-induced hyposmia on brain structure and cognitive functions.

METHODS

The study included 36 hyposmic (h-COV) and 21 normosmic (n-COV) participants who had recovered from mild COVID-19 infection, as well as 25 healthy controls (HCs). All participants underwent neurological examination, neuropsychiatric assessment and Sniffin' Sticks tests. High-resolution anatomical images were collected; olfactory bulb (OB) volume and cortical thickness were measured.

RESULTS

Addenbrooke's Cognitive Examination-Revised total and language sub-scores were slightly but significantly lower in the h-COV group compared to the HC group (p = 0.04 and p = 0.037). The h-COV group exhibited poorer performance in the Sniffin' Sticks test terms of discrimination score, identification score and the composite score compared to the n-COV and HC groups (p < 0.001, p = 0.001 and p = 0.002 respectively). A decrease in left and right OB volumes was observed in the h-COV group compared to the n-COV and HC groups (p = 0.003 and p = 0.006 respectively). The cortical thickness analysis revealed atrophy in the left lateral orbitofrontal cortex in the h-COV group compared to HCs. A significant low positive correlation of varying degrees was detected between discrimination and identification scores and both OB and left orbital sulci.

CONCLUSION

Temporary or permanent hyposmia after COVID-19 infection leads to atrophy in the OB and olfactory-related cortical structures and subtle cognitive problems in the long term.

Clinical implications of brain asymmetries

No two human brains are alike, and with the rise of precision medicine in neurology, we are seeing an increased emphasis on understanding the individual variability in brain structure and function that renders every brain unique. Functional and structural brain asymmetries are a fundamental principle of brain organization, and recent research suggests substantial individual variability in these asymmetries that needs to be considered in clinical practice. In this Review, we provide an overview of brain asymmetries, variations in such asymmetries and their relevance in the clinical context. We review recent findings on brain asymmetries in neuropsychiatric and neurodevelopmental disorders, as well as in specific learning disabilities, with an emphasis on large-scale database studies and meta-analyses. We also highlight the relevance of asymmetries for disease symptom onset in neurodegenerative diseases and their implications for lateralized treatments, including brain stimulation. We conclude that alterations in brain asymmetry are not sufficiently specific to act as diagnostic biomarkers but can serve as meaningful symptom or treatment response biomarkers in certain contexts. On the basis of these insights, we provide several recommendations for neurological clinical practice.

Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline

Introduction

Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent.

Methods

To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus.

Results

SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD.

Discussion

The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.

DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data

Voxel-based multiple testing is widely used in neuroimaging data analysis. Traditional false discovery rate (FDR) control methods often ignore the spatial dependence among the voxel-based tests and thus suffer from substantial loss of testing power. While recent spatial FDR control methods have emerged, their validity and optimality remain questionable when handling the complex spatial dependencies of the brain. Concurrently, deep learning methods have revolutionized image segmentation, a task closely related to voxel-based multiple testing. In this paper, we propose DeepFDR, a novel spatial FDR control method that leverages unsupervised deep learning-based image segmentation to address the voxel-based multiple testing problem. Numerical studies, including comprehensive simulations and Alzheimer's disease FDG-PET image analysis, demonstrate DeepFDR's superiority over existing methods. DeepFDR not only excels in FDR control and effectively diminishes the false nondiscovery rate, but also boasts exceptional computational efficiency highly suited for tackling large-scale neuroimaging data.

Gray matter volume in women with the BRCA mutation with and without ovarian removal: evidence for increased risk of late-life Alzheimer's disease or dementia

OBJECTIVE

Ovarian removal prior to spontaneous/natural menopause (SM) is associated with increased risk of late life dementias including Alzheimer's disease. This increased risk may be related to the sudden and early loss of endogenous estradiol. Women with breast cancer gene mutations (BRCAm) are counseled to undergo oophorectomy prior to SM to significantly reduce their risk of developing breast, ovarian, and cervical cancers. There is limited evidence of the neurological effects of ovarian removal prior to the age of SM showing women without the BRCAm had cortical thinning in medial temporal lobe structures. A second study in women with BRCAm and bilateral salpingo-oophorectomy (BSO) noted changes in cognition.

METHODS

The present, cross-sectional study examined whole-brain differences in gray matter (GM) volume using high-resolution, quantitative magnetic resonance imaging in women with BRCAm and intact ovaries (BRCA-preBSO [study cohort with BRCA mutation prior to oophorectomy]; n = 9) and after surgery with (BSO + estradiol-based therapy [ERT]; n = 10) and without (BSO; n = 10) postsurgical estradiol hormone therapy compared with age-matched women (age-matched controls; n = 10) with their ovaries.

RESULTS

The BRCA-preBSO and BSO groups showed significantly lower GM volume in the left medial temporal and frontal lobe structures. BSO + ERT exhibited few areas of lower GM volume compared with age-matched controls. Novel to this study, we also observed that all three BRCAm groups exhibited significantly higher GM volume compared with age-matched controls, suggesting continued plasticity.

CONCLUSIONS

The present study provides evidence, through lower GM volume, to support both the possibility that the BRCAm, alone, and early life BSO may play a role in increasing the risk for late-life dementia. At least for BRCAm with BSO, postsurgical ERT seems to ameliorate GM losses.

Using a deep generation network reveals neuroanatomical specificity in hemispheres

Asymmetry is an important property of brain organization, but its nature is still poorly understood. Capturing the neuroanatomical components specific to each hemisphere facilitates the understanding of the establishment of brain asymmetry. Since deep generative networks (DGNs) have powerful inference and recovery capabilities, we use one hemisphere to predict the opposite hemisphere by training the DGNs, which automatically fit the built-in dependencies between the left and right hemispheres. After training, the reconstructed images approximate the homologous components in the hemisphere. We use the difference between the actual and reconstructed hemispheres to measure hemisphere-specific components due to asymmetric expression of environmental and genetic factors. The results show that our model is biologically plausible and that our proposed metric of hemispheric specialization is reliable, representing a wide range of individual variation. Together, this work provides promising tools for exploring brain asymmetry and new insights into self-supervised DGNs for representing the brain.

Brain structural indicators of β-amyloid neuropathology

Recent efforts demonstrated the efficacy of identifying early-stage neuropathology of Alzheimer's disease (AD) through lumbar puncture cerebrospinal fluid assessment and positron emission tomography (PET) radiotracer imaging. These methods are effective yet are invasive, expensive, and not widely accessible. We extend and improve the multiscale structural mapping (MSSM) procedure to develop structural indicators of β-amyloid neuropathology in preclinical AD, by capturing both macrostructural and microstructural properties throughout the cerebral cortex using a structural MRI. We find that the MSSM signal is regionally altered in clear positive and negative cases of preclinical amyloid pathology (N = 220) when cortical thickness alone or hippocampal volume is not. It exhibits widespread effects of amyloid positivity across the posterior temporal, parietal, and medial prefrontal cortex, surprisingly consistent with the typical pattern of amyloid deposition. The MSSM signal is significantly correlated with amyloid PET in almost half of the cortex, much of which overlaps with regions where beta-amyloid accumulates, suggesting it could provide a regional brain 'map' that is not available from systemic markers such as plasma markers.

