Functional MRI of brain physiology in aging and neurodegenerative diseases

Stochastic brain dynamics exhibits differential regional distribution and maturation-related changes

Functional magnetic resonance imaging (fMRI) is a powerful non-invasive method for studying brain function by analyzing blood oxygenation level-dependent (BOLD) signals. These signals arise from intricate interplays of deterministic and stochastic biological elements. Quantifying the stochastic part is challenging due to its reliance on assumptions about the deterministic segment. We present a methodological framework to estimate intrinsic stochastic brain dynamics in fMRI data without assuming deterministic dynamics. Our approach utilizes Approximate Entropy and its behavior in noisy series to identify and characterize dynamical noise in unobservable fMRI dynamics. Applied to extensive fMRI datasets (645 Cam-CAN, 1086 Human Connectome Project subjects), we explore lifelong maturation of intrinsic brain noise. Findings indicate 10% to 60% of fMRI signal power is due to intrinsic stochastic brain elements, varying by age. These components demonstrate a physiological role of neural noise which shows a distinct distributions across brain regions and increase linearly during maturation.

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.

Brain vascularization in deep brain stimulation surgeries: epilepsy, Parkinson's disease, and obsessive-compulsive disorder

BACKGROUND

In our experience, we encountered more blood vessels during deep brain stimulation (DBS) surgeries in epilepsy. In this study, we have quantified and compared the cerebral vascularization in epilepsy, Parkinson's disease (PD) and obsessive-compulsive disorder (OCD).

METHODS

A retrospective observational study in 15 epilepsy and 15 PD patients was performed. The amount, location, and size of blood vessels within 5 millimeters (mm) of all DBS electrode trajectories (N.=120) for both targets (anterior nucleus of the thalamus: ANT and subthalamic nucleus: STN) in both patient groups were quantified and compared on a Medtronic workstation (Dublin, Ireland). Additionally, blood vessels in the trajectories (N.=120) of another group of 15 PD (STN) and 15 OCD (ventral capsule-ventral striatum [VC-VS]) patients were quantified and compared (trajectories N.=120), also to the first group. Statistical analyses were performed with SPSS version 27.0 (descriptive statistics, independent samples t-tests, Mann Whitney U Test, ANOVA Test and post-hoc Tukey Test). A P value <0.05 was considered statistically significant.

RESULTS

Our results showed a significant greater amount of cerebral blood vessels in epilepsy patients (10 SD±4) compared to PD (PD1 6 SD±1 and PD2 5 SD±3) and OCD (5 SD±1) with P<0.0001. Also, all other subanalyses showed more vascularization in the epilepsy group.

CONCLUSIONS

Our results show that the brain of epilepsy patients seems to be more vascularized compared to PD and OCD patients. This can make the surgical planning for DBS more challenging, and the use of multiple trajectories limited.

Targeting amyloid proteins for clinical diagnosis of neurodegenerative diseases

Abnormal aggregation and accumulation of pathological amyloid proteins such as amyloid-β, Tau, and α-synuclein play key pathological roles and serve as histological hallmarks in different neurodegenerative diseases (NDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD). In addition, various post-translational modifications (PTMs) have been identified on pathological amyloid proteins and are subjected to change during disease progression. Given the central role of amyloid proteins in NDs, tremendous efforts have been made to develop amyloid-targeting strategies for clinical diagnosis and molecular classification of NDs. In this review, we summarize two major strategies for targeting amyloid aggregates, with a focus on the trials in AD diagnosis. The first strategy is a positron emission tomography (PET) scan of protein aggregation in the brain. We mainly focus on introducing the development of small-molecule PET tracers for specifically recognizing pathological amyloid fibrils. The second strategy is the detection of PTM biomarkers on amyloid proteins in cerebrospinal fluid and plasma. We discuss the pathological roles of different PTMs in diseases and how we can use the PTM profile of amyloid proteins for clinical diagnosis. Finally, we point out the potential technical challenges of these two strategies, and outline other potential strategies, as well as a combination of multiple strategies, for molecular diagnosis of NDs.

Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R ² = 0.64) and paracentral gyrus (R ² = 0.71), and the left pars opercularis (R ² = 0.67), superior frontal gyrus (R ² = 0.62) and inferior parietal cortex (R ² = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.

