Apolipoprotein-E deficiency leads to brain network alteration characterized by diffusion MRI and graph theory.

Late-onset Alzheimer's disease (LOAD) is a major health concern for senior citizens, characterized by memory loss, confusion, and impaired cognitive abilities. Apolipoprotein-E (ApoE) is a well-known risk factor for LOAD, though exactly how ApoE affects LOAD risks is unknown. We hypothesize that ApoE attenuation of LOAD resiliency or vulnerability has a neurodevelopmental origin via changing brain network architecture. We investigated the brain network structure in adult ApoE knock out (ApoE KO) and wild-type (WT) mice with diffusion tensor imaging (DTI) followed by graph theory to delineate brain network topology. Left and right hemisphere connectivity revealed significant differences in number of connections between the hippocampus, amygdala, caudate putamen and other brain regions. Network topology based on the graph theory of ApoE KO demonstrated decreased functional integration, network efficiency, and network segregation between the hippocampus and amygdala and the rest of the brain, compared to those in WT counterparts. Our data show that brain network developed differently in ApoE KO and WT mice at 5 months of age, especially in the network reflected in the hippocampus, amygdala, and caudate putamen. This indicates that ApoE is involved in brain network development which might modulate LOAD risks via changing brain network structures.

Impaired functional connectivity of the hippocampus in translational murine models of NMDA-receptor antibody associated neuropsychiatric pathology.

Decreased hippocampal connectivity and disruption of functional networks are established resting-state functional MRI (rs-fMRI) features that are associated with neuropsychiatric symptom severity in human anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. However, the underlying pathophysiology of NMDAR encephalitis remains poorly understood. Application of patient-derived monoclonal antibodies against the NR1 (GluN1) subunit of the NMDAR now allows for the translational investigation of functional connectivity in experimental murine NMDAR antibody disease models with neurodevelopmental disorders. Using rs-fMRI, we studied functional connectivity alterations in (1) adult C57BL/6 J mice that were intrathecally injected with a recombinant human NR1 antibody over 14 days (n = 10) and in (2) a newly established mouse model with in utero exposure to a human recombinant NR1 antibody (NR1-offspring) at the age of (2a) 8 weeks (n = 15) and (2b) 10 months (n = 14). Adult NR1-antibody injected mice showed impaired functional connectivity within the left hippocampus compared to controls, resembling impaired connectivity patterns observed in human NMDAR encephalitis patients. Similarly, NR1-offspring showed significantly reduced functional connectivity in the hippocampus after 8 weeks, and impaired connectivity in the hippocampus was likewise observed in NR1-offspring at the age of 10 months. We successfully reproduced functional connectivity changes within the hippocampus in different experimental murine systems that were previously observed in human NMDAR encephalitis patients. Translational application of this method within a combined imaging and histopathological framework will allow future experimental studies to identify the underlying biological mechanisms and may eventually facilitate non-invasive monitoring of disease activity and treatment responses in autoimmune encephalitis.

Prediction of Stroke Outcome in Mice Based on Noninvasive MRI and Behavioral Testing.

BACKGROUND: Prediction of poststroke outcome using the degree of subacute deficit or magnetic resonance imaging is well studied in humans. While mice are the most commonly used animals in preclinical stroke research, systematic analysis of outcome predictors is lacking. METHODS: We intended to incorporate heterogeneity into our retrospective study to broaden the applicability of our findings and prediction tools. We therefore analyzed the effect of 30, 45, and 60 minutes of arterial occlusion on the variance of stroke volumes. Next, we built a heterogeneous cohort of 215 mice using data from 15 studies that included 45 minutes of middle cerebral artery occlusion and various genotypes. Motor function was measured using a modified protocol for the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were coregistered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. RESULTS: Variance of stroke volumes was increased by 45 minutes of arterial occlusion compared with 60 minutes. The inclusion of various genotypes enhanced heterogeneity further. We detected both a subacute and residual motor-functional deficit after stroke in mice and different recovery trajectories could be observed. In mice with small cortical lesions, lesion volume was the best predictor of the subacute deficit. The residual deficit could be predicted most accurately by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increased prediction accuracy. A subset of anatomic regions within the ischemic lesion had particular impact on the prediction of long-term outcomes. Prediction accuracy depended on the degree of functional impairment. CONCLUSIONS: For the first time, we developed and validated a robust tool for the prediction of functional outcomes after experimental stroke in mice using a large and genetically heterogeneous cohort. These results are discussed in light of study design and imaging limitations. In the future, using outcome prediction can improve the design of preclinical studies and guide intervention decisions.

Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images.

Magnetic resonance imaging (MRI) is widely used for ischemic stroke lesion detection in mice. A challenge is that lesion segmentation often relies on manual tracing by trained experts, which is labor-intensive, time-consuming, and prone to inter- and intra-rater variability. Here, we present a fully automated ischemic stroke lesion segmentation method for mouse T2-weighted MRI data. As an end-to-end deep learning approach, the automated lesion segmentation requires very little preprocessing and works directly on the raw MRI scans. We randomly split a large dataset of 382 MRI scans into a subset (n = 293) to train the automated lesion segmentation and a subset (n = 89) to evaluate its performance. We compared Dice coefficients and accuracy of lesion volume against manual segmentation, as well as its performance on an independent dataset from an open repository with different imaging characteristics. The automated lesion segmentation produced segmentation masks with a smooth, compact, and realistic appearance that are in high agreement with manual segmentation. We report dice scores higher than the agreement between two human raters reported in previous studies, highlighting the ability to remove individual human bias and standardize the process across research studies and centers.

Intersectin deficiency impairs cortico-striatal neurotransmission and causes obsessive-compulsive behaviors in mice.

The generation of appropriate behavioral responses involves dedicated neuronal circuits. The cortico-striatal-thalamo-cortical loop is especially important for the expression of motor routines and habits. Defects in this circuitry are closely linked to obsessive stereotypic behaviors, hallmarks of neuropsychiatric diseases including autism spectrum disorders (ASDs) and obsessive-compulsive disorders (OCDs). However, our knowledge of the essential synaptic machinery required to maintain balanced neurotransmission and plasticity within the cortico-striatal circuitry remains fragmentary. Mutations in the large synaptic scaffold protein intersectin1 (ITSN1) have been identified in patients presenting with ASD symptoms including stereotypic behaviors, although a causal relationship between stereotypic behavior and intersectin function has not been established. We report here that deletion of the two closely related proteins ITSN1 and ITSN2 leads to severe ASD/OCD-like behavioral alterations and defective cortico-striatal neurotransmission in knockout (KO) mice. Cortico-striatal function was compromised at multiple levels in ITSN1/2-depleted animals. Morphological analyses showed that the striatum of intersectin KO mice is decreased in size. Striatal neurons exhibit reduced complexity and an underdeveloped dendritic spine architecture. These morphological abnormalities correlate with defects in cortico-striatal neurotransmission and plasticity as well as reduced N-methyl-D-aspartate (NMDA) receptor currents as a consequence of postsynaptic NMDA receptor depletion. Our findings unravel a physiological role of intersectin in cortico-striatal neurotransmission to counteract ASD/OCD. Moreover, we delineate a molecular pathomechanism for the neuropsychiatric symptoms of patients carrying intersectin mutations that correlates with the observation that NMDA receptor dysfunction is a recurrent feature in the development of ASD/OCD-like symptoms.

Mechanical properties of murine hippocampal subregions investigated by atomic force microscopy and in vivo magnetic resonance elastography.

The hippocampus is a very heterogeneous brain structure with different mechanical properties reflecting its functional variety. In particular, adult neurogenesis in rodent hippocampus has been associated with specific viscoelastic properties in vivo and ex vivo. Here, we study the microscopic mechanical properties of hippocampal subregions using ex vivo atomic force microscopy (AFM) in correlation with the expression of GFP in presence of the nestin promoter, providing a marker of neurogenic activity. We further use magnetic resonance elastography (MRE) to investigate whether in vivo mechanical properties reveal similar spatial patterns, however, on a much coarser scale. AFM showed that tissue stiffness increases with increasing distance from the subgranular zone (p = 0.0069), and that stiffness is 39% lower in GFP than non-GFP regions (p = 0.0004). Consistently, MRE showed that dentate gyrus is, on average, softer than Ammon´s horn (shear wave speed = 3.2 ± 0.2 m/s versus 4.4 ± 0.3 m/s, p = 0.01) with another 3.4% decrease towards the subgranular zone (p = 0.0001). The marked reduction in stiffness measured by AFM in areas of high neurogenic activity is consistent with softer MRE values, indicating the sensitivity of macroscopic mechanical properties in vivo to micromechanical structures as formed by the neurogenic niche of the hippocampus.