Lateralized brunt of sleep deprivation on white matter injury in a rat model of Alzheimer's disease

Sleep disturbance is a recognized risk factor for Alzheimer's disease (AD), but the underlying micro-pathological evidence remains limited. To bridge this gap, we established an amyloid-β oligomers (AβO)-induced rat model of AD and subjected it to intermittent sleep deprivation (SD). Diffusion tensor imaging (DTI) and transmission electron microscopy were employed to assess white matter (WM) integrity and ultrastructural changes in myelin sheaths. Our findings demonstrated that SD exacerbated AβO-induced cognitive decline. Furthermore, we found SD aggravated AβO-induced asymmetrical impairments in WM, presenting with reductions in tract integrity observed in commissural fibers and association fasciculi, particularly the right anterior commissure, right corpus callosum, and left cingulum. Ultrastructural changes in myelin sheaths within the hippocampus and corpus callosum further confirmed a lateralized effect. Moreover, SD worsened AβO-induced lateralized disruption of the brain structural network, with impairments in critical nodes of the left hemisphere strongly correlated with cognitive dysfunction. This work represents the first identification of a lateralized impact of SD on the mesoscopic network and cognitive deficits in an AD rat model. These findings could deepen our understanding of the complex interplay between sleep disturbance and AD pathology, providing valuable insights into the early progression of the disease, as well as the development of neuroimaging biomarkers for screening early AD patients with self-reported sleep disturbances. Enhanced understanding of these mechanisms may pave the way for targeted interventions to alleviate cognitive decline and improve the quality of life for individuals at risk of or affected by AD.

Brain gray matter morphometry relates to onset age of bilingualism and theory of mind in young and older adults

Lifelong bilingualism may result in neural reserve against decline not only in the general cognitive domain, but also in social cognitive functioning. In this study, we show the brain structural correlates that are associated with second language age of acquisition (L2AoA) and theory of mind (the ability to reason about mental states) in normal aging. Participants were bilingual adults (46 young, 50 older) who completed a theory-of-mind task battery, a language background questionnaire, and an anatomical MRI scan to obtain cortical morphometric features (i.e., gray matter volume, thickness, and surface area). Findings indicated a theory-of-mind decline in older adults compared to young adults, controlling for education and general cognition. Importantly, earlier L2AoA and better theory-of-mind performance were associated with larger volume, higher thickness, and larger surface area in the bilateral temporal, medial temporal, superior parietal, and prefrontal brain regions. These regions are likely to be involved in mental representations, language, and cognitive control. The morphometric association with L2AoA in young and older adults were comparable, but its association with theory of mind was stronger in older adults than young adults. The results demonstrate that early bilingual acquisition may provide protective benefits to intact theory-of-mind abilities against normal age-related declines.

Sex- and region-specific cortical and hippocampal whole genome transcriptome profiles from control and APP/PS1 Alzheimer's disease mice

A variety of Alzheimer's disease (AD) mouse models has been established and characterized within the last decades. To get an integrative view of the sophisticated etiopathogenesis of AD, whole genome transcriptome studies turned out to be indispensable. Here we carried out microarray data collection based on RNA extracted from the retrosplenial cortex and hippocampus of age-matched, eight months old male and female APP/PS1 AD mice and control animals to perform sex- and brain region specific analysis of transcriptome profiles. The results of our studies reveal novel, detailed insight into differentially expressed signature genes and related fold changes in the individual APP/PS1 subgroups. Gene ontology and Venn analysis unmasked that intersectional, upregulated genes were predominantly involved in, e.g., activation of microglial, astrocytic and neutrophilic cells, innate immune response/immune effector response, neuroinflammation, phagosome/proteasome activation, and synaptic transmission. The number of (intersectional) downregulated genes was substantially less in the different subgroups and related GO categories included, e.g., the synaptic vesicle docking/fusion machinery, synaptic transmission, rRNA processing, ubiquitination, proteasome degradation, histone modification and cellular senescence. Importantly, this is the first study to systematically unravel sex- and brain region-specific transcriptome fingerprints/signature genes in APP/PS1 mice. The latter will be of central relevance in future preclinical and clinical AD related studies, biomarker characterization and personalized medicinal approaches.

Brain asymmetries from mid- to late life and hemispheric brain age

The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.

Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease

In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.

A multiscale characterization of cortical shape asymmetries in early psychosis

Psychosis has often been linked to abnormal cortical asymmetry, but prior results have been inconsistent. Here, we applied a novel spectral shape analysis to characterize cortical shape asymmetries in patients with early psychosis across different spatial scales. We used the Human Connectome Project for Early Psychosis dataset (aged 16-35), comprising 56 healthy controls (37 males, 19 females) and 112 patients with early psychosis (68 males, 44 females). We quantified shape variations of each hemisphere over different spatial frequencies and applied a general linear model to compare differences between healthy controls and patients with early psychosis. We further used canonical correlation analysis to examine associations between shape asymmetries and clinical symptoms. Cortical shape asymmetries, spanning wavelengths from about 22 to 75 mm, were significantly different between healthy controls and patients with early psychosis (Cohen's d = 0.28-0.51), with patients showing greater asymmetry in cortical shape than controls. A single canonical mode linked the asymmetry measures to symptoms (canonical correlation analysis r = 0.45), such that higher cortical asymmetry was correlated with more severe excitement symptoms and less severe emotional distress. Significant group differences in the asymmetries of traditional morphological measures of cortical thickness, surface area, and gyrification, at either global or regional levels, were not identified. Cortical shape asymmetries are more sensitive than other morphological asymmetries in capturing abnormalities in patients with early psychosis. These abnormalities are expressed at coarse spatial scales and are correlated with specific symptom domains.

A deep learning model for brain age prediction using minimally preprocessed T1w images as input

Introduction

In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction.

Methods

We used a multicohort dataset of cognitively healthy individuals (age range = 32.0-95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2-4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset's images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4).

Results

The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1-4, respectively. The model's performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63-2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction.

Discussion

We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.

Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (Tursiops truncatus) are located in the upper cortical layers

Introduction

The auditory system of dolphins and whales allows them to dive in dark waters, hunt for prey well below the limit of solar light absorption, and to communicate with their conspecific. These complex behaviors require specific and sufficient functional circuitry in the neocortex, and vicarious learning capacities. Dolphins are also precocious animals that can hold their breath and swim within minutes after birth. However, diving and hunting behaviors are likely not innate and need to be learned. Our hypothesis is that the organization of the auditory cortex of dolphins grows and mature not only in the early phases of life, but also in adults and aging individuals. These changes may be subtle and involve sub-populations of cells specificall linked to some circuits.

Methods

In the primary auditory cortex of 11 bottlenose dolphins belonging to three age groups (calves, adults, and old animals), neuronal cell shapes were analyzed separately and by cortical layer using custom computer vision and multivariate statistical analysis, to determine potential minute morphological differences across these age groups.

Results

The results show definite changes in interneurons, characterized by round and ellipsoid shapes predominantly located in upper cortical layers. Notably, neonates interneurons exhibited a pattern of being closer together and smaller, developing into a more dispersed and diverse set of shapes in adulthood.

Discussion

This trend persisted in older animals, suggesting a continuous development of connections throughout the life of these marine animals. Our findings further support the proposition that thalamic input reach upper layers in cetaceans, at least within a cortical area critical for their survival. Moreover, our results indicate the likelihood of changes in cell populations occurring in adult animals, prompting the need for characterization.