Molecular Biomarkers of Neuronal Injury in Epilepsy Shared with Neurodegenerative Diseases

In neurodegenerative diseases, changes in neuronal proteins in the cerebrospinal fluid and blood are viewed as potential biomarkers of the primary pathology in the central nervous system (CNS). Recent reports suggest, however, that level of neuronal proteins in fluids also alters in several types of epilepsy in various age groups, including children. With increasing evidence supporting clinical and sub-clinical seizures in Alzheimer's disease, Lewy body dementia, Parkinson's disease, and in other less common neurodegenerative conditions, these findings call into question the specificity of neuronal protein response to neurodegenerative process and urge analysis of the effects of concomitant epilepsy and other comorbidities. In this article, we revisit the evidence for alterations in neuronal proteins in the blood and cerebrospinal fluid associated with epilepsy with and without neurodegenerative diseases. We discuss shared and distinctive characteristics of changes in neuronal markers, review their neurobiological mechanisms, and consider the emerging opportunities and challenges for their future research and diagnostic use.

Impaired dynamics of precapillary sphincters and pericytes at first-order capillaries predict reduced neurovascular function in the aging mouse brain

The microvascular inflow tract, comprising the penetrating arterioles, precapillary sphincters and first-order capillaries, is the bottleneck for brain blood flow and energy supply. Exactly how aging alters the structure and function of the microvascular inflow tract remains unclear. By in vivo four-dimensional two-photon imaging, we reveal an age-dependent decrease in vaso-responsivity accompanied by a decrease in vessel density close to the arterioles and loss of vascular mural cell processes, although the number of mural cell somas and their alpha smooth muscle actin density were preserved. The age-related reduction in vascular reactivity was mostly pronounced at precapillary sphincters, highlighting their crucial role in capillary blood flow regulation. Mathematical modeling revealed impaired pressure and flow control in aged mice during vasoconstriction. Interventions that preserve dynamics of cerebral blood vessels may ameliorate age-related decreases in blood flow and prevent brain frailty.

Association between social comparison orientation and hippocampal properties in older adults: A multimodal MRI study

Social comparison orientation (SCO) refers to the tendency to compare oneself with others and has two distinct dimensions: one about opinions and the other about abilities. Although dissociable neural mechanisms underlying the two dimensions of social comparison can be assumed, little is known about how each dimension of SCO is associated with cognitive and brain health among older adults. To investigate this, we analyzed the SCO scale questionnaire data, neuropsychological assessment data, and multimodal MRI data collected from 90 community-dwelling older adults. We found that global cognitive performance was positively correlated with the score of the opinion subscale but not with the score of the ability subscale and the total score. Similarly, hippocampal volume was positively correlated with opinion score alone. Additionally, the resting-state functional connectivity between the hippocampal seed and the default mode network showed a positive correlation only with the opinion score. Moreover, fractional anisotropy in the hippocampal cingulum was positively correlated with opinion score only. These findings suggest that global cognition and hippocampal properties in older age are associated with the SCO of opinion, which could reflect a regular habit of performing the types of cognitively demanding activities involved in evaluation of self and other opinions.

Spontaneous brain activity in healthy aging: An overview through fluctuations and regional homogeneity

Introduction

This study aims to explore whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences among age groups within a population ranging from middle age to older adults.

Methods

The sample comprised 112 healthy persons (M = 68.80, SD = 7.99) aged 48-89 who were split into six age groups (< 60, 60-64, 65-69, 70-74, 75-79, and ≥ 80). Fractional amplitude of low-frequency fluctuation and ReHo analyses were performed and were compared among the six age groups, and the significant results commonly found across groups were correlated with the gray matter volume of the areas and the age variable.

Results

Increased activity was found using fALFF in the superior temporal gyrus and inferior frontal gyrus when comparing the first group and the fifth. Regarding ReHo analysis, Group 6 showed increased ReHo in the temporal lobe (hippocampus), right and left precuneus, right caudate, and right and left thalamus depending on the age group. Moreover, significant correlations between age and fALFF and ReHo clusters, as well as with their gray matter volume were found, meaning that the higher the age, the higher the regional synchronization, the lower the fALFF activation, and the lower gray matter of the right thalamus.

Conclusion

Both techniques have been shown to be valuable and usable tools for disentangling brain changes in activation in a very low interval of years in healthy aging.

Hemodynamic MRI parameters to predict asymptomatic unilateral carotid artery stenosis with random forest machine learning

BACKGROUND

Internal carotid artery stenosis (ICAS) can cause stroke and cognitive decline. Associated hemodynamic impairments, which are most pronounced within individual watershed areas (iWSA) between vascular territories, can be assessed with hemodynamic-oxygenation-sensitive MRI and may help to detect severely affected patients. We aimed to identify the most sensitive parameters and volumes of interest (VOI) to predict high-grade ICAS with random forest machine learning. We hypothesized an increased predictive ability considering iWSAs and a decreased cognitive performance in correctly classified patients.

