Memantine treatment does not affect compulsive behavior or frontostriatal connectivity in an adolescent rat model for quinpirole-induced compulsive checking behavior

RATIONALE: Compulsivity often develops during childhood and is associated with elevated glutamate levels within the frontostriatal system. This suggests that anti-glutamatergic drugs, like memantine, may be an effective treatment. OBJECTIVE: Our goal was to characterize the acute and chronic effect of memantine treatment on compulsive behavior and frontostriatal network structure and function in an adolescent rat model of compulsivity. METHODS: Juvenile Sprague-Dawley rats received repeated quinpirole, resulting in compulsive checking behavior (n = 32; compulsive) or saline injections (n = 32; control). Eight compulsive and control rats received chronic memantine treatment, and eight compulsive and control rats received saline treatment for seven consecutive days between the 10th and 12th quinpirole/saline injection. Compulsive checking behavior was assessed, and structural and functional brain connectivity was measured with diffusion MRI and resting-state fMRI before and after treatment. The other rats received an acute single memantine (compulsive: n = 12; control: n = 12) or saline injection (compulsive: n = 4; control: n = 4) during pharmacological MRI after the 12th quinpirole/saline injection. An additional group of rats received a single memantine injection after a single quinpirole injection (n = 8). RESULTS: Memantine treatment did not affect compulsive checking nor frontostriatal structural and functional connectivity in the quinpirole-induced adolescent rat model. While memantine activated the frontal cortex in control rats, no significant activation responses were measured after single or repeated quinpirole injections. CONCLUSIONS: The lack of a memantine treatment effect in quinpirole-induced compulsive adolescent rats may be partly explained by the interaction between glutamatergic and dopaminergic receptors in the brain, which can be evaluated with functional MRI

Connecting the dots: Structural and functional connections in healthy and diseased brain

Our brain consists of billions of neurons, and even many more connections between those neurons. These connections are essential for all our daily life functions. One can view these connections in two ways: from a structural and functional perspective. Structural connections are the physical connections between (groups of) neurons, and comparable to train tracts in a train network. Functional connectivity informs on the transfer of signals between (groups of) neurons, similar to the passage of trains over train tracts. In this thesis, we captured structural and functional connections, and their mutual relationship, in the healthy human and rat brain using MRI. In addition, we investigated these connections and their relationships under specific disease conditions, like obsessive-compulsive disorder (OCD) and stroke. From our studies, we obtained new information about the complex organization of structural and functional connections in the brain, which differs between brain regions. In addition, we found that structural and functional connections in the rat brain show specific changes over the lifespan. These changes may explain why specific disorders develop during certain life periods. We identified altered maturation of structural connections in adolescent rats with OCD. Besides, we showed that the organization of structural and functional networks in older rat brains affects the impact of a stroke. This thesis, therefore, provides new insights into the arrangement of structural and functional brain connections and how changes in these connections from young to old age may contribute to disease development

PR034

MRI data of participant PR03

Pregnancy-associated changes in resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture

Raw MRI data, correlation variables and demographic/group information related to the paper ' ‘Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture’ published in Nature Communications. Only data of the participants who have provided permission to share their data are provided

PR075

MRI data of participant PR07

A systematic review on the quantitative relationship between structural and functional network connectivity strength in mammalian brains

The mammalian brain is composed of densely connected and interacting regions, which form structural and functional networks. An improved understanding of the structure-function relation is crucial to understand the structural underpinnings of brain function and brain plasticity after injury. It is currently unclear how functional connectivity strength relates to structural connectivity strength. We obtained an overview of recent papers that report on correspondences between quantitative functional and structural connectivity measures in the mammalian brain. We included network studies in which functional connectivity was measured with resting-state fMRI, and structural connectivity with either diffusion-weighted MRI or neuronal tract tracers. Twenty-seven of the 28 included studies showed a positive structure-function relationship. Large inter-study variations were found comparing functional connectivity strength with either quantitative diffusion-based (correlation coefficient (r) ranges: 0.18-0.82) or neuronal tracer-based structural connectivity measures (r = 0.24-0.74). Two functional datasets demonstrated lower structure-function correlations with neuronal tracer-based (r = 0.22 and r = 0.30) than with diffusion-based measures (r = 0.49 and r = 0.65). The robust positive quantitative structure-function relationship supports the hypothesis that structural connectivity provides the hardware from which functional connectivity emerges. However, methodological differences between the included studies complicate the comparison across studies, which emphasize the need for validation and standardization in brain structure-function studies