When Age Tips the Balance: a Dual Mechanism Affecting Hemispheric Specialization for Language

Aging engenders neuroadaptations, generally reducing specificity and selectivity in functional brain responses. Our investigation delves into the functional specialization of brain hemispheres within language-related networks across adulthood. In a cohort of 728 healthy adults spanning ages 18 to 88, we modeled the trajectories of inter-hemispheric asymmetry concerning the principal functional gradient across 37 homotopic regions of interest (hROIs) of an extensive language network, known as the Language-and-Memory Network. Our findings reveal that over two-thirds of Language-and-Memory Network hROIs undergo asymmetry changes with age, falling into two main clusters. The first cluster evolves from left-sided specialization to right-sided tendencies, while the second cluster transitions from right-sided asymmetry to left-hemisphere dominance. These reversed asymmetry shifts manifest around midlife, occurring after age 50, and are associated with poorer language production performance. Our results provide valuable insights into the influence of functional brain asymmetries on language proficiency and present a dynamic perspective on brain plasticity during the typical aging process.

Cerebral dominance representation of directed connectivity within and between left-right hemispheres and frontal-posterior lobes in mild cognitive impairment

Electroencephalography can assess connectivity between brain hemispheres, potentially influencing cognitive functions. Much of the existing electroencephalography research primarily focuses on undirected connectivity, leaving uncertainties about directed connectivity alterations between left-right brain hemispheres or frontal-posterior lobes in mild cognitive impairment. We analyzed resting-state electroencephalography data from 34 mild cognitive impairment individuals and 23 normal controls using directed transfer function and graph theory for directed network analysis. Concerning the dominance within left-right hemispheres or frontal-posterior lobes, the mild cognitive impairment group exhibited decreased connectivity within the frontal compared with posterior brain regions in the delta and theta bands. Regarding the dominance between the brain hemispheres or lobes, the mild cognitive impairment group showed reduced connectivity from the posterior to the frontal regions versus the reverse direction in the same bands. Among all participants, the intra-lobe frontal-posterior dominance correlated positively with executive function in the delta and alpha bands. Inter-lobe dominance between frontal and posterior regions also positively correlated with executive function, attention, and language in the delta band. Additionally, interhemispheric dominance between the left and right hemispheres positively correlated with attention in delta and theta bands. These findings suggest altered cerebral dominance in mild cognitive impairment, potentially serving as electrophysiological markers for neurocognitive disorders.

Identifying biomarkers for tDCS treatment response in Alzheimer's disease patients: a machine learning approach using resting-state EEG classification

Background

Transcranial direct current stimulation (tDCS) is a promising treatment for Alzheimer's Disease (AD). However, identifying objective biomarkers that can predict brain stimulation efficacy, remains a challenge. The primary aim of this investigation is to delineate the cerebral regions implicated in AD, taking into account the existing lacuna in comprehension of these regions. In pursuit of this objective, we have employed a supervised machine learning algorithm to prognosticate the neurophysiological outcomes resultant from the confluence of tDCS therapy plus cognitive intervention within both the cohort of responders and non-responders to antecedent tDCS treatment, stratified on the basis of antecedent cognitive outcomes.

Methods

The data were obtained through an interventional trial. The study recorded high-resolution electroencephalography (EEG) in 70 AD patients and analyzed spectral power density during a 6 min resting period with eyes open focusing on a fixed point. The cognitive response was assessed using the AD Assessment Scale-Cognitive Subscale. The training process was carried out through a Random Forest classifier, and the dataset was partitioned into K equally-partitioned subsamples. The model was iterated k times using K-1 subsamples as the training bench and the remaining subsample as validation data for testing the model.

Results

A clinical discriminating EEG biomarkers (features) was found. The ML model identified four brain regions that best predict the response to tDCS associated with cognitive intervention in AD patients. These regions included the channels: FC1, F8, CP5, Oz, and F7.

Conclusion

These findings suggest that resting-state EEG features can provide valuable information on the likelihood of cognitive response to tDCS plus cognitive intervention in AD patients. The identified brain regions may serve as potential biomarkers for predicting treatment response and maybe guide a patient-centered strategy.

Clinical Trial Registration

https://classic.clinicaltrials.gov/ct2/show/NCT02772185?term=NCT02772185&draw=2&rank=1, identifier ID: NCT02772185.

Lateralization of the hippocampus: A review of molecular, functional, and physiological properties in health and disease

The hippocampus is a part of the brain's medial temporal lobe that is located under the cortex. It belongs to the limbic system and helps to collect and transfer information from short-term to long-term memory, as well as spatial orientation in each mammalian brain hemisphere. After more than two centuries of research in brain asymmetry, the hippocampus has attracted much attention in the study of brain lateralization. The hippocampus is very important in cognitive disorders, related to seizures and dementia, such as epilepsy and Alzheimer's disease. In addition, the motivation to study the hippocampus has increased significantly due to the asymmetry in the activity of the left and right hippocampi in healthy people, and its disruption during some neurological diseases. After a general review of the hippocampal structure and its importance in related diseases, the asymmetry in the brain with a focus on the hippocampus during the growth and maturation of healthy people, as well as the differences created in patients at the molecular, functional, and physiological levels are discussed. Most previous work indicates that the hippocampus is lateralized in healthy people. Also, lateralization at different levels remarkably changes in patients, and it appears that the most complex cognitive disorder is caused by a new dominant asymmetric system.

Diverging asymmetry of intrinsic functional organization in autism

Autism is a neurodevelopmental condition involving atypical sensory-perceptual functions together with language and socio-cognitive deficits. Previous work has reported subtle alterations in the asymmetry of brain structure and reduced laterality of functional activation in individuals with autism relative to non-autistic individuals (NAI). However, whether functional asymmetries show altered intrinsic systematic organization in autism remains unclear. Here, we examined inter- and intra-hemispheric asymmetry of intrinsic functional gradients capturing connectome organization along three axes, stretching between sensory-default, somatomotor-visual, and default-multiple demand networks, to study system-level hemispheric imbalances in autism. We observed decreased leftward functional asymmetry of language network organization in individuals with autism, relative to NAI. Whereas language network asymmetry varied across age groups in NAI, this was not the case in autism, suggesting atypical functional laterality in autism may result from altered developmental trajectories. Finally, we observed that intra- but not inter-hemispheric features were predictive of the severity of autistic traits. Our findings illustrate how regional and patterned functional lateralization is altered in autism at the system level. Such differences may be rooted in atypical developmental trajectories of functional organization asymmetry in autism.