MATERIALS AND METHODS

Twenty-four patients with asymptomatic, unilateral, high-grade carotid artery stenosis and 24 age-matched healthy controls underwent MRI comprising pseudo-continuous arterial spin labeling (pCASL), breath-holding functional MRI (BH-fMRI), dynamic susceptibility contrast (DSC), T2 and T2* mapping, MPRAGE and FLAIR. Quantitative maps of eight perfusion, oxygenation and microvascular parameters were obtained. Mean values of respective parameters within and outside of iWSAs split into gray (GM) and white matter (WM) were calculated for both hemispheres and for interhemispheric differences resulting in 96 features. Random forest classifiers were trained on whole GM/WM VOIs, VOIs considering iWSAs and with additional feature selection, respectively.

RESULTS

The most sensitive features in decreasing order were time-to-peak (TTP), cerebral blood flow (CBF) and cerebral vascular reactivity (CVR), all of these inside of iWSAs. Applying iWSAs combined with feature selection yielded significantly higher receiver operating characteristics areas under the curve (AUC) than whole GM/WM VOIs (AUC: 0.84 vs. 0.90, p = 0.039). Correctly predicted patients presented with worse cognitive performances than frequently misclassified patients (Trail-making-test B: 152.5s vs. 94.4s, p = 0.034).

CONCLUSION

Random forest classifiers trained on multiparametric MRI data allow identification of the most relevant parameters and VOIs to predict ICAS, which may improve personalized treatments.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging

Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the adult lifespan

The preservation of cognitive function in old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort. As age differences in CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network were implicated in fluid reasoning. Age differences in CBF explained not only performance-related BOLD responses but also performance-independent BOLD responses. Our results suggest that CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function and preserve cognitive performance.

Multimodal striatal neuromarkers in distinguishing parkinsonian variant of multiple system atrophy from idiopathic Parkinson's disease

AIMS

To develop an automatic method of classification for parkinsonian variant of multiple system atrophy (MSA-P) and Idiopathic Parkinson's disease (IPD) in early to moderately advanced stages based on multimodal striatal alterations and identify the striatal neuromarkers for distinction.

METHODS

77 IPD and 75 MSA-P patients underwent 3.0 T multimodal MRI comprising susceptibility-weighted imaging, resting-state functional magnetic resonance imaging, T1-weighted imaging, and diffusion tensor imaging. Iron-radiomic features, volumes, functional and diffusion scalars of bilateral 10 striatal subregions were calculated and provided to the support vector machine for classification RESULTS: A combination of iron-radiomic features, function, diffusion, and volumetric measures optimally distinguished IPD and MSA-P in the testing dataset (accuracy 0.911 and area under the receiver operating characteristic curves [AUC] 0.927). The diagnostic performance further improved when incorporating clinical variables into the multimodal model (accuracy 0.934 and AUC 0.953). The most crucial factor for classification was the functional activity of the left dorsolateral putamen.

CONCLUSION

The machine learning algorithm applied to multimodal striatal dysfunction depicted dorsal striatum and supervening prefrontal lobe and cerebellar dysfunction through the frontostriatal and cerebello-striatal connections and facilitated accurate classification between IPD and MSA-P. The dorsolateral putamen was the most valuable neuromarker for the classification.

Imaging of Normal Brain Aging

Understanding normal brain aging physiology is essential to improving healthy human longevity, differentiation, and early detection of diseases, such as neurodegenerative diseases, which are an enormous social and economic burden. Functional decline, such as reduced physical activity and cognitive abilities, is typically associated with brain aging. The authors summarize the aging brain mechanism and effects of aging on the brain observed by brain structural MR imaging and advanced neuroimaging techniques, such as diffusion tensor imaging and functional MR imaging.

Neural Networks in Autosomal Dominant Alzheimer’s Disease: Insights From Functional Magnetic Resonance Imaging Studies

Alzheimer’s disease (AD) is the most common form of dementia, with no cure to stop its progression. Early detection, diagnosis, and intervention have become the hot spots in AD research. The long asymptomatic and slightly symptomatic phases of autosomal dominant AD (ADAD) allow studies to explore early biomarkers and the underlying pathophysiological changes. Functional magnetic resonance imaging (fMRI) provides a method to detect abnormal patterns of brain activity and functional connectivity in vivo, which correlates with cognitive decline earlier than structural changes and more strongly than amyloid deposition. Here, we will provide a brief overview of the network-level findings in ADAD in fMRI studies. In general, abnormalities in brain activity were mainly found in the hippocampus, the medial temporal lobe (MTL), the posterior cortex, the cingulate cortices, and the frontal regions in ADAD. Moreover, ADAD and sporadic AD (SAD) have similar fMRI changes, but not with aging.