Long-Term Connectome Analysis Reveals Reshaping of Visual, Spatial Networks in a Model With Vascular Dementia Features.

BACKGROUND: Connectome analysis of neuroimaging data is a rapidly expanding field that offers the potential to diagnose, characterize, and predict neurological disease. Animal models provide insight into biological mechanisms that underpin disease, but connectivity approaches are currently lagging in the rodent. METHODS: We present a pipeline adapted for structural and functional connectivity analysis of the mouse brain, and we tested it in a mouse model of vascular dementia. RESULTS: We observed lacunar infarctions, microbleeds, and progressive white matter change across 6 months. For the first time, we report that default mode network activity is disrupted in the mouse model. We also identified specific functional circuitry that was vulnerable to vascular stress, including perturbations in a sensorimotor, visual resting state network that were accompanied by deficits in visual and spatial memory tasks. CONCLUSIONS: These findings advance our understanding of the mouse connectome and provide insight into how it can be altered by vascular insufficiency.

Contribution of Tissue Inflammation and Blood-Brain Barrier Disruption to Brain Softening in a Mouse Model of Multiple Sclerosis.

Neuroinflammatory processes occurring during multiple sclerosis cause disseminated softening of brain tissue, as quantified by in vivo magnetic resonance elastography (MRE). However, inflammation-mediated tissue alterations underlying the mechanical integrity of the brain remain unclear. We previously showed that blood-brain barrier (BBB) disruption visualized by MRI using gadolinium-based contrast agent (GBCA) does not correlate with tissue softening in active experimental autoimmune encephalomyelitis (EAE). However, it is unknown how confined BBB changes and other inflammatory processes may determine local elasticity changes. Therefore, we aim to elucidate which inflammatory hallmarks are determinant for local viscoelastic changes observed in EAE brains. Hence, novel multifrequency MRE was applied in combination with GBCA-based MRI or very small superparamagnetic iron oxide particles (VSOPs) in female SJL mice with induced adoptive transfer EAE (n = 21). VSOPs were doped with europium (Eu-VSOPs) to facilitate the post-mortem analysis. Accumulation of Eu-VSOPs, which was previously demonstrated to be sensitive to immune cell infiltration and ECM remodeling, was also found to be independent of GBCA enhancement. Following registration to a reference brain atlas, viscoelastic properties of the whole brain and areas visualized by either Gd or VSOP were quantified. MRE revealed marked disseminated softening across the whole brain in mice with established EAE (baseline: 3.1 ± 0.1 m/s vs. EAE: 2.9 ± 0.2 m/s, p < 0.0001). A similar degree of softening was observed in sites of GBCA enhancement i.e., mainly within cerebral cortex and brain stem (baseline: 3.3 ± 0.4 m/s vs. EAE: 3.0 ± 0.5 m/s, p = 0.018). However, locations in which only Eu-VSOP accumulated, mainly in fiber tracts (baseline: 3.0 ± 0.4 m/s vs. EAE: 2.6 ± 0.5 m/s, p = 0.023), softening was more pronounced when compared to non-hypointense areas (percent change of stiffness for Eu-VSOP accumulation: -16.81 ± 16.49% vs. for non-hypointense regions: -5.85 ± 3.81%, p = 0.048). Our findings suggest that multifrequency MRE is sensitive to differentiate between local inflammatory processes with a strong immune cell infiltrate that lead to VSOP accumulation, from disseminated inflammation and BBB leakage visualized by GBCA. These pathological events visualized by Eu-VSOP MRI and MRE may include gliosis, macrophage infiltration, alterations of endothelial matrix components, and/or extracellular matrix remodeling. MRE may therefore represent a promising imaging tool for non-invasive clinical assessment of different pathological aspects of neuroinflammation.

The Effects of Selective Inhibition of Histone Deacetylase 1 and 3 in Huntington's Disease Mice.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease characterized by a late clinical onset of psychiatric, cognitive, and motor symptoms. Transcriptional dysregulation is an early and central disease mechanism which is accompanied by epigenetic alterations in HD. Previous studies demonstrated that targeting transcriptional changes by inhibition of histone deacetylases (HDACs), especially the class I HDACs, provides therapeutic effects. Yet, their exact mechanisms of action and the features of HD pathology, on which these inhibitors act remain to be elucidated. Here, using transcriptional profiling, we found that selective inhibition of HDAC1 and HDAC3 by RGFP109 alleviated transcriptional dysregulation of a number of genes, including the transcription factor genes Neurod2 and Nr4a2, and gene sets and programs, especially those that are associated to insulin-like growth factor pathway, in the striatum of R6/1 mice. RGFP109 treatment led to a modest improvement of the motor skill learning and coordination deficit on the RotaRod test, while it did not alter the locomotor and anxiety-like phenotypes in R6/1 animals. We also found, by volumetric MRI, a widespread brain atrophy in the R6/1 mice at the symptomatic disease stage, on which RGFP109 showed no significant effects. Collectively, our combined work suggests that specific HDAC1 and HDAC3 inhibition may offer benefits for alleviating the motor phenotypic deficits and transcriptional dysregulation in HD.