Evaluation of volumetric asymmetry of the dorsolateral prefrontal cortex and medial temporal lobe in Alzheimer's disease using the atlas-based method

Brain areas affected during neurodegenerative disease progression are considered anatomically connected to the first affected areas. The dorsolateral prefrontal cortex (DLPFC) has connections with the medial temporal lobe (MTL), which includes regions that become atrophic in Alzheimer's disease. In this study, we aimed to investigate the degree of volumetric asymmetry of DLPFC and MTL structures. This is a cross-sectional volumetric study involving 25 Alzheimer's disease patients and 25 healthy adults who underwent MRI with a 3D turbo spin echo sequence at 1.5 Tesla. The atlas-based method incorporated MRIStudio software to automatically measure the volume of brain structures. We compared the asymmetry index and volumetric changes across study groups and correlated them with Mini-Mental State Examination scores. We observed significant volumetric rightward lateralization in the DLPFC and superior frontal gyrus in Alzheimer's disease patients compared to the healthy controls. There was a significant volume loss in the MTL structures of Alzheimer's disease patients. Atrophy of MTL structures was positively correlated with right DLPFC volume changes in Alzheimer's disease patients. Volumetric asymmetry of the DLPFC may be a characteristic for determining disease progression in Alzheimer's disease patients. Future studies are recommended to evaluate whether these volumetric asymmetrical changes are specific to Alzheimer's disease and whether asymmetry measurements can serve as diagnostic markers.

Bidirectional Mapping Perception-enhanced Cycle-consistent Generative Adversarial Network for Super-resolution of Brain MRI images

As an effective tool for visualizing neurodegeneration, high-resolution structural magnetism facilitates quantitative image analysis and clinical applications. Super-resolution reconstruction technology allows to improve the resolution of images without upgrading the scanning hardware. However, existing super-resolution techniques relied on paired image data sets and lacked further quantitative analysis of the generated images. In this study, we proposed a semi-supervised generative adversarial network (GAN) model for super-resolution of brain MRI, and the synthetic images were evaluated using various quantitative measures. This model adopted the cycle-consistency structure to allow for a mixture of unpaired data for training. Perceptual loss was further introduced into the model to preserve detailed texture features at high frequencies. 363 subjects with both high-resolution (HR) and low-resolution (LR) scans and 217 subjects with HR scans only were used for model derivation, training, and validation. We extracted multiple voxel-based and surface-based morphological features of the synthetic and real 3D HR images for comparison. We further evaluated the synthetic images in the differential diagnosis of diseases. Our model achieved superior mean absolute error (0.049±0.021), mean squared error (0.0059±0.0043), peak signal-to-noise ratio (29.41±3.71), structural similarity index measure (0.914±0.048). Eight morphological metrics, both voxel-based and surface-based, showed significant agreement (P<0.0001). The gap of accuracy in disease diagnosis between synthetic and real HR images was within 5% and significantly outperformed the LR images. Our proposed model enables the reconstruction of HR MRI and could be used accurately for image quantification.Clinical relevance- Quantitative evaluation of the synthetic high-resolution images was used to determine whether the synthetic images have sufficient realism and diversity.

Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex

Cortical asymmetry is a ubiquitous feature of brain organization that is subtly altered in some neurodevelopmental disorders, yet we lack knowledge of how its development proceeds across life in health. Achieving consensus on the precise cortical asymmetries in humans is necessary to uncover the developmental timing of asymmetry and the extent to which it arises through genetic and later influences in childhood. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in seven datasets and chart asymmetry trajectories longitudinally across life (4-89 years; observations = 3937; 70% longitudinal). We find replicable asymmetry interrelationships, heritability maps, and test asymmetry associations in large-scale data. Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in childhood and peaks in early adulthood. Areal asymmetry is low-moderately heritable (max h2SNP ~19%) and correlates phenotypically and genetically in specific regions, indicating coordinated development of asymmetries partly through genes. In contrast, thickness asymmetry is globally interrelated across the cortex in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in population-level right-asymmetric regions (and vice versa), and exhibits low or absent heritability. We find less areal asymmetry in the most consistently lateralized region in humans associates with subtly lower cognitive ability, and confirm small handedness and sex effects. Results suggest areal asymmetry is developmentally stable and arises early in life through genetic but mainly subject-specific stochastic effects, whereas childhood developmental growth shapes thickness asymmetry and may lead to directional variability of global thickness lateralization in the population.

Age differences in cortical thickness and their association with cognition in chimpanzee (Pan troglodytes)

Humans and chimpanzees are genetically similar and share a number of life history, behavioral, cognitive and neuroanatomical similarities. Notwithstanding, our understanding of age-related changes in cognitive and motor functions in chimpanzees remains largely unstudied despite recent evident demonstrating that chimpanzees exhibit many of the same neuropathological features of Alzheimer's disease observed in human postmortem brains. Here, we examined age-related differences in cognition and cortical thickness measured from magnetic resonance images in a sample of 215 chimpanzees ranging in age between 9 and 54 years. We found that chimpanzees showed global and region-specific thinning of cortex with increasing age. Further, within the elderly cohort, chimpanzees that performed better than average had thicker cortex in frontal, temporal and parietal regions compared to chimpanzees that performed worse than average. Independent of age, we also found sex differences in cortical thickness in 4 brain regions. Males had higher adjusted cortical thickness scores for the caudal anterior cingulate, rostral anterior cingulate, and medial orbital frontal while females had higher values for the inferior parietal cortex. We found no evidence that increasing age nor sex was associated with asymmetries in cortical thickness. Moreover, age-related differences in cognitive function were only weakly associated with asymmetries in cortical thickness. In summary, as has been reported in humans and other primates, elderly chimpanzees show thinner cortex and variation in cortical thickness is associated with general cognitive functions.

sEBM: Scaling Event Based Models to Predict Disease Progression via Implicit Biomarker Selection and Clustering

The Event Based Model (EBM) is a probabilistic generative model to explore biomarker changes occurring as a disease progresses. Disease progression is hypothesized to occur through a sequence of biomarker dysregulation "events". The EBM estimates the biomarker dysregulation event sequence. It computes the data likelihood for a given dysregulation sequence, and subsequently evaluates the posterior distribution on the dysregulation sequence. Since the posterior distribution is intractable, Markov Chain Monte-Carlo is employed to generate samples under the posterior distribution. However, the set of possible sequences increases as N ! where N is the number of biomarkers (data dimension) and quickly becomes prohibitively large for effective sampling via MCMC. This work proposes the "scaled EBM" (sEBM) to enable event based modeling on large biomarker sets (e.g. high-dimensional data). First, sEBM implicitly selects a subset of biomarkers useful for modeling disease progression and infers the event sequence only for that subset. Second, sEBM clusters biomarkers with similar positions in the event sequence and only orders the "clusters", with each successive cluster corresponding to the next stage in disease progression. These two modifications used to construct the sEBM method provably reduces the possible space of event sequences by multiple orders of magnitude. The novel modifications are supported by theory and experiments on synthetic and real clinical data provides validation for sEBM to work in higher dimensional settings. Results on synthetic data with known ground truth shows that sEBM outperforms previous EBM variants as data dimensions increase. sEBM was successfully implemented with up to 300 biomarkers, which is a 6-fold increase over previous EBM applications. A real-world clinical application of sEBM is performed using 119 neuroimaging markers from publicly available Alzheimer's Disease Neuroimaging Initiative (ADNI) data to stratify subjects into 6 stages of disease progression. Subjects included cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer's Disease (AD). sEBM stage is differentiated for the 3 groups ( χ 2 p - v a l u e < 4.6 e - 32 ) . Increased sEBM stage is a strong predictor of conversion risk to AD ( p - v a l u e < 2.3 e - 14 ) for MCI subjects, as verified with a Cox proportional-hazards model adjusted for age, sex, education and APOE4 status. Like EBM, sEBM does not rely on apriori defined diagnostic labels and only uses cross-sectional data.