Modeling neurodegenerative disorders in zebrafish

Neurodegeneration is a major cause of Alzheimer's, Parkinson's, Huntington's, multiple and amyotrophic lateral sclerosis, pontocerebellar hypoplasia, dementia and other related brain disorders. Their complex pathogenesis commonly includes genetic and neurochemical deficits, misfolded protein toxicity, demyelination, apoptosis and mitochondrial dysfunctions. Albeit differing in specific underlying mechanisms, neurodegenerative disorders typically display evolutionarily conserved mechanisms across taxa. Here, we review the role of zebrafish models in recapitulating major human and rodent neurodegenerative conditions, demonstrating this species as a highly relevant experimental model for research on neurodegenerative diseases, and discussing how these fish models can further clarify the underlying genetic, neurochemical, neuroanatomical and behavioral pathogenic mechanisms.

Age-Related Changes in Micro Brain Characteristics Based on Relaxed Mean-Field Model

Brain health is an important research direction of neuroscience. In addition to the effects of diseases, we cannot ignore the negative effect of aging on brain health. There have been many studies on brain aging, but only a few have used dynamic models to analyze differences in micro brain characteristics in healthy people. In this article, we use the relaxed mean-field model (rMFM) to study the effects of normal aging. Two main parameters of this model are the recurrent connection strength and subcortical input strength. The sensitivity of the rMFM to the initial values of the parameters has not been fully discussed in previous research. We examine this issue through repeated numerical experiments and obtain a reasonable initial parameter range for this model. Differences in recurrent connection strength and subcortical input strength due to aging have also not been studied previously. We use statistical methods to find the regions of interest (ROIs) exhibiting significant differences between young and old groups. Further, we carry out a difference analysis on the process of change of these ROIs on a more detailed timescale. We find that even with the same final results, the trends of change in these ROIs are different. This shows that to develop possible methods to prevent or delay brain damage due to aging, more attention needs to be paid to the trends of change of different ROIs, not just the final results.

Electrophysiological resting state brain network and episodic memory in healthy aging adults

Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.

Age Estimation from fMRI Data Using Recurrent Neural Network

Finding a biomarker that indicates the subject’s age is one of the most important topics in biology. Several recent studies tried to extract a biomarker from brain imaging data including fMRI data. However, most of them focused on MRI data, which do not provide dynamics and lack attempts to apply recently proposed deep learning models. We propose a deep neural network model that estimates the age of a subject from fMRI images using a recurrent neural network (RNN), more precisely, a gated recurrent unit (GRU). However, applying neural networks is not trivial due to the high dimensional nature of fMRI data. In this work, we propose a novel preprocessing technique using the Automated Anatomical Labeling (AAL) atlas, which significantly reduces the input dimension. The proposed dimension reduction technique allows us to train our model with 640 training and validation samples from different projects under mean squared error (MSE). Finally, we obtain the correlation value of 0.905 between the predicted age and the actual age on 155 test samples. The proposed model estimates the age within the range of ±12 on most of the test samples. Our model is written in Python and is freely available for download.

Evidence of cerebral hemodynamic dysregulation in middle-aged APOE ε4 carriers: The PREVENT-Dementia study

Accumulating evidence suggests vascular dysregulation in preclinical Alzheimer's disease. In this study, cerebral hemodynamics and their coupling with cognition in middle-aged apolipoprotein ε4 carriers (APOEε4+) were investigated. Longitudinal 3 T T1-weighted and arterial spin labelling MRI data from 158 participants (40-59 years old) in the PREVENT-Dementia study were analysed (125 two-year follow-up). Cognition was evaluated using the COGNITO battery. Cerebral blood flow (CBF) and cerebrovascular resistance index (CVRi) were quantified for the flow territories of the anterior, middle and posterior cerebral arteries. CBF was corrected for underlying atrophy and individual hematocrit. Hemodynamic measures were the dependent variables in linear regression models, with age, sex, years of education and APOEε4 carriership as predictors. Further analyses were conducted with cognitive outcomes as dependent variables, using the same model as before with additional APOEε4 × hemodynamics interactions. At baseline, APOEε4+ showed increased CBF and decreased CVRi compared to non-carriers in the anterior and middle cerebral arteries, suggestive of potential vasodilation. Hemodynamic changes were similar between groups. Interaction analysis revealed positive associations between CBF changes and performance changes in delayed recall (for APOEε4 non-carriers) and verbal fluency (for APOEε4 carriers) cognitive tests. These observations are consistent with neurovascular dysregulation in middle-aged APOEε4+.

