Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions

Understanding how the brain's macroscale dynamics are shaped by underlying microscale mechanisms is a key problem in neuroscience. In animal models, we can now investigate this relationship in unprecedented detail by directly manipulating cellular-level properties while measuring the whole-brain response using resting-state fMRI. Here, we focused on understanding how blood-oxygen-level-dependent (BOLD) dynamics, measured within a structurally well-defined striato-thalamo-cortical circuit in mice, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial caudate putamen (CPdm). We characterize changes in both the BOLD dynamics of individual cortical and subcortical brain areas, and patterns of inter-regional coupling (functional connectivity) between pairs of areas. Using a classification approach based on a large and diverse set of time-series properties, we found that CPdm neuromodulation alters BOLD dynamics within thalamic subregions that project back to dorsomedial striatum. In the cortex, changes in local dynamics were strongest in unimodal regions (which process information from a single sensory modality) and weakened along a hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results show that targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, such as by making BOLD dynamics more predictable over time by increasing its self-correlation structure. This contributes to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.

QuNex-An integrative platform for reproducible neuroimaging analytics

Introduction

Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability.

Methods

To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a "turnkey" command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features.

Results

The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform.

Discussion

Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.

A consensus protocol for functional connectivity analysis in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

Modeling Brain Dysconnectivity in Rodents

Altered or atypical functional connectivity as measured with functional magnetic resonance imaging (fMRI) is a hallmark feature of brain connectopathy in psychiatric, developmental, and neurological disorders. However, the biological underpinnings and etiopathological significance of this phenomenon remain unclear. The recent development of MRI-based techniques for mapping brain function in rodents provides a powerful platform to uncover the determinants of functional (dys)connectivity, whether they are genetic mutations, environmental risk factors, or specific cellular and circuit dysfunctions. Here, we summarize the recent contribution of rodent fMRI toward a deeper understanding of network dysconnectivity in developmental and psychiatric disorders. We highlight substantial correspondences in the spatiotemporal organization of rodent and human fMRI networks, supporting the translational relevance of this approach. We then show how this research platform might help us comprehend the importance of connectional heterogeneity in complex brain disorders and causally relate multiscale pathogenic contributors to functional dysconnectivity patterns. Finally, we explore how perturbational techniques can be used to dissect the fundamental aspects of fMRI coupling and reveal the causal contribution of neuromodulatory systems to macroscale network activity, as well as its altered dynamics in brain diseases. These examples outline how rodent functional imaging is poised to advance our understanding of the bases and determinants of human functional dysconnectivity.

CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility

Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in the brain, which are particularly important for higher-order cognitive function and flexibility. However, whether a causal relationship exists between interhemispheric connectivity alterations and cognitive deficits in NDD remains elusive. Here, we focused on CDKL5 Deficiency Disorder (CDD), a severe neurodevelopmental disorder caused by mutations in the X-linked Cyclin-dependent kinase-like 5 (CDKL5) gene. We found an increase in homotopic interhemispheric connectivity and functional hyperconnectivity across higher cognitive areas in adult male and female CDKL5-deficient mice by resting-state functional MRI (rs-fMRI) analysis. This was accompanied by an increase in the number of callosal synaptic inputs but decrease in local synaptic connectivity in the cingulate cortex of juvenile CDKL5-deficient mice, suggesting an impairment in excitatory synapse development and a differential role of CDKL5 across excitatory neuron subtypes. These deficits were associated with significant cognitive impairments in CDKL5 KO mice. Selective deletion of CDKL5 in the largest subtype of CPN likewise resulted in an increase of functional callosal inputs, without however significantly altering intracortical cingulate networks. Notably, such callosal-specific changes were sufficient to cause cognitive deficits. Finally, when CDKL5 was selectively re-expressed only in this CPN subtype, in otherwise CDKL5-deficient mice, it was sufficient to prevent the cognitive impairments of CDKL5 mutants. Together, these results reveal a novel role of CDKL5 by demonstrating that it is both necessary and sufficient for proper CPN connectivity and cognitive function and flexibility, and further validates a causal relationship between CPN dysfunction and cognitive impairment in a model of NDD.