Spatial-temporal data-augmentation-based functional brain network analysis for brain disorders identification

Introduction

Due to the lack of devices and the difficulty of gathering patients, the small sample size is one of the most challenging problems in functional brain network (FBN) analysis. Previous studies have attempted to solve this problem of sample limitation through data augmentation methods, such as sample transformation and noise addition. However, these methods ignore the unique spatial-temporal information of functional magnetic resonance imaging (fMRI) data, which is essential for FBN analysis.

Methods

To address this issue, we propose a spatial-temporal data-augmentation-based classification (STDAC) scheme that can fuse the spatial-temporal information, increase the samples, while improving the classification performance. Firstly, we propose a spatial augmentation module utilizing the spatial prior knowledge, which was ignored by previous augmentation methods. Secondly, we design a temporal augmentation module by random discontinuous sampling period, which can generate more samples than former approaches. Finally, a tensor fusion method is used to combine the features from the above two modules, which can make efficient use of spatial-temporal information of fMRI simultaneously. Besides, we apply our scheme to different types of classifiers to verify the generalization performance. To evaluate the effectiveness of our proposed scheme, we conduct extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and REST-meta-MDD Project (MDD) dataset.

Results

Experimental results show that the proposed scheme achieves superior classification accuracy (ADNI: 82.942%, MDD: 63.406%) and feature interpretation on the benchmark datasets.

Discussion

The proposed STDAC scheme, utilizing both spatial and temporal information, can generate more diverse samples than former augmentation methods for brain disorder classification and analysis.

G protein-coupled receptors in neurodegenerative diseases and psychiatric disorders

Neuropsychiatric disorders are multifactorial disorders with diverse aetiological factors. Identifying treatment targets is challenging because the diseases are resulting from heterogeneous biological, genetic, and environmental factors. Nevertheless, the increasing understanding of G protein-coupled receptor (GPCR) opens a new possibility in drug discovery. Harnessing our knowledge of molecular mechanisms and structural information of GPCRs will be advantageous for developing effective drugs. This review provides an overview of the role of GPCRs in various neurodegenerative and psychiatric diseases. Besides, we highlight the emerging opportunities of novel GPCR targets and address recent progress in GPCR drug development.

Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features

Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.

The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer's disease

PURPOSE

Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity.

METHODS

Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with 18F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with 18F-Florzolotau]. Based on the absolute global tau interhemispheric differences, each cohort was divided into two groups (asymmetric versus symmetric tau distribution). The two groups were cross-sectionally compared in terms of demographic, cognitive characteristics, and pathological burden. The cognitive decline trajectories were analyzed longitudinally.

RESULTS

Fourteen (23.3%) and 42 (48.3%) patients in the ADNI and SMS cohorts showed an asymmetric tau distribution, respectively. An asymmetric tau distribution was associated with an earlier age at disease onset (proportion of early-onset AD: ADNI/SMS/combined cohorts, p = 0.093/0.026/0.001) and more severe pathological burden (i.e., global tau burden: ADNI/SMS cohorts, p < 0.001/= 0.007). And patients with an asymmetric tau distribution were characterized by a steeper cognitive decline longitudinally (i.e., the annual decline of Mini-Mental Status Examination score: ADNI/SMS/combined cohorts, p = 0.053 / 0.035 / < 0.001).

CONCLUSIONS

Asymmetry in tau deposition, which may be associated with an earlier age at onset, more severe pathological burden, and a steeper cognitive decline, is potentially an important characteristic of AD heterogeneity.

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Cortical thinning in chemotherapy-treated older long-term breast cancer survivors

Cognitive decline is an increasing issue for cancer survivors, especially for older adults, as chemotherapy affects brain structure and function. The purpose of this single center study was to evaluate alterations in cortical thickness and cognition in older long-term survivors of breast cancer who had been treated with chemotherapy years ago. In this prospective cohort study, we enrolled 3 groups of women aged ≥ 65 years with a history of stage I-III breast cancer who had received adjuvant chemotherapy 5 to 15 years ago (chemotherapy group, C +), age-matched women with breast cancer but no chemotherapy (no-chemotherapy group, C-) and healthy controls (HC). All participants underwent brain magnetic resonance imaging and neuropsychological testing with the NIH Toolbox Cognition Battery at time point 1 (TP1) and again at 2 years after enrollment (time point 2 (TP2)). At TP1, there were no significant differences in cortical thickness among the 3 groups. Longitudinally, the C + group showed cortical thinning in the fusiform gyrus (p = 0.006, effect size (d) = -0.60 [ -1.86, -0.66]), pars triangularis (p = 0.026, effect size (d) = -0.43 [-1.68, -0.82]), and inferior temporal lobe (p = 0.026, effect size (d) = -0.38 [-1.62, -0.31]) of the left hemisphere. The C + group also showed decreases in neuropsychological scores such as the total composite score (p = 0.01, effect size (d) = -3.9726 [-0.9656, -6.9796], fluid composite score (p = 0.03, effect size (d) = -4.438 [-0.406, -8.47], and picture vocabulary score (p = 0.04, effect size (d) = -3.7499 [-0.0617, -7.438]. Our results showed that cortical thickness could be a candidate neuroimaging biomarker for cancer-related cognitive impairment and accelerated aging in older long-term cancer survivors.

Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment

Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.

Characterization of the angular gyrus in an older adult population: a multimodal multilevel approach

The angular gyrus (AG) has been associated with multiple cognitive functions, such as language, spatial and memory functions. Since the AG is thought to be a cross-modal hub region suffering from significant age-related structural atrophy, it may also play a key role in age-related cognitive decline. However, the exact relation between structural atrophy of the AG and cognitive decline in older adults is not fully understood, which may be related to two aspects: First, the AG is cytoarchitectonically divided into two areas, PGa and PGp, potentially sub-serving different cognitive functions. Second, the older adult population is characterized by high between-subjects variability which requires targeting individual phenomena during the aging process. We therefore performed a multimodal (gray matter volume [GMV], resting-state functional connectivity [RSFC] and structural connectivity [SC]) characterization of AG subdivisions PGa and PGp in a large older adult population, together with relations to age, cognition and lifestyle on the group level. Afterwards, we switched the perspective to the individual, which is especially important when it comes to the assessment of individual patients. The AG can be considered a heterogeneous structure in of the older brain: we found the different AG parts to be associated with different patterns of whole-brain GMV associations as well as their associations with RSFC, and SC patterns. Similarly, differential effects of age, cognition and lifestyle on the GMV of AG subdivisions were observed. This suggests each region to be structurally and functionally differentially involved in the older adult's brain network architecture, which was supported by differential molecular and genetic patterns, derived from the EBRAINS multilevel atlas framework. Importantly, individual profiles deviated considerably from the global conclusion drawn from the group study. Hence, general observations within the older adult population need to be carefully considered, when addressing individual conditions in clinical practice.

Assessment and Comparison of Nonlinear Measures in Resting-State Magnetoencephalograms in Alzheimer's Disease and Mild Cognitive Impairment

BACKGROUND

Nonlinear dynamical measures, such as fractal dimension (FD), entropy, and Lempel-Ziv complexity (LZC), have been extensively investigated individually for detecting information content in magnetoencephalograms (MEGs) from patients with Alzheimer's disease (AD).