The Spatiotemporal Coupling: Regional Energy Failure and Aberrant Proteins in Neurodegenerative Diseases

The spatial and temporal coordination of each element is a pivotal characteristic of systems, and the central nervous system (CNS) is not an exception. Glial elements and the vascular interface have been considered more recently, together with the extracellular matrix and the immune system. However, the knowledge of the single-element configuration is not sufficient to predict physiological or pathological long-lasting changes. Ionic currents, complex molecular cascades, genomic rearrangement, and the regional energy demand can be different even in neighboring cells of the same phenotype, and their differential expression could explain the region-specific progression of the most studied neurodegenerative diseases. We here reviewed the main nodes and edges of the system, which could be studied to develop a comprehensive knowledge of CNS plasticity from the neurovascular unit to the synaptic cleft. The future goal is to redefine the modeling of synaptic plasticity and achieve a better understanding of neurological diseases, pointing out cellular, subcellular, and molecular components that couple in specific neuroanatomical and functional regions.

Impaired cerebral vascular and metabolic responses to parametric N-back tasks in subjective cognitive decline

Previous studies reported abnormally increased and/or decreased blood oxygen level-dependent (BOLD) activations during functional tasks in subjective cognitive decline (SCD). The neurophysiological basis underlying these functional aberrations remains debated. This study aims to investigate vascular and metabolic responses and their dependence on cognitive processing loads during functional tasks in SCD. Twenty-one SCD and 18 control subjects performed parametric N-back working-memory tasks during MRI scans. Task-evoked percentage changes (denoted as δ) in cerebral blood volume (δCBV), cerebral blood flow (δCBF), BOLD signal (δBOLD) and cerebral metabolic rate of oxygen (δCMRO₂) were evaluated. In the frontal lobe, trends of decreased δCBV, δCBF and δCMRO₂ and increased δBOLD were observed in SCD compared with control subjects under lower loads, and these trends increased to significant differences under the 3-back load. δCBF was significantly correlated with δCMRO₂ in controls, but not in SCD subjects. As N-back loads increased, the differences between SCD and control subjects in δCBF and δCMRO₂ tended to enlarge. In the parietal lobe, no significant between-group difference was observed. Our findings suggested that impaired vascular and metabolic responses to functional tasks occurred in the frontal lobe of SCD, which contributed to unusual BOLD hyperactivation and was modulated by cognitive processing loads.

A novel method based on matching pursuit decomposition of gait signals for Parkinson's disease, Amyotrophic lateral sclerosis and Huntington's disease detection

BACKGROUND AND OBJECTIVE

An accurate detection of neurodegenerative diseases (NDDs) definitely improves the life of patients and has attracted growing attention.

METHODS

In this paper, a general automatic method for detection of Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS) and Huntington's disease (HD) has been proposed based on the localized time-frequency information of gait signals. The new main part of the detection method is to obtain a small set of sparse coefficients for the local representation of gait signals with appropriate time and frequency resolution. For this purpose, a hybrid feature set based on sparse matching pursuit decomposition and two sets of nonlinear and linear features has been developed. Then, principal components of the proposed feature have been analyzed using a sparse coding classifier. Results The proposed approach has achieved high average accuracy rates of 93%, 94%, and 97% for PD, ALS, and HD detection, respectively.

CONCLUSIONS

The obtained results have indicated that combination of time and frequency information of the gait signals through adaptive localized window length in MP makes it more efficient in comparison with the existing time, frequency or other time-frequency gait parameters. The great potential of nonlinear sparse features for PD and HD detection and linear ones for ALS detection has also been shown.

A brief review of non-invasive brain imaging technologies and the near-infrared optical bioimaging

Brain disorders seriously affect life quality. Therefore, non-invasive neuroimaging has received attention to monitoring and early diagnosing neural disorders to prevent their progress to a severe level. This short review briefly describes the current MRI and PET/CT techniques developed for non-invasive neuroimaging and the future direction of optical imaging techniques to achieve higher resolution and specificity using the second near-infrared (NIR-II) region of wavelength with organic molecules.

Dynamics of the Multipathway Regulation of the Vasodilator Bold Effect Induced by a Nerve Impulse: A Kinetic Model of the Neurovascular Coupling Process

A kinetic model of the dynamics of a multipathway mechanism of neurovascular coupling induced by nerve impulses was constructed. The model calculations were compared with experimental data on the changes in the blood oxygen level dependent signal during sensory-motor and visual excitation before and after the use of the nonsteroidal anti-inflammatory drug indomethacin. The influence of the catalytic activity of key enzymes on the dynamics of the neurovascular response in the proposed model is shown. The multipathway mechanism of the biochemical reactions provides stability of the neurovascular coupling during various possible catalytic activities of the key enzymes in the process.

