Chronic methamphetamine effects on brain structure and function in rats

Methamphetamine (MA) addiction is a growing epidemic worldwide. Chronic MA use has been shown to lead to neurotoxicity in rodents and humans. Magnetic resonance imaging (MRI) studies in MA users have shown enlarged striatal volumes and positron emission tomography (PET) studies have shown decreased brain glucose metabolism (BGluM) in the striatum of detoxified MA users. The present study examines structural changes of the brain, observes microglial activation, and assesses changes in brain function, in response to chronic MA treatment. Rats were randomly split into three distinct treatment groups and treated daily for four months, via i.p. injection, with saline (controls), or low dose (LD) MA (4 mg/kg), or high dose (HD) MA (8 mg/kg). Sixteen weeks into the treatment period, rats were injected with a glucose analog, [18F] fluorodeoxyglucose (FDG), and their brains were scanned with micro-PET to assess regional BGluM. At the end of MA treatment, magnetic resonance imaging at 21T was performed on perfused rats to determine regional brain volume and in vitro [3H]PK 11195 autoradiography was performed on fresh-frozen brain tissue to measure microglia activation. When compared with controls, chronic HD MA-treated rats had enlarged striatal volumes and increases in [3H]PK 11195 binding in striatum, the nucleus accumbens, frontal cortical areas, the rhinal cortices, and the cerebellar nuclei. FDG microPET imaging showed that LD MA-treated rats had higher BGluM in insular and somatosensory cortices, face sensory nucleus of the thalamus, and brainstem reticular formation, while HD MA-treated rats had higher BGluM in primary and higher order somatosensory and the retrosplenial cortices, compared with controls. HD and LD MA-treated rats had lower BGluM in the tail of the striatum, rhinal cortex, and subiculum and HD MA also had lower BGluM in hippocampus than controls. These results corroborate clinical findings and help further examine the mechanisms behind MA-induced neurotoxicity

Segmentation of rodent brains from mri based on a novel statistical structure prediction method

Functional segmentation of brain images is important in understating the relationships between anatomy and mental diseases in brains. Volumetric analysis of various brain structures such as the cerebellum plays a critical role in studying the structural changes in brain regions as a function of development, trauma, or neurodegeneratioin. Although various segmentation methods in clinical studies have been proposed, most of them require a priori knowledge about the locations of the structures of interest, preventing the fully automatic segmentation. In this paper, we present a novel method for detecting and locating the brain structures of interest that can be used for the fully automatic functional segmentation of 2D rodent brain MR images. The presented method focuses on detecting the topological changes of brain structures based on a novel area ratio criteria. The mean successful rate of the detection method shows 89.4 % accuracy compared to the expert-identified ground truth. Index Terms — Biomedical image processing, Image segmentation, Learning systems, Robust active shape mode

3d segmentation of rodent brain structures using hierarchical shape priors and deformable models

Object boundary extraction is an important task in brain image analysis. Acquiring detailed 3D representations of the brain structures could improve the detection rate of diseases at earlier stages. Deformable model based segmentation methods have been widely used with considerable success. Recently, 3D Active Volume Model (AVM) was proposed, which incorporates both gradient and region information for robustness. However, the segmentation performance of this model depends on the position, size and shape of the initialization, especially for data with complex texture. Furthermore, there is no shape prior information integrated. In this paper, we present an approach combining AVM and Active Shape Model (ASM). Our method uses shape information from training data to constrain the deformation of AVM. Experiments have been made on the segmentation of complex structures of the rodent brain from MR images, and the proposed method performed better than the original AVM

3d segmentation of rodent brain structures using hierarchical shape priors and deformable models

ABSTRACT Object boundary extraction is an important task in brain image analysis. Acquiring detailed 3D representations of the brain structures could improve the detection rate of diseases at earlier stages. Deformable model based segmentation methods have been widely used with considerable success. Recently, 3D Active Volume Model (AVM) was proposed, which incorporates both gradient and region information for robustness. However, the segmentation performance of this model depends on the position, size and shape of the initialization, especially for data with complex texture. Furthermore, there is no shape prior information integrated. In this paper, we present an approach combining AVM and Active Shape Model (ASM). Our method uses shape information from training data to constrain the deformation of AVM. Experiments have been made on the segmentation of complex structures of the rodent brain from MR images, and the proposed method performed better than the original AVM

Dopamine D4 receptors modulate brain metabolic activity in the prefrontal cortex and cerebellum at rest and in response to methylphenidate

Methylphenidate (MP) is widely used to treat attention deficit hyperactivity disorder (ADHD). Variable number of tandem repeats polymorphisms in the dopamine D4 receptor (D(4)) gene have been implicated in vulnerability to ADHD and the response to MP. Here we examined the contribution of dopamine D4 receptors (D4Rs) to baseline brain glucose metabolism and to the regional metabolic responses to MP. We compared brain glucose metabolism (measured with micro-positron emission tomography and [(18)F]2-fluoro-2-deoxy-D-glucose) at baseline and after MP (10 mg/kg, i.p.) administration in mice with genetic deletion of the D(4). Images were analyzed using a novel automated image registration procedure. Baseline D(4)(-/-) mice had lower metabolism in the prefrontal cortex (PFC) and greater metabolism in the cerebellar vermis (CBV) than D(4)(+/+) and D(4)(+/-) mice; when given MP, D(4)(-/-) mice increased metabolism in the PFC and decreased it in the CBV, whereas in D(4)(+/+) and D(4)(+/-) mice, MP decreased metabolism in the PFC and increased it in the CBV. These findings provide evidence that D4Rs modulate not only the PFC, which may reflect the activation by dopamine of D4Rs located in this region, but also the CBV, which may reflect an indirect modulation as D4Rs are minimally expressed in this region. As individuals with ADHD show structural and/or functional abnormalities in these brain regions, the association of ADHD with D4Rs may reflect its modulation of these brain regions. The differential response to MP as a function of genotype could explain differences in brain functional responses to MP between patients with ADHD and healthy controls and between patients with ADHD with different D(4) polymorphisms.This work was supported by the NIAAA (AA 11 034, AA07574 andAA07611

Multi-level profiling of the Fmr1 KO rat unveils altered behavioral traits along with aberrant glutamatergic function

Abstract Fragile X syndrome (FXS) is the most common cause of inherited intellectual disabilities and the most prevalent monogenic cause of autism. Although the knockout (KO) of the Fmr1 gene homolog in mice is primarily used for elucidating the neurobiological substrate of FXS, there is limited association of the experimental data with the pathophysiological condition in humans. The use of Fmr1 KO rats offers additional translational validity in this regard. Therefore, we employed a multi-level approach to study the behavioral profile and the glutamatergic and GABAergic neurotransmission status in pathophysiology-associated brain structures of Fmr1 KO rats, including the recordings of evoked and spontaneous field potentials from hippocampal slices, paralleled with next-generation RNA sequencing (RNA-seq). We found that these rats exhibit hyperactivity and cognitive deficits, along with characteristic bidirectional glutamatergic and GABAergic alterations in the prefrontal cortex and the hippocampus. These results are coupled to affected excitability and local inhibitory processes in the hippocampus, along with a specific transcriptional profile, highlighting dysregulated hippocampal network activity in KO rats. Overall, our data provide novel insights concerning the biobehavioral profile of FmR1 KO rats and translationally upscales our understanding on pathophysiology and symptomatology of FXS syndrome