OBJECTIVE

To compare systematically the performance of twenty conventional and recently introduced nonlinear dynamical measures in studying AD versus mild cognitive impairment (MCI) and healthy control (HC) subjects using MEG.

METHODS

We compared twenty nonlinear measures to distinguish MEG recordings from 36 AD (mean age = 74.06±6.95 years), 18 MCI (mean age = 74.89±5.57 years), and 26 HC subjects (mean age = 71.77±6.38 years) in different brain regions and also evaluated the effect of the length of MEG epochs on their performance. We also studied the correlation between these measures and cognitive performance based on the Mini-Mental State Examination (MMSE).

RESULTS

The results obtained by LZC, zero-crossing rate (ZCR), FD, and dispersion entropy (DispEn) measures showed significant differences among the three groups. There was no significant difference between HC and MCI. The highest Hedge's g effect sizes for HC versus AD and MCI versus AD were respectively obtained by Higuchi's FD (HFD) and fuzzy DispEn (FuzDispEn) in the whole brain and was most prominent in left lateral. The results obtained by HFD and FuzDispEn had a significant correlation with the MMSE scores. DispEn-based techniques, LZC, and ZCR, compared with HFD, were less sensitive to epoch length in distinguishing HC form AD.

CONCLUSIONS

FuzDispEn was the most consistent technique to distinguish MEG dynamical patterns in AD compared with HC and MCI.

Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification

BACKGROUND

Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer's disease (AD), fine motor function has been relatively understudied.

OBJECTIVE

We examined if finger tapping is affected in AD, related to AD biomarkers, and able to classify MCI or AD.

METHODS

Forty-seven cognitively normal, 27 amnestic MCI, and 26 AD subjects completed unimanual and bimanual computerized tapping tests. We tested 1) group differences in tapping with permutation models; 2) associations between tapping and biomarkers (PET amyloid-β, hippocampal volume, and APOEɛ4 alleles) with linear regression; and 3) the predictive value of tapping for group classification using machine learning.

RESULTS

AD subjects had slower reaction time and larger speed variability than controls during all tapping conditions, except for dual tapping. MCI subjects performed worse than controls on reaction time and speed variability for dual and non-dominant hand tapping. Tapping speed and variability were related to hippocampal volume, but not to amyloid-β deposition or APOEɛ4 alleles. Random forest classification (overall accuracy = 70%) discriminated control and AD subjects, but poorly discriminated MCI from controls or AD.

CONCLUSIONS

MCI and AD are linked to more variable finger tapping with slower reaction time. Associations between finger tapping and hippocampal volume, but not amyloidosis, suggest that tapping deficits are related to neuropathology that presents later during the disease. Considering that tapping performance is able to differentiate between control and AD subjects, it can offer a cost-efficient tool for augmenting existing AD biomarkers.

From attention-deficit hyperactivity disorder to sporadic Alzheimer's disease-Wnt/mTOR pathways hypothesis

Alzheimer's disease (AD) is the most common neurodegenerative disorder with the majority of patients classified as sporadic AD (sAD), in which etiopathogenesis remains unresolved. Though sAD is argued to be a polygenic disorder, apolipoprotein E (APOE) ε4, was found three decades ago to pose the strongest genetic risk for sAD. Currently, the only clinically approved disease-modifying drugs for AD are aducanumab (Aduhelm) and lecanemab (Leqembi). All other AD treatment options are purely symptomatic with modest benefits. Similarly, attention-deficit hyperactivity disorder (ADHD), is one of the most common neurodevelopmental mental disorders in children and adolescents, acknowledged to persist in adulthood in over 60% of the patients. Moreover, for ADHD whose etiopathogenesis is not completely understood, a large proportion of patients respond well to treatment (first-line psychostimulants, e.g., methylphenidate/MPH), however, no disease-modifying therapy exists. Interestingly, cognitive impairments, executive, and memory deficits seem to be common in ADHD, but also in early stages of mild cognitive impairment (MCI), and dementia, including sAD. Therefore, one of many hypotheses is that ADHD and sAD might have similar origins or that they intercalate with one another, as shown recently that ADHD may be considered a risk factor for sAD. Intriguingly, several overlaps have been shown between the two disorders, e.g., inflammatory activation, oxidative stress, glucose and insulin pathways, wingless-INT/mammalian target of rapamycin (Wnt/mTOR) signaling, and altered lipid metabolism. Indeed, Wnt/mTOR activities were found to be modified by MPH in several ADHD studies. Wnt/mTOR was also found to play a role in sAD and in animal models of the disorder. Moreover, MPH treatment in the MCI phase was shown to be successful for apathy including some improvement in cognition, according to a recent meta-analysis. In several AD animal models, ADHD-like behavioral phenotypes have been observed indicating a possible interconnection between ADHD and AD. In this concept paper, we will discuss the various evidence in human and animal models supporting the hypothesis in which ADHD might increase the risk for sAD, with common involvement of the Wnt/mTOR-pathway leading to lifespan alteration at the neuronal levels.

Asymmetry-enhanced attention network for Alzheimer's diagnosis with structural Magnetic Resonance Imaging

BACKGROUND AND OBJECTIVE

With the aging of the global population becoming severe, Alzheimer's disease (AD) has become one of the world's most common senile diseases. Many studies have suggested that the brain's left-right asymmetry is one of the possible diagnostic landmarks for AD. However, most published approaches to classification problems may not adequately explore the asymmetry between the left and right hemispheres. At the same time, the relationship between asymmetry traits and other classifier features remains understudied.

METHODS

In this paper, we proposed an asymmetry enhanced attention network (ASEAN) for AD diagnosis that effectively combines the anatomical asymmetry characteristics of the brain to enhance the accuracy and stability of classification tasks. First, we proposed a multi-scale asymmetry feature extraction module (MSAF) that can extract the asymmetry features of the brain from various scales. Second, we proposed an asymmetry refinement module (ARM) that considers the dependency between feature maps to suppress the irrelevant regions of the asymmetric feature maps. In addition, a parameter-free attention module was introduced to infer 4D attention weights and improve the network's representation capability.

RESULTS

The proposed method achieved performance improvements on two databases: Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarkers and Lifestyle (AIBL). For the classification tasks on ADNI, the proposed method achieves 92.1% accuracy, 96.2% sensitivity, and 91.3% specificity on the AD vs. CN (Cognitively Normal) task. Compared with state-of-the-art methods, the proposed method could achieve comparable results.

CONCLUSION

The proposed model can extract long-range left-right brain similarity as complementary information and improve the model's diagnostic performance. A large number of experiments also support the model's validity. At the same time, this work provides a valuable reference for other neurological diseases, particularly those that exhibit left-right brain asymmetry during development.