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

The Role of Cerebrovascular-Reactivity Mapping in Functional MRI: Calibrated fMRI and Resting-State fMRI

Task and resting-state functional MRI (fMRI) is primarily based on the same blood-oxygenation level-dependent (BOLD) phenomenon that MRI-based cerebrovascular reactivity (CVR) mapping has most commonly relied upon. This technique is finding an ever-increasing role in neuroscience and clinical research as well as treatment planning. The estimation of CVR has unique applications in and associations with fMRI. In particular, CVR estimation is part of a family of techniques called calibrated BOLD fMRI, the purpose of which is to allow the mapping of cerebral oxidative metabolism (CMRO2) using a combination of BOLD and cerebral-blood flow (CBF) measurements. Moreover, CVR has recently been shown to be a major source of vascular bias in computing resting-state functional connectivity, in much the same way that it is used to neutralize the vascular contribution in calibrated fMRI. Furthermore, due to the obvious challenges in estimating CVR using gas challenges, a rapidly growing field of study is the estimation of CVR without any form of challenge, including the use of resting-state fMRI for that purpose. This review addresses all of these aspects in which CVR interacts with fMRI and the role of CVR in calibrated fMRI, provides an overview of the physiological biases and assumptions underlying hypercapnia-based CVR and calibrated fMRI, and provides a view into the future of non-invasive CVR measurement.

Magnetic Resonance Imaging of Marmoset Monkeys

The use of the common marmoset monkey (Callithrix jacchus) for neuroscientific research has grown markedly in the last decade. Magnetic resonance imaging (MRI) has played a significant role in establishing the extent of comparability of marmoset brain architecture with the human brain and brains of other preclinical species (eg, macaques and rodents). As a non-invasive technique, MRI allows for the flexible acquisition of the same sequences across different species in vivo, including imaging of whole-brain functional topologies not possible with more invasive techniques. Being one of the smallest New World primates, the marmoset may be an ideal nonhuman primate species to study with MRI. As primates, marmosets have an elaborated frontal cortex with features analogous to the human brain, while also having a small enough body size to fit into powerful small-bore MRI systems typically employed for rodent imaging; these systems offer superior signal strength and resolution. Further, marmosets have a rich behavioral repertoire uniquely paired with a lissencephalic cortex (like rodents). This smooth cortical surface lends itself well to MRI and also other invasive methodologies. With the advent of transgenic modification techniques, marmosets have gained significant traction as a powerful complement to canonical mammalian modelling species. Marmosets are poised to make major contributions to preclinical investigations of the pathophysiology of human brain disorders as well as more basic mechanistic explorations of the brain. The goal of this article is to provide an overview of the practical aspects of implementing MRI and fMRI in marmosets (both under anesthesia and fully awake) and discuss the development of resources recently made available for marmoset imaging.

From research to clinical practice: a European neuroradiological survey on quantitative advanced MRI implementation

Objective

Quantitative MRI (qMRI) methods provide versatile neuroradiological applications and are a hot topic in research. The degree of their clinical implementation is however barely known. This survey was created to illuminate which and how qMRI techniques are currently applied across Europe.

Methods

In total, 4753 neuroradiologists from 27 countries received an online questionnaire. Demographic and professional data, experience with qMRI techniques in the brain and head and neck, usage, reasons for/against application, and knowledge of the QIBA and EIBALL initiatives were assessed.

Results

Two hundred seventy-two responders in 23 countries used the following techniques clinically (mean values in %): DWI (82.0%, n = 223), DSC (67.3%, n = 183), MRS (64.3%, n = 175), DCE (43.4%, n = 118), BOLD-fMRI (42.6%, n = 116), ASL (37.5%, n = 102), fat quantification (25.0%, n = 68), T2 mapping (16.9%, n = 46), T1 mapping (15.1%, n = 41), PET-MRI (11.8%, n = 32), IVIM (5.5%, n = 15), APT-CEST (4.8%, n = 13), and DKI (3.3%, n = 9). The most frequent usage indications for any qMRI technique were tissue differentiation (82.4%, n = 224) and oncological monitoring (72.8%, n = 198). Usage differed between countries, e.g. ASL: Germany (n = 13/63; 20.6%) vs. France (n = 31/40; 77.5%). Neuroradiologists endorsed the use of qMRI because of an improved diagnostic accuracy (89.3%, n = 243), but 50.0% (n = 136) are in need of better technology, 34.9% (n = 95) wish for more communication, and 31.3% need help with result interpretation/generation (n = 85). QIBA and EIBALL were not well known (12.5%, n = 34, and 11.0%, n = 30).

Conclusions

The clinical implementation of qMRI methods is highly variable. Beyond the aspect of readiness for clinical use, better availability of support and a wider dissemination of guidelines could catalyse a broader implementation.