Extracting Dynamical Understanding From Neural-Mass Models of Mouse Cortex

New brain atlases with high spatial resolution and whole-brain coverage have rapidly advanced our knowledge of the brain's neural architecture, including the systematic variation of excitatory and inhibitory cell densities across the mammalian cortex. But understanding how the brain's microscale physiology shapes brain dynamics at the macroscale has remained a challenge. While physiologically based mathematical models of brain dynamics are well placed to bridge this explanatory gap, their complexity can form a barrier to providing clear mechanistic interpretation of the dynamics they generate. In this work, we develop a neural-mass model of the mouse cortex and show how bifurcation diagrams, which capture local dynamical responses to inputs and their variation across brain regions, can be used to understand the resulting whole-brain dynamics. We show that strong fits to resting-state functional magnetic resonance imaging (fMRI) data can be found in surprisingly simple dynamical regimes—including where all brain regions are confined to a stable fixed point—in which regions are able to respond strongly to variations in their inputs, consistent with direct structural connections providing a strong constraint on functional connectivity in the anesthetized mouse. We also use bifurcation diagrams to show how perturbations to local excitatory and inhibitory coupling strengths across the cortex, constrained by cell-density data, provide spatially dependent constraints on resulting cortical activity, and support a greater diversity of coincident dynamical regimes. Our work illustrates methods for visualizing and interpreting model performance in terms of underlying dynamical mechanisms, an approach that is crucial for building explanatory and physiologically grounded models of the dynamical principles that underpin large-scale brain activity.

Arterial spin labeling demonstrates preserved regional cerebral blood flow in the P301L mouse model of tauopathy

There is growing evidence for the vascular contribution to cognitive impairment and dementia in Alzheimer's disease (AD) and other neurodegenerative diseases. While perfusion deficits have been observed in patients with Alzheimer's disease and tauopaties, little is known about the role of tau in vascular dysfunction. In the present study, regional cerebral blood (rCBF) was characterized in P301L mice with arterial spin labeling. No differences in rCBF in P301L mice compared to their age-matched non-transgenic littermates at mid (10-12 months of age) and advanced (19-21 months of age) disease stages. This was concomitant with preservation of cortical brain structure as assessed with structural T₂-weighted magnetic resonance imaging. These results show that hypoperfusion and neurodegeneration are not a phenotype of P301L mice. More studies are thus needed to understand the relationship of tau, neurodegeneration and vascular dysfunction and its modulators in AD and primary tauopathies.

Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia

The basal ganglia (BG) are a group of subcortical nuclei responsible for motor and executive function. Central to BG function are striatal cells expressing D1 (D1R) and D2 (D2R) dopamine receptors. D1R and D2R cells are considered functional antagonists that facilitate voluntary movements and inhibit competing motor patterns, respectively. However, whether they maintain a uniform function across the striatum and what influence they exert outside the BG is unclear. Here, we address these questions by combining optogenetic activation of D1R and D2R cells in the mouse ventrolateral caudoputamen with fMRI. Striatal D1R/D2R stimulation evokes distinct activity within the BG-thalamocortical network and differentially engages cerebellar and prefrontal regions. Computational modeling of effective connectivity confirms that changes in D1R/D2R output drive functional relationships between these regions. Our results suggest a complex functional organization of striatal D1R/D2R cells and hint toward an interconnected fronto-BG-cerebellar network modulated by striatal D1R and D2R cells.

Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes

Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modeled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.

Prenatal interleukin 6 elevation increases glutamatergic synapse density and disrupts hippocampal connectivity in offspring

Early prenatal inflammatory conditions are thought to be a risk factor for different neurodevelopmental disorders. Maternal interleukin-6 (IL-6) elevation during pregnancy causes abnormal behavior in offspring, but whether these defects result from altered synaptic developmental trajectories remains unclear. Here we showed that transient IL-6 elevation via injection into pregnant mice or developing embryos enhanced glutamatergic synapses and led to overall brain hyperconnectivity in offspring into adulthood. IL-6 activated synaptogenesis gene programs in glutamatergic neurons and required the transcription factor STAT3 and expression of the RGS4 gene. The STAT3-RGS4 pathway was also activated in neonatal brains during poly(I:C)-induced maternal immune activation, which mimics viral infection during pregnancy. These findings indicate that IL-6 elevation at early developmental stages is sufficient to exert a long-lasting effect on glutamatergic synaptogenesis and brain connectivity, providing a mechanistic framework for the association between prenatal inflammatory events and brain neurodevelopmental disorders.