Racial discrimination associates with lower cingulate cortex thickness in trauma-exposed black women

Racial discrimination (RD) has been consistently linked to adverse brain health outcomes. These may be due in part to RD effects on neural networks involved with threat appraisal and regulation; RD has been linked to altered activity in the rostral anterior cingulate cortex (rACC) and structural decrements in the anterior cingulum bundle and hippocampus. In the present study, we examined associations of RD with cingulate, hippocampus and amygdala gray matter morphology in a sample of trauma-exposed Black women. Eighty-one Black women aged 19-62 years were recruited as part of an ongoing study of trauma. Participants completed assessments of RD, trauma exposure, and posttraumatic stress disorder (PTSD), and underwent T1-weighted anatomical imaging. Cortical thickness, surface area and gray matter volume were extracted from subregions of cingulate cortex, and gray matter volume was extracted from amygdala and hippocampus, and entered into partial correlation analyses that included RD and other socio-environmental variables. After correction for multiple comparisons and accounting for variance associated with other stressors and socio-environmental factors, participants with more RD exposure showed proportionally lower cortical thickness in the left rACC, caudal ACC, and posterior cingulate cortex (ps < = 0.01). These findings suggest that greater experiences of RD are linked to compromised cingulate gray matter thickness. In the context of earlier findings indicating that RD produces increased response in threat neurocircuitry, our data suggest that RD may increase vulnerability for brain health problems via cingulate cortex alterations. Further research is needed to elucidate biological mechanisms for these changes.

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.

Cortical thinning 3 years after ischaemic stroke is associated with cognitive impairment and APOE ε4

Cortical thinning has been described in many neurodegenerative diseases and used for both diagnosis and disease monitoring. The imaging signatures of post-stroke vascular cognitive impairment have not been well described. We investigated the trajectory of cortical thickness over 3 years following ischaemic stroke compared to healthy stroke-free age- and sex-matched controls. We also compared cortical thickness between cognitively normal and impaired stroke survivors, and between APOE ɛ4 carriers and non-carriers. T1-weighted MRI and cognitive data for 90 stroke survivors and 36 controls from the Cognition And Neocortical Volume After Stroke (CANVAS) study were used. Cortical thickness was estimated using FreeSurfer volumetric reconstruction according to the Desikan-Killiany parcellation atlas. Segmentation inaccuracies were manually corrected and infarcted ipsilesional vertices in cortical thickness maps were identified and excluded using stroke lesion masks traced a-priori. Mixed-effects regression was used to compare cortical thickness cross-sectionally between groups and longitudinally between timepoints. Healthy control and stroke groups did not differ on demographics and most clinical characteristics, though controls were less likely to have atrial fibrillation. Age was negatively associated with global mean cortical thickness independent of sex or group, with women in both groups having significantly thicker cortex. Three months post-stroke, cortical thinning was limited and focal. From 3 months to 3 years, the rate of cortical thinning in stroke was faster compared to that in healthy controls. However, this difference in cortical thinning rate could not survive family-wise correction for multiple comparisons. Yet, cortical thinning at 3 years was found more spread especially in ipsilesional hemispheres in regions implicated in motor, sensory, and memory processing and recovery. The cognitively impaired stroke survivors showed greater cortical thinning, compared to controls, than those who were cognitively normal at 3 years. Also, carriers of the APOE ɛ4 allele in stroke exhibited greater cortical thinning independent of cognitive status. The temporal changes of cortical thickness in both healthy and stroke cohorts followed previously reported patterns of cortical thickness asymmetry loss across the human adult life. However, this loss of thickness asymmetry was amplified in stroke. The post-stroke trajectories of cortical thickness reported in this study may contribute to our understanding of imaging signatures of vascular cognitive impairment.

Comparing brain asymmetries independently of brain size

Studies examining cerebral asymmetries typically divide the l-R Measure (e.g., Left-Right Volume) by the L + R Measure to obtain an Asymmetry Index (AI). However, contrary to widespread belief, such a division fails to render the AI independent from the L + R Measure and/or from total brain size. As a result, variations in brain size may bias correlation estimates with the AI or group differences in AI. We investigated how to analyze brain asymmetries in to distinguish global from regional effects, and report unbiased group differences in cerebral asymmetries in the UK Biobank (N = 40, 028). We used 306 global and regional brain measures provided by the UK Biobank. Global gray and white matter volumes were taken from Freesurfer ASEG, subcortical gray matter volumes from Freesurfer ASEG and subsegmentation, cortical gray matter volumes, mean thicknesses, and surface areas from the Destrieux atlas applied on T1-and T2-weighted images, cerebellar gray matter volumes from FAST FSL, and regional white matter volumes from Freesurfer ASEG. We analyzed the extent to which the L + R Measure, Total Cerebral Measure (TCM, e.g., Total Brain Volume), and l-R TCM predict regional asymmetries. As a case study, we assessed the consequences of omitting each of these predictors on the magnitude and significance of sex differences in asymmetries. We found that the L + R Measure, the TCM, and the l-R TCM predicted the AI of more than 89% of regions and that their relationships were generally linear. Removing any of these predictors changed the significance of sex differences in 33% of regions and the magnitude of sex differences across 13-42% of regions. Although we generally report similar sex and age effects on cerebral asymmetries to those of previous large-scale studies, properly adjusting for regional and global brain size revealed additional sex and age effects on brain asymmetry.

Longitudinal Brain Changes After Stroke and the Association With Cognitive Decline

Background

Cognitive impairment is common after stroke. So is cortical- and subcortical atrophy, with studies reporting more atrophy in the ipsilesional hemisphere than the contralesional hemisphere. The current study aimed to investigate the longitudinal associations between (I) lateralization of brain atrophy and stroke hemisphere, and (II) cognitive impairment and brain atrophy after stroke. We expected to find that (I) cortical thickness and hippocampal-, thalamic-, and caudate nucleus volumes declined more in the ipsilesional than the contralesional hemisphere up to 36 months after stroke. Furthermore, we predicted that (II) cognitive decline was associated with greater stroke volumes, and with greater cortical thickness and subcortical structural volume atrophy across the 36 months.

Methods

Stroke survivors from five Norwegian hospitals were included from the multisite-prospective “Norwegian Cognitive Impairment After Stroke” (Nor-COAST) study. Analyses were run with clinical, neuropsychological and structural magnetic resonance imaging (MRI) data from baseline, 18- and 36 months. Cortical thicknesses and subcortical volumes were obtained via FreeSurfer segmentations and stroke lesion volumes were semi-automatically derived using ITK-SNAP. Cognition was measured using MoCA.

Results

Findings from 244 stroke survivors [age = 72.2 (11.3) years, women = 55.7%, stroke severity NIHSS = 4.9 (5.0)] were included at baseline. Of these, 145 (59.4%) had an MRI scan at 18 months and 72 (49.7% of 18 months) at 36 months. Most cortices and subcortices showed a higher ipsi- compared to contralesional atrophy rate, with the effect being more prominent in the right hemisphere. Next, greater degrees of atrophy particularly in the medial temporal lobe after left-sided strokes and larger stroke lesion volumes after right-sided strokes were associated with cognitive decline over time.

Conclusion

Atrophy in the ipsilesional hemisphere was greater than in the contralesional hemisphere over time. This effect was found to be more prominent in the right hemisphere, pointing to a possible higher resilience to stroke of the left hemisphere. Lastly, greater atrophy of the cortex and subcortex, as well as larger stroke volume, were associated with worse cognition over time and should be included in risk assessments of cognitive decline after stroke.