Key Points

• Neuroradiologists endorse the use of qMRI techniques as they subjectively improve diagnostic accuracy.

• Clinical implementation is highly variable between countries, techniques, and indications.

• The use of advanced imaging could be promoted through an increase in technical support and training of both doctors and technicians.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-020-07582-2.

Locus Coeruleus and neurovascular unit: From its role in physiology to its potential role in Alzheimer's disease pathogenesis

Locus coeruleus (LC) is the main noradrenergic (NA) nucleus of the central nervous system. LC degenerates early during Alzheimer's disease (AD) and NA loss might concur to AD pathogenesis. Aside from neurons, LC terminals provide dense innervation of brain intraparenchymal arterioles/capillaries, and NA modulates astrocyte functions. The term neurovascular unit (NVU) defines the strict anatomical/functional interaction occurring between neurons, glial cells, and brain vessels. NVU plays a fundamental role in coupling the energy demand of activated brain regions with regional cerebral blood flow, it includes the blood-brain barrier (BBB), plays an active role in neuroinflammation, and participates also to the glymphatic system. NVU alteration is involved in AD pathophysiology through several mechanisms, mainly related to a relative oligoemia in activated brain regions and impairment of structural and functional BBB integrity, which contributes also to the intracerebral accumulation of insoluble amyloid. We review the existing data on the morphological features of LC-NA innervation of the NVU, as well as its contribution to neurovascular coupling and BBB proper functioning. After introducing the main experimental data linking LC with AD, which have repeatedly shown a key role of neuroinflammation and increased amyloid plaque formation, we discuss the potential mechanisms by which the loss of NVU modulation by LC might contribute to AD pathogenesis. Surprisingly, thus far not so many studies have tested directly these mechanisms in models of AD in which LC has been lesioned experimentally. Clarifying the interaction of LC with NVU in AD pathogenesis may disclose potential therapeutic targets for AD.

Quantitative Cerebrovascular Reactivity in Normal Aging: Comparison Between Phase-Contrast and Arterial Spin Labeling MRI

Purpose: Cerebrovascular reactivity (CVR) is an index of the dilatory function of cerebral blood vessels and has shown great promise in the diagnosis of risk factors in cerebrovascular disease. Aging is one such risk factor; thus, it is important to characterize age-related differences in CVR. CVR can be measured by BOLD MRI but few studies have measured quantitative cerebral blood flow (CBF)-based CVR in the context of aging. This study aims to determine the age effect on CVR using two quantitative CBF techniques, phase-contrast (PC), and arterial spin labeling (ASL) MRI.

Methods: In 49 participants (32 younger and 17 older), CVR was measured with PC, ASL, and BOLD MRI. These CVR methods were compared across young and older groups to determine their dependence on age. PC and ASL CVR were also studied for inter-correlation and mean differences. Gray and white matter CVR values were also studied.

Results: PC CVR was higher in younger participants than older participants (by 17%, p = 0.046). However, there were no age differences in ASL or BOLD CVR. ASL CVR was significantly correlated with PC CVR (p = 0.042) and BOLD CVR (p = 0.016), but its values were underestimated compared to PC CVR (p = 0.045). ASL CVR map revealed no difference between gray matter and white matter tissue types, whereas gray matter was significantly higher than white matter in the BOLD CVR map.

Conclusion: This study compared two quantitative CVR techniques in the context of brain aging and revealed that PC CVR is a more sensitive method for detection of age differences, despite the absence of spatial information. The ASL method showed a significant correlation with PC and BOLD, but it tends to underestimate CVR due to confounding factors associated with this technique. Importantly, our data suggest that there is not a difference in CBF-based CVR between the gray and white matter, in contrast to previous observation using BOLD MRI.

Integrity of Neurocognitive Networks in Dementing Disorders as Measured with Simultaneous PET/Functional MRI

Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with ¹⁸F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous resting-state fMRI and ¹⁸F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and ¹⁸F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.

Enhanced Gray Matter Volume Compensates for Decreased Brain Activity in the Ocular Motor Area in Children with Anisometropic Amblyopia

Purpose

Anisometropic amblyopia usually occurs during early childhood and results in monocular visual deficit. Recent neuroimaging studies have demonstrated structural and functional alterations in pediatric anisometropic amblyopia (PAA) patients. However, the relationship between structural and functional alterations remains largely unknown. The aim of this study was to investigate the relationship between structural and functional alterations in PAA patients.

Materials and Methods

Eighteen PAA patients and 14 healthy children underwent a multimodal MRI scanning including T1WI and functional MRI (fMRI). Voxel-based morphometry was used to assess structural alterations between PAA patients and healthy children. Regional homogeneity (ReHo) was used to investigate changes in local spontaneous brain activity in the enrolled subjects. Correlations between structural, functional alterations, and clinical information were analyzed in the PAA group.