Emerging imaging methods to study whole-brain function in rodent models

In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.

Toward integrative approaches to study the causal role of neural oscillations via transcranial electrical stimulation

Diverse transcranial electrical stimulation (tES) techniques have recently been developed to elucidate the role of neural oscillations, but critically, it remains questionable whether neural entrainment genuinely occurs and is causally related to the resulting behavior. Here, we provide a perspective on an emerging integrative research program across systems, species, theoretical and experimental frameworks to elucidate the potential of tES to induce neural entrainment. We argue that such an integrative agenda is a requirement to establish tES as a tool to test the causal role of neural oscillations and highlight critical issues that should be considered when adopting a translational approach.

Imaging evolution of the primate brain: the next frontier?

Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.

Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions

To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recognize ethologically relevant behaviors and lack the flexibility to be employed in variable testing environments. Critical advances based on deep-learning and machine vision over the last couple of years now enable markerless tracking of individual body parts of freely moving rodents with high precision. Here, we compare the performance of commercially available platforms (EthoVision XT14, Noldus; TSE Multi-Conditioning System, TSE Systems) to cross-verified human annotation. We provide a set of videos-carefully annotated by several human raters-of three widely used behavioral tests (open field test, elevated plus maze, forced swim test). Using these data, we then deployed the pose estimation software DeepLabCut to extract skeletal mouse representations. Using simple post-analyses, we were able to track animals based on their skeletal representation in a range of classic behavioral tests at similar or greater accuracy than commercial behavioral tracking systems. We then developed supervised machine learning classifiers that integrate the skeletal representation with the manual annotations. This new combined approach allows us to score ethologically relevant behaviors with similar accuracy to humans, the current gold standard, while outperforming commercial solutions. Finally, we show that the resulting machine learning approach eliminates variation both within and between human annotators. In summary, our approach helps to improve the quality and accuracy of behavioral data, while outperforming commercial systems at a fraction of the cost.

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.

Shedding Light on Social Reward Circuitry: (Un)common Blueprints in Humans and Rodents

Human behavior is strongly influenced by our motivation to establish social relationships and maintain them throughout life. Despite the importance of social behavior across species, it is still unclear how neural mechanisms drive social actions. Rodent models have been used for decades to unravel the neural pathways and substrates of social interactions. With the advent of novel approaches to selectively modulate brain circuits in animal models, unprecedented testing of brain regions and neuromodulators that encode social information can be achieved. However, it is unclear which classes of social behavior and related neural circuits can be generalized across species and which are unique to humans. There is a growing need to define a unified blueprint of social brain systems. Here, we review human and rodent literature on the brain's social actuators, specifically focusing on social motivation. We discuss the potential of implementing multimodal neuroimaging to guide us toward a consensus of brain areas and circuits for social behavior regulation. Understanding the circuital similarity and diversity is the critical step to improve the translation of research findings from rodents to humans.

Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

Primate homologs of mouse cortico-striatal circuits

With the increasing necessity of animal models in biomedical research, there is a vital need to harmonise findings across species by establishing similarities and differences in rodent and primate neuroanatomy. Using connectivity fingerprint matching, we compared cortico-striatal circuits across humans, non-human primates, and mice using resting-state fMRI data in all species. Our results suggest that the connectivity patterns for the nucleus accumbens and cortico-striatal motor circuits (posterior/lateral putamen) were conserved across species, making them reliable targets for cross-species comparisons. However, a large number of human and macaque striatal voxels were not matched to any mouse cortico-striatal circuit (mouse->human: 85% unassigned; mouse->macaque 69% unassigned; macaque->human; 31% unassigned). These unassigned voxels were localised to the caudate nucleus and anterior putamen, overlapping with executive function and social/language regions of the striatum and connected to prefrontal-projecting cerebellar lobules and anterior prefrontal cortex, forming circuits that seem to be unique for non-human primates and humans.