Deuterium Metabolic Imaging of the Healthy and Diseased Brain

Altered brain metabolism contributes to pathophysiology in cerebrovascular and neurodegenerative diseases such as stroke and Alzheimer's disease. Current clinical tools to study brain metabolism rely on positron emission tomography (PET) requiring specific hardware and radiotracers, or magnetic resonance spectroscopy (MRS) involving technical complexity. In this review we highlight deuterium metabolic imaging (DMI) as a novel translational technique for assessment of brain metabolism, with examples from brain tumor and stroke studies. DMI is an MRS-based method that enables detection of deuterated substrates, such as glucose, and their metabolic products, such as lactate, glutamate and glutamine. It provides additional detail of downstream metabolites compared to analogous approaches like fluorodeoxyglucose (FDG)-PET, and can be implemented and executed on clinical and preclinical MR systems. We foresee that DMI, with future improvements in spatial and temporal resolutions, holds promise to become a valuable MR imaging (MRI) method for non-invasive mapping of glucose uptake and its downstream metabolites in healthy and diseased brain

Differences in structural and functional networks between young adult and aged rat brains before and after stroke lesion simulations

Neural network changes during aging may contribute to vulnerability and resilience to brain lesions in age-related neurological disorders, such as stroke. However, the relationship between age-related neural network features and stroke outcome is unknown. Therefore, we assessed structural and functional network status in young adult and aged rat brain, and measured the effects of simulated stroke lesions. Eleven rats underwent diffusion-weighted MRI and resting-state functional MRI at young adult age (post-natal day 88) and old age (between post-natal day 760 and 880). Structural and functional brain network features were calculated from graph-based network analysis. We performed three lesion simulations based on the brain injury pattern in frequently applied rodent stroke models, i.e. a small cortical lesion, a subcortical lesion, or a large cortical plus subcortical lesion, for which we computationally removed the involved network regions. Global network characteristics, i.e. integration and segregation, were not significantly different between the two age groups. However, we detected local differences in structural and functional networks between young adult and old rats, mainly reflected by shifts of hub regions. Stroke lesion simulations induced significant global and local network changes, characterized by lower efficiency and shifts of hub regions in structural and functional networks, which was most evident after a large cortical plus subcortical lesion. Functional and structural hub region shifts after lesion simulations differed between young adult and aged rats. Our lesion simulation study demonstrates that age-dependent brain network status affects structural and functional network reorganization after stroke, particularly involving hub shifts, which may influence functional outcome. Computational lesion studies offer a cheap and simple alternative to empirical studies and can complement or guide more complicated experimental studies in animal models and patients

Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture

While animal studies have demonstrated a unique reproduction-related neuroplasticity, little is known on the effects of pregnancy on the human brain. Here we investigated whether pregnancy is associated with changes to resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture using a comprehensive pre-conception cohort study. We show that pregnancy leads to selective and robust changes in neural architecture and neural network organization, which are most pronounced in the Default Mode Network. These neural changes correlated with pregnancy hormones, primarily third-trimester estradiol, while no associations were found with other factors such as osmotic effects, stress and sleep. Furthermore, the changes related to measures of maternal-fetal bonding, nesting behavior and the physiological responsiveness to infant cues, and predicted measures of mother-infant bonding and bonding impairments. These findings suggest there are selective pregnancy-related modifications in brain structure and function that may facilitate peripartum maternal processes of key relevance to the mother-infant dyad