Seasonal plasticity in the adult somatosensory cortex.

Seasonal cycles govern life on earth, from setting the time for the mating season to influencing migrations and governing physiological conditions like hibernation. The effect of such changing conditions on behavior is well-appreciated, but their impact on the brain remains virtually unknown. We investigate long-term seasonal changes in the mammalian brain, known as Dehnel's effect, where animals exhibit plasticity in body and brain sizes to counter metabolic demands in winter. We find large seasonal variation in cellular architecture and neuronal activity in the smallest terrestrial mammal, the Etruscan shrew, Suncus etruscus Their brain, and specifically their neocortex, shrinks in winter. Shrews are tactile hunters, and information from whiskers first reaches the somatosensory cortex layer 4, which exhibits a reduced width (-28%) in winter. Layer 4 width (+29%) and neuron number (+42%) increase the following summer. Activity patterns in the somatosensory cortex show a prominent reduction of touch-suppressed neurons in layer 4 (-55%), the most metabolically active layer. Loss of inhibitory gating occurs with a reduction in parvalbumin-positive interneurons, one of the most active neuronal subtypes and the main regulators of inhibition in layer 4. Thus, a reduction in neurons in layer 4 and particularly parvalbumin-positive interneurons may incur direct metabolic benefits. However, changes in cortical balance can also affect the threshold for detecting sensory stimuli and impact prey choice, as observed in wild shrews. Thus, seasonal neural adaptation can offer synergistic metabolic and behavioral benefits to the organism and offer insights on how neural systems show adaptive plasticity in response to ecological demands.

A Semiquantitative Non-invasive Measurement of PcomA Patency in C57BL/6 Mice Explains Variance in Ischemic Brain Damage in Filament MCAo.

Numerous studies on experimental ischemic stroke use the filament middle cerebral artery occlusion (fMCAo) model in C57BL/6 mice, but lesion sizes in this strain are highly variable. A known contributor is variation in the posterior communicating artery (PcomA) patency. We therefore aimed to provide a semiquantitative non-invasive in vivo method to routinely assess PcomA patency. We included 43 male C57BL/6 mice from four independent studies using a transient 45 min fMCAo model. Edema-corrected lesion sizes were measured by magnetic resonance (MR) imaging 24 h after reperfusion. Time-of-flight MR angiography was performed 7 days before and 24 h after fMCAo. Scores of PcomA size measured 24 h after, but not scores measured 7 days before fMCAo were negatively correlated with lesion size. Variability in PcomA patency explained 30% of the variance in our cohort (p < 0.0001, coefficient of determination r 2 = 0.3). In a simulation using parameters typical for experimental stroke research, the power to detect a true effect of d = 1 between two groups increased by 15% when an according covariate was included in the statistical model. We have demonstrated that in vivo measurement of PcomA size is feasible and can lead to increased accuracy in assessing the effect of treatments.

The developmental origins of voice processing in the human brain.

In human adults, voices are processed in specialized brain regions in superior temporal cortices. We examined the development of this cortical organization during infancy by using near-infrared spectroscopy. In experiment 1, 7-month-olds but not 4-month-olds showed increased responses in left and right superior temporal cortex to the human voice when compared to nonvocal sounds, suggesting that voice-sensitive brain systems emerge between 4 and 7 months of age. In experiment 2, 7-month-old infants listened to words spoken with neutral, happy, or angry prosody. Hearing emotional prosody resulted in increased responses in a voice-sensitive region in the right hemisphere. Moreover, a region in right inferior frontal cortex taken to serve evaluative functions in the adult brain showed particular sensitivity to happy prosody. The pattern of findings suggests that temporal regions specialize in processing voices very early in development and that, already in infancy, emotions differentially modulate voice processing in the right hemisphere.