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

Directed functional connectivity using dynamic graphical models

There are a growing number of neuroimaging methods that model spatio-temporal patterns of brain activity to allow more meaningful characterizations of brain networks. This paper proposes dynamic graphical models (DGMs) for dynamic, directed functional connectivity. DGMs are a multivariate graphical model with time-varying coefficients that describe instantaneous directed relationships between nodes. A further benefit of DGMs is that networks may contain loops and that large networks can be estimated. We use network simulations and human resting-state fMRI (N = 500) to investigate the validity and reliability of the estimated networks. We simulate systematic lags of the hemodynamic response at different brain regions to investigate how these lags potentially bias directionality estimates. In the presence of such lag confounds (0.4-0.8 s offset between connected nodes), our method has a sensitivity of 72%-77% to detect the true direction. Stronger lag confounds have reduced sensitivity, but do not increase false positives (i.e., directionality estimates of the opposite direction). In human resting-state fMRI, the default mode network has consistent influence on the cerebellar, the limbic and the auditory/temporal networks. We also show a consistent reciprocal relationship between the visual medial and visual lateral network. Finally, we apply the method in a small mouse fMRI sample and discover a highly plausible relationship between areas in the hippocampus feeding into the cingulate cortex. We provide a computationally efficient implementation of DGM as a free software package for R.

Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories

Autism spectrum disorders (ASD) are a set of complex neurodevelopmental disorders for which there is currently no targeted therapeutic approach. It is thought that alterations of genes regulating migration and synapse formation during development affect neural circuit formation and result in aberrant connectivity within distinct circuits that underlie abnormal behaviors. However, it is unknown whether deviant developmental trajectories are circuit-specific for a given autism risk-gene. We used MRI to probe changes in functional and structural connectivity from childhood to adulthood in Fragile-X (Fmr1-/y) and contactin-associated (CNTNAP2-/-) knockout mice. Young Fmr1-/y mice (30 days postnatal) presented with a robust hypoconnectivity phenotype in corticocortico and corticostriatal circuits in areas associated with sensory information processing, which was maintained until adulthood. Conversely, only small differences in hippocampal and striatal areas were present during early postnatal development in CNTNAP2-/- mice, while major connectivity deficits in prefrontal and limbic pathways developed between adolescence and adulthood. These findings are supported by viral tracing and electron micrograph approaches and define 2 clearly distinct connectivity endophenotypes within the autism spectrum. We conclude that the genetic background of ASD strongly influences which circuits are most affected, the nature of the phenotype, and the developmental time course of the associated changes.

The Microglial Innate Immune Receptor TREM2 Is Required for Synapse Elimination and Normal Brain Connectivity

The triggering receptor expressed on myeloid cells 2 (TREM2) is a microglial innate immune receptor associated with a lethal form of early, progressive dementia, Nasu-Hakola disease, and with an increased risk of Alzheimer's disease. Microglial defects in phagocytosis of toxic aggregates or apoptotic membranes were proposed to be at the origin of the pathological processes in the presence of Trem2 inactivating mutations. Here, we show that TREM2 is essential for microglia-mediated synaptic refinement during the early stages of brain development. The absence of Trem2 resulted in impaired synapse elimination, accompanied by enhanced excitatory neurotransmission and reduced long-range functional connectivity. Trem2^-/- mice displayed repetitive behavior and altered sociability. TREM2 protein levels were also negatively correlated with the severity of symptoms in humans affected by autism. These data unveil the role of TREM2 in neuronal circuit sculpting and provide the evidence for the receptor's involvement in neurodevelopmental diseases.

White matter changes and gait decline in cerebral small vessel disease

The relation between progression of cerebral small vessel disease (SVD) and gait decline is uncertain, and diffusion tensor imaging (DTI) studies on gait decline are lacking. We therefore investigated the longitudinal associations between (micro) structural brain changes and gait decline in SVD using DTI. 275 participants were included from the Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort (RUN DMC), a prospective cohort of participants with cerebral small vessel disease aged 50-85 years. Gait (using GAITRite) and magnetic resonance imaging measures were assessed during baseline (2006-2007) and follow-up (2011 - 2012). Linear regression analysis was used to investigate the association between changes in conventional magnetic resonance and diffusion tensor imaging measures and gait decline. Tract-based spatial statistics analysis was used to investigate region-specific associations between changes in white matter integrity and gait decline. 56.2% were male, mean age was 62.9 years (SD8.2), mean follow-up duration was 5.4 years (SD0.2) and mean gait speed decline was 0.2 m/s (SD0.2). Stride length decline was associated with white matter atrophy (β = 0.16, p = 0.007), and increase in mean white matter radial diffusivity and mean diffusivity, and decrease in mean fractional anisotropy (respectively, β = - 0.14, p = 0.009; β = - 0.12, p = 0.018; β = 0.10, p = 0.049), independent of age, sex, height, follow-up duration and baseline stride length. Tract-based spatial statistics analysis showed significant associations between stride length decline and fractional anisotropy decrease and mean diffusivity increase (primarily explained by radial diffusivity increase) in multiple white matter tracts, with the strongest associations found in the corpus callosum and corona radiata, independent of traditional small vessel disease markers. White matter atrophy and loss of white matter integrity are associated with gait decline in older adults with small vessel disease after 5 years of follow-up. These findings suggest that progression of SVD might play an important role in gait decline.