Psychological Resilience and Neurodegenerative Risk: A Connectomics-Transcriptomics Investigation in Healthy Adolescent and Middle-Aged Females

Adverse life events can inflict substantial long-term damage, which, paradoxically, has been posited to stem from initially adaptative responses to the challenges encountered in one's environment. Thus, identification of the mechanisms linking resilience against recent stressors to longer-term psychological vulnerability is key to understanding optimal functioning across multiple timescales. To address this issue, our study tested the relevance of neuro-reproductive maturation and senescence, respectively, to both resilience and longer-term risk for pathologies characterised by accelerated brain aging, specifically, Alzheimer's Disease (AD). Graph theoretical and partial least squares analyses were conducted on multimodal imaging, reported biological aging and recent adverse experience data from the Lifespan Human Connectome Project (HCP). Availability of reproductive maturation/senescence measures restricted our investigation to adolescent (N =178) and middle-aged (N=146) females. Psychological resilience was linked to age-specific brain senescence patterns suggestive of precocious functional development of somatomotor and control-relevant networks (adolescence) and earlier aging of default mode and salience/ventral attention systems (middle adulthood). Biological aging showed complementary associations with the neural patterns relevant to resilience in adolescence (positive relationship) versus middle-age (negative relationship). Transcriptomic and expression quantitative trait locus data analyses linked the neural aging patterns correlated with psychological resilience in middle adulthood to gene expression patterns suggestive of increased AD risk. Our results imply a partially antagonistic relationship between resilience against proximal stressors and longer-term psychological adjustment in later life. They thus underscore the importance of fine-tuning extant views on successful coping by considering the multiple timescales across which age-specific processes may unfold.

Amyloid-β oligomers in the nucleus accumbens decrease motivation via insertion of calcium-permeable AMPA receptors

It is essential to identify the neuronal mechanisms of Alzheimer's Disease (AD)-associated neuropsychiatric symptoms, e.g., apathy, before improving the life quality of AD patients. Here, we focused on the nucleus accumbens (NAc), a critical brain region processing motivation, also known to display AD-associated pathological changes in human cases. We found that the synaptic calcium permeable (CP)-AMPA receptors (AMPARs), which are normally absent in the NAc, can be revealed by acute exposure to Aβ oligomers (AβOs), and play a critical role in the emergence of synaptic loss and motivation deficits. Blockade of NAc CP-AMPARs can effectively prevent AβO-induced downsizing and pruning of spines and silencing of excitatory synaptic transmission. We conclude that AβO-triggered synaptic insertion of CP-AMPARs is a key mechanism mediating synaptic degeneration in AD, and preserving synaptic integrity may prevent or delay the onset of AD-associated psychiatric symptoms.

Recovery of superior frontal gyrus cortical thickness and resting-state functional connectivity in abstinent heroin users after 8 months of follow-up

Compared with healthy controls, heroin users (HUs) show evidence of structural and functional brain alterations. However, little is known about the possibility of brain recovery after protracted heroin abstinence. The purpose of this study was to investigate whether brain recovery is possible after protracted abstinence in HUs. A total of 108 subjects with heroin addiction completed structural and functional scans, and 61 of those subjects completed 8-month follow-up scans. Resting-state data and 3D-T1 MR images were collected for all participants, first at baseline and again after 8 months. Cognitive function and craving were measured by the Trail Making Test-A (TMT-A) and Visual Analog Scale for Craving, respectively. The cortical thickness and resting-state functional connectivity (RSFC) differences were then analyzed and compared between baseline and follow-up, and correlations were obtained between neuroimaging and behavioral changes. HUs demonstrated improved cognition (shorter TMT-A time) and reduced craving at the follow-up (HU2) relative to baseline (HU1), and the cortical thickness in the bilateral superior frontal gyrus (SFG) was significantly greater at HU2 than at HU1. Additionally, the RSFC of the left SFG with the inferior frontal gyrus (IFG), insula, and nucleus accumbens and that of the right SFG with the IFG, insula and orbitofrontal cortex (OFC) were increased at HU2. The changes in TMT-A time were negatively correlated with the RSFC changes between the left SFG and the bilateral IFG, the bilateral caudate, and the right insula. The changes in craving were negatively correlated with the RSFC changes between the left OFC and the bilateral SFG. Our results demonstrated that impaired frontal-limbic neurocircuitry can be partially restored, which might enable improved cognition as well as reduced craving in substance-abusing individuals. We provided novel scientific evidence for the partial recovery of brain circuits implicated in cognition and craving after protracted abstinence.

Verifying small vessel disease and mild cognitive impairment with a computational мagnetic resonance imaging analysis

Aim. To illustrate capabilities of the computational brain мagnetic resonance imaging (MRI) analyses on a small vessel disease (SVD) sample. Materials and methods. Thirty-one patients underwent brain MRI in standard sequences. We used Lesion Segmentation Tool to assess white matter hyperintensities (WMH) volume and Computational Anatomy Toolbox to calculate cortical thickness. Both software plug-ins work within the Statistical Parametric Mapping 12 software for MATLAB. We also performed cognitive testing with the Montreal Cognitive Assessment test and tests to detect hippocampal and executive domain dysfunction. Results. Sixteen patients had mild vascular cognitive impairment. The Median Fazekas scale score was 2 and 2 points. The median intracranial volume fraction occupied by the WMH was 0.07%. It correlated with the executive domain performance but not with cortical thickness. Cortical thickness within several clusters of the prefrontal complex and temporal lobe correlated with performance in cognitive tests. Among the computed MRI markers of the SVD, the occipital lobe cortical thickness had an area under the curve of 70%, and among the cognitive tests, the cued recall measure had an area under the curve of 73.8% to detect mild cognitive impairment. Conclusion. The abovementioned metrics is a valuable tool to objectively estimate white and grey matter state in patients with small vessel disease. Performing those analyses helped to assess SVD properties in the sample further and register new correlations between MRI and cognitive markers.

Associations Between Cerebral Vasoreactivity and Cognitive Function in the Middle-Aged Non-Demented Population

Background: Increasing evidence shows early vascular dysregulation in the pathophysiology of Alzheimer’s disease (AD) in elderly population. Objective: We wondered about the relationship between vascular health and cognitive performance in middle-aged adults. The present study aims to evaluate whether and which brain vascular hemodynamic parameters are associated with cognitive functions in a middle-aged, non-demented population. Methods: We recruited 490 middle-aged community-based participants (30–60 years). Transcranial color-coded sonography was used to measure cerebral vascular hemodynamics, including mean flow velocity, pulsatility index, and breath-holding index (BHI) in the middle cerebral arteries (MCAs). Cognitive functions were assessed using the Montreal Cognitive Assessment (MoCA). A multivariate linear regression model was used to determine the association between the MoCA scores and each intracranial hemodynamic parameter. Results: In 369 participants (median age 52 years [IQR 47–56], 48.8% men) with robust acoustic windows, the factors related to poorer MoCA scores were older age, less education extent, and the habitats of cigarette smoking or alcohol consumption. Multivariate analyses did not show a significant association between any intracranial hemodynamic parameters in both MCAs and MoCA scores in the total study population. Left MCA BHI was found to be significantly and independently correlated with the MoCA scores only in people aged 55–60 years (n = 111, B = 0.70, 95% confidence interval, 0.13–1.26, p = 0.017), however, not in people younger than 55 years. Conclusion: Our results emphasize the role of neurovascular abnormalities in the early pathophysiology of cognitive impairment and suggest cerebral vasoreactivity as the earliest detectable cognition-associated hemodynamic parameter.

Developmental Brain Asymmetry. The Good and the Bad Sides

Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.