Results

Compared with healthy children, PAA patients exhibited significantly reduced ReHo of spontaneous brain activity in the right superior temporal gyrus (STG) and right middle frontal gyrus (MFG) and increased gray matter volume in the right lobules 4 and 5 of the cerebellum. The gray matter volume of the right lobules 4 and 5 of the cerebellum was negatively correlated with the ReHo values of the right MFG.

Conclusions

Our findings may suggest that PAA patients experience structural and functional abnormalities in brain regions related to oculomotor and visual-spatial information. In addition, the increased gray matter volume may compensate the decreased brain activity in the oculomotor regions, which reflects compensatory or neural plasticity in PAA patients.

The Application of the Rorschach Inkblot Test in the Study of Neural and Cognitive Aging

Abstract. The Rorschach Inkblot test has been adopted and adapted by many researchers to assess and predict different aspects of human experience and cognitive performance. The present review examines research that incorporates the Rorschach to evaluate neural and cognitive aging as well as decline in age-related disease. Specifically, differences in amygdala and cortical regions, as well as mirror neuron and asymmetrical hemisphere activity that correlate with specific responses to Rorschach stimuli are discussed in the context of typical changes in brain structure and function in the course of aging. In addition, the present review provides a proposed framework for expanding the use of the Rorschach to evaluate other domains of neural and cognitive function. The authors conclude that, despite a need for increased research, the Rorschach is a viable measure to evaluate certain aspects of cognitive function and decline throughout the lifespan.

Are Kynurenines Accomplices or Principal Villains in Dementia? Maintenance of Kynurenine Metabolism

Worldwide, 50 million people suffer from dementia, a group of symptoms affecting cognitive and social functions, progressing severely enough to interfere with daily life. Alzheimer’s disease (AD) accounts for most of the dementia cases. Pathological and clinical findings have led to proposing several hypotheses of AD pathogenesis, finding a presence of positive feedback loops and additionally observing the disturbance of a branch of tryptophan metabolism, the kynurenine (KYN) pathway. Either causative or resultant of dementia, elevated levels of neurotoxic KYN metabolites are observed, potentially upregulating multiple feedback loops of AD pathogenesis. Memantine is an N-methyl-D-aspartate glutamatergic receptor (NMDAR) antagonist, which belongs to one of only two classes of medications approved for clinical use, but other NMDAR modulators have been explored so far in vain. An endogenous KYN pathway metabolite, kynurenic acid (KYNA), likewise inhibits the excitotoxic NMDAR. Besides its anti-excitotoxicity, KYNA is a multitarget compound that triggers anti-inflammatory and antioxidant activities. Modifying the KYNA level is a potential multitarget strategy to normalize the disturbed KYN pathway and thus to alleviate juxtaposing AD pathogeneses. In this review, the maintenance of KYN metabolism by modifying the level of KYNA is proposed and discussed in search for a novel lead compound against the progression of dementia.

The association between BOLD-based cerebrovascular reactivity (CVR) and end-tidal CO2 in healthy subjects

Cerebrovascular reactivity (CVR) mapping using CO₂-inhalation can provide important insight into vascular health. At present, blood-oxygenation-level-dependent (BOLD) MRI acquisition is the most commonly used CVR method due to its high sensitivity, high spatial resolution, and relatively straightforward processing. However, large variations in CVR across subjects and across different sessions of the same subject are often observed, which can cloud the ability of this promising measure in detecting diseases or monitoring treatment responses. The present work aims to identify the physiological components underlying the observed variability in CVR data. When studying the association between CVR value and the subject’s CO₂ levels in a total of N = 253 healthy participants, we found that CVR was lower in individuals with a higher basal end-tidal CO₂, EtCO₂ (slope = −0.0036 ± 0.0008%/mmHg², p < 0.001), or with a greater EtCO₂ change (ΔEtCO₂) with hypercapnic condition (slope = −0.0072 ± 0.0018%/mmHg², p < 0.001). In a within-subject setting, when studying the CVR difference between two repeated scans (with repositioning) in relation to the corresponding differences in basal EtCO₂ and ΔEtCO₂ (n = 11), it was found that CVR values were lower if the basal EtCO₂ or ΔEtCO₂ during that particular scan session was greater. The present work suggests that basal physiological state and the level of hypercapnic stimulus intensity should be considered in application studies of CVR in order to reduce inter-subject and intra-subject variations in the data. Potential approaches to use these findings to reduce noise and augment sensitivity are proposed.

Imaging the aged brain: pertinence and methods

The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.