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ=0.58), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ=-0.43). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Hypertension, cerebrovascular impairment, and cognitive decline in aged AβPP/PS1 mice

Cardiovascular risk factors, especially hypertension, are also major risk factors for Alzheimer's disease (AD). To elucidate the underlying vascular origin of neurodegenerative processes in AD, we investigated the relation between systolic blood pressure (SBP) cerebral blood flow (CBF) and vasoreactivity with brain structure and function in a 16-18 months old double transgenic AβPP_swe/PS1_dE9 (AβPP/PS1) mouse model for AD. These aging AβPP/PS1 mice showed an increased SBP linked to a declined regional CBF. Furthermore, using advanced MRI techniques, decline of functional and structural connectivity was revealed in the AD-like mice coupled to impaired cognition, increased locomotor activity, and anxiety-related behavior. Post mortem analyses demonstrated also increased neuroinflammation, and both decreased synaptogenesis and neurogenesis in the AβPP/PS1 mice. Additionally, deviant levels of fatty acids and sterols were present in the brain tissue of the AβPP/PS1 mice indicating maladapted brain fatty acid metabolism. Our findings suggest a link between increased SBP, decreased cerebral hemodynamics and connectivity in an AD mouse model during aging, leading to behavioral and cognitive impairments. As these results mirror the complex clinical symptomatology in the prodromal phase of AD, we suggest that this AD-like murine model could be used to investigate prevention and treatment strategies for early AD patients. Moreover, this study helps to develop more efficient therapies and diagnostics for this very early stage of AD.

Hypertension Impairs Cerebral Blood Flow in a Mouse Model for Alzheimer's Disease

AIMS

Hypertension, a risk factor for Alzheimer's disease (AD), is a treatable condition, which offers possibilities for prevention of AD. Elevated angiotensin II (AngII) is an important cause of essential hypertension. AngII has deleterious effects on endothelial function and cerebral blood flow (CBF), which may contribute to AD. AngII blocking agents can thus provide potential candidates to reduce AD risk factors in hypertensive patients.

METHODS

We studied the effect of 2 months induced hypertension (AngII-infusion via osmotic micropumps) on systolic blood pressure (SBP) and CBF in 10 months-old wild-type (WT) C57bl/6j and AβPPswe/PS1ΔE9 (AβPP/PS1) mice, and treatment with two different antihypertensives, 1) eprosartan mesylate (EM, 0.35mg/kg) or 2) hydrochlorotiazide (HCT, 7.5mg/kg), after 1 month of induced-hypertension. SBP was monitored twice each month via tail cuff plethysmography. CBF was measured with MR by flow-sensitive alternating inversion recovery.

RESULTS

Chronic AngII-infusion induced an increase in SBP in both AβPP/PS1 and WT mice accompanied by a decrease in hippocampal and thalamic CBF only in the AβPP/PS1 mice. An additional difference between the AβPP/PS1 mice and WT mice was that SBP was much higher in AβPP/PS1 mice in both hypertensive and normotensive conditions. Moreover, both antihypertensives were less effective in reducing AngII-induced hypertension to normal levels in AβPP/PS1 mice, while being effective in WT mice.

CONCLUSIONS

It can be concluded that AngII-induced elevated SBP results in impaired CBF and a decreased response to blood pressure lowering treatment in a transgenic model of AD. Our findings suggest a relation between midlife hypertension and decreased CBF in an AD mouse model, similar to the relation which has been found in AD patients. This translational mouse model could be used to investigate possible prevention and treatment strategies for AD.

Structural-functional connectivity deficits of neocortical circuits in the Fmr1 (-/y) mouse model of autism

Fragile X syndrome (FXS), the most common inherited form of intellectual disability disorder and a frequent cause of autism spectrum disorder (ASD), is characterized by a high prevalence of sensory symptoms. Perturbations in the anatomical connectivity of neocortical circuits resulting in their functional defects have been hypothesized to contribute to the underlying etiology of these disorders. We tested this idea by probing alterations in the functional and structural connectivity of both local and long-ranging neocortical circuits in the Fmr1 (-/y) mouse model of FXS. To achieve this, we combined in vivo ultrahigh-field diffusion tensor magnetic resonance imaging (MRI), functional MRI, and viral tracing approaches in adult mice. Our results show an anatomical hyperconnectivity phenotype for the primary visual cortex (V1), but a disproportional low connectivity of V1 with other neocortical regions. These structural data are supported by defects in the structural integrity of the subcortical white matter in the anterior and posterior forebrain. These anatomical alterations might contribute to the observed functional decoupling across neocortical regions. We therefore identify FXS as a "connectopathy," providing a translational model for understanding sensory processing defects and functional decoupling of neocortical areas in FXS and ASD.

Improved spatial learning strategy and memory in aged Alzheimer AβPPswe/PS1dE9 mice on a multi-nutrient diet

There is accumulating evidence showing that lifestyle factors like diet may influence the onset and progression of Alzheimer's disease (AD). Our previous studies suggest that a multi-nutrient diet, Fortasyn, containing nutritional precursors and cofactors for membrane synthesis, viz. docosahexaenoic acid, eicosapentaenoic acid, uridine-mono-phosphate, choline, phospholipids, folic acid, vitamins B6, B12, C, E, and selenium, has an ameliorating effect on cognitive deficits in an AD mouse model. In the present study we analyzed learning strategies and memory of 11-month-old AβPPswe/PS1dE9 (AβPP/PS1) mice in the Morris water maze (MWM) task performed after nine months of dietary intervention with a control diet or a Fortasyn diet to characterize diet-induced changes in cognitive performance. The Fortasyn diet had no significant effect on MWM task acquisition. To assess hippocampus-dependent learning, the strategies that the mice used to find the hidden platform in the MWM were analyzed using the swim path data. During the fourth day of the MWM, AβPP/PS1 mice on control diet more often used the non-spatial random search strategy, while on the Fortasyn diet, the transgenic animals exhibited more chaining strategy than their wild-type littermates. During the probe trial, AβPP/PS1 mice displayed no clear preference for the target quadrant. Notably, in both transgenic and nontransgenic mice on Fortasyn diet, the latency to reach the former platform position was decreased compared to mice on the control diet. In conclusion, this specific nutrient combination showed a tendency to improve searching behavior in AβPP/PS1 mice by increasing the use of a more efficient search strategy and improving their swim efficiency by decreasing the latency to reach the former platform position.

Alzheimer's disease: pathophysiology and applications of magnetic nanoparticles as MRI theranostic agents

Alzheimer's disease (AD) is the most common form of dementia. During the recent decade, nanotechnology has been widely considered, as a promising tool, for theranosis (diagnosis and therapy) of AD. Here we first discuss pathophysiology and characteristics of AD with a focus on the amyloid cascade hypothesis. Then magnetic nanoparticles (MNPs) and recent works on their applications in AD, focusing on the superparamagnetic iron oxide nanoparticles (SPIONs), are reviewed. Furthermore, the amyloid-nanoparticle interaction is highlighted, with the scope to be highly considered by the scientists aiming for diagnostics and/or treatment of AD employing nanoparticles. Furthermore, recent findings on the "ignored" parameters (e.g., effect of protein "corona" at the surface of nanoparticles on amyloid-β (Aβ) fibrillation process) are discussed.

Multinutrient diets improve cerebral perfusion and neuroprotection in a murine model of Alzheimer's disease

Nutritional intervention may retard the development of Alzheimer's disease (AD). In this study we tested the effects of 2 multi-nutrient diets in an AD mouse model (APPswe/PS1dE9). One diet contained membrane precursors such as omega-3 fatty acids and uridine monophosphate (DEU), whereas another diet contained cofactors for membrane synthesis as well (Fortasyn); the diets were developed to enhance synaptic membranes synthesis, and contain components that may improve vascular health. We measured cerebral blood flow (CBF) and water diffusivity with ultra-high-field magnetic resonance imaging, as alterations in these parameters correlate with clinical symptoms of the disease. APPswe/PS1dE9 mice on control diet showed decreased CBF and changes in brain water diffusion, in accordance with findings of hypoperfusion, axonal disconnection and neuronal loss in patients with AD. Both multinutrient diets were able to increase cortical CBF in APPswe/PS1dE9 mice and Fortasyn reduced water diffusivity, particularly in the dentate gyrus and in cortical regions. We suggest that a specific diet intervention has the potential to slow AD progression, by simultaneously improving cerebrovascular health and enhancing neuroprotective mechanisms.

Effects of specific multi-nutrient enriched diets on cerebral metabolism, cognition and neuropathology in AβPPswe-PS1dE9 mice

Recent studies have focused on the use of multi-nutrient dietary interventions in search of alternatives for the treatment and prevention of Alzheimer's disease (AD). In this study we investigated to which extent long-term consumption of two specific multi-nutrient diets can modulate AD-related etiopathogenic mechanisms and behavior in 11-12-month-old AβPPswe-PS1dE9 mice. Starting from 2 months of age, male AβPP-PS1 mice and wild-type littermates were fed either a control diet, the DHA+EPA+UMP (DEU) diet enriched with uridine monophosphate (UMP) and the omega-3 fatty acids docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), or the Fortasyn® Connect (FC) diet enriched with the DEU diet plus phospholipids, choline, folic acid, vitamins and antioxidants. We performed behavioral testing, proton magnetic resonance spectroscopy, immunohistochemistry, biochemical analyses and quantitative real-time PCR to gain a better understanding of the potential mechanisms by which these multi-nutrient diets exert protective properties against AD. Our results show that both diets were equally effective in changing brain fatty acid and cholesterol profiles. However, the diets differentially affected AD-related pathologies and behavioral measures, suggesting that the effectiveness of specific nutrients may depend on the dietary context in which they are provided. The FC diet was more effective than the DEU diet in counteracting neurodegenerative aspects of AD and enhancing processes involved in neuronal maintenance and repair. Both diets elevated interleukin-1β mRNA levels in AβPP-PS1 and wild-type mice. The FC diet additionally restored neurogenesis in AβPP-PS1 mice, decreased hippocampal levels of unbound choline-containing compounds in wild-type and AβPP-PS1 animals, suggesting diminished membrane turnover, and decreased anxiety-related behavior in the open field behavior. In conclusion, the current data indicate that specific multi-nutrient diets can influence AD-related etiopathogenic processes. Intervention with the FC diet might be of interest for several other neurodegenerative and neurological disorders.

Impact of a multi-nutrient diet on cognition, brain metabolism, hemodynamics, and plasticity in apoE4 carrier and apoE knockout mice

Lipid metabolism and genetic background together strongly influence the development of both cardiovascular and neurodegenerative diseases like Alzheimer's disease (AD). A non-pharmacological way to prevent the genotype-induced occurrence of these pathologies is given by dietary behavior. In the present study, we tested the effects of long-term consumption of a specific multi-nutrient diet in two models for atherosclerosis and vascular risk factors in AD: the apolipoprotein ε4 (apoE4) and the apoE knockout (apoE ko) mice. This specific multi-nutrient diet was developed to support neuronal membrane synthesis and was expected to contribute to the maintenance of vascular health. At 12 months of age, both genotypes showed behavioral changes compared to control mice and we found increased neurogenesis in apoE ko mice. The specific multi-nutrient diet decreased anxiety-related behavior in the open field, influenced sterol composition in serum and brain tissue, and increased the concentration of omega-3 fatty acids in the brain. Furthermore, we found that wild-type and apoE ko mice fed with this multi-nutrient diet showed locally increased cerebral blood volume and decreased hippocampal glutamate levels. Taken together, these data suggest that a specific dietary intervention has beneficial effects on early pathological consequences of hypercholesterolemia and vascular risk factors for AD.

A longitudinal study of cognition, proton MR spectroscopy and synaptic and neuronal pathology in aging wild-type and AβPPswe-PS1dE9 mice

Proton magnetic resonance spectroscopy (¹H MRS) is a valuable tool in Alzheimer’s disease research, investigating the functional integrity of the brain. The present longitudinal study set out to characterize the neurochemical profile of the hippocampus, measured by single voxel ¹H MRS at 7 Tesla, in the brains of AβPPSswe-PS1dE9 and wild-type mice at 8 and 12 months of age. Furthermore, we wanted to determine whether alterations in hippocampal metabolite levels coincided with behavioral changes, cognitive decline and neuropathological features, to gain a better understanding of the underlying neurodegenerative processes. Moreover, correlation analyses were performed in the 12-month-old AβPP-PS1 animals with the hippocampal amyloid-β deposition, TBS-T soluble Aβ levels and high-molecular weight Aβ aggregate levels to gain a better understanding of the possible involvement of Aβ in neurochemical and behavioral changes, cognitive decline and neuropathological features in AβPP-PS1 transgenic mice. Our results show that at 8 months of age AβPPswe-PS1dE9 mice display behavioral and cognitive changes compared to age-matched wild-type mice, as determined in the open field and the (reverse) Morris water maze. However, there were no variations in hippocampal metabolite levels at this age. AβPP-PS1 mice at 12 months of age display more severe behavioral and cognitive impairment, which coincided with alterations in hippocampal metabolite levels that suggest reduced neuronal integrity. Furthermore, correlation analyses suggest a possible role of Aβ in inflammatory processes, synaptic dysfunction and impaired neurogenesis.

Monitoring the effects of bevacizumab beyond progression in a murine colorectal cancer model: a functional imaging approach

Clinical studies have shown that bevacizumab beyond progression to first line therapy is beneficial for overall survival in advanced stage colorectal cancer. We studied the utility of several functional imaging modalities to assess the efficacy of bevacizumab beyond progression (BBP). All BALB/c mice with s.c. LS174T xenografts were treated with capecitabine, oxaliplatin and bevacizumab combination therapy. Tumor volume was assessed using caliper measurements. Increase of 1.5 times the initial volume on two subsequent measurements, was considered progression. In half of the mice bevacizumab treatment was continued (n = 13) after progressive disease was established, while the others received saline injections (n = 12). Within 3 days after progression, multi-modal imaging was performed using FDG-PET, diffusion weighted imaging, T2* and dynamic contrast enhanced MRI. Measurements were repeated 7 and 10 days after the first measurements. Afterwards, tumors were analyzed for expression of carbonic anhydrase IX, glucose transporter 1, 9 F1 to stain the vasculature and Ki67 to assess proliferation. In the BBP group tumor growth after progression was reduced compared to the control group (p < 0.01). FDG-PET showed a trend towards lower FDG uptake in the BBP group (p = 0.08). DWI, T2* and DCE-MRI parameters were not significantly different between both groups. The immunohistochemical analyses showed higher CAIX-positive fraction (p < 0.01) and lower Ki67 expression (p = 0.06) in the BBP group. The relative vascular area was significantly lower in the BBP group (p = 0.03). GLUT-1 expression and vascular density did not significantly differ between both groups. Bevacizumab after progression resulted in significant changes in the tumor proliferation and microenvironment compared to discontinuation of bevacizumab. FDG-PET may be sensitive to BBP-induced effects.

Layer-specific diffusion weighted imaging in human primary visual cortex in vitro

One of the most prominent characteristics of the human neocortex is its laminated structure. The first person to observe this was Francesco Gennari in the second half the 18th century: in the middle of the depth of primary visual cortex, myelinated fibres are so abundant that he could observe them with bare eyes as a white line. Because of its saliency, the stria of Gennari has a rich history in cyto- and myeloarchitectural research as well as in magnetic resonance (MR) microscopy. In the present paper we show for the first time the layered structure of the human neocortex with ex vivo diffusion weighted imaging (DWI). To achieve the necessary spatial and angular resolution, primary visual cortex samples were scanned on an 11.7 T small-animal MR system to characterize the diffusion properties of the cortical laminae and the stria of Gennari in particular. The results demonstrated that fractional anisotropy varied over cortical depth, showing reduced anisotropy in the stria of Gennari, the inner band of Baillarger and the deepest layer of the cortex. Orientation density functions showed multiple components in the stria of Gennari and deeper layers of the cortex. Potential applications of layer-specific diffusion imaging include characterization of clinical abnormalities, cortical mapping and (intra)cortical tractography. We conclude that future high-resolution in vivo cortical DWI investigations should take into account the layer-specificity of the diffusion properties.