The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory.

Epilepsy, a neurological disorder characterized by recurrent seizures, is known to be associated with impaired sleep and memory. Although the specific mechanisms underlying these impairments are uncertain, the known role of sleep in memory consolidation suggests a potential relationship may exist between seizure activity, disrupted sleep, and memory impairment. A possible mediator in this relationship is the sleep spindle, the characteristic electroencephalographic (EEG) feature of non-rapid-eye-movement (NREM) sleep in humans and other mammals. Growing evidence supports the idea that sleep spindles, having thalamic origin, may mediate the process of long-term memory storage and plasticity by generating neuronal conditions that favor these processes. To study this potential relationship, a single model in which memory, sleep, and epilepsy can be simultaneously observed is of necessity. Rodent models of epilepsy appear to fulfill this requirement. Not only do rodents express both sleep spindles and seizure-induced sleep disruptions, but they also allow researchers to invasively study neurobiological processes both pre- and post- epileptic onset via the artificial induction of epilepsy (a practice that cannot be carried out in human subjects). However, the degree to which sleep architecture differs between rodents and humans makes direct comparisons between the two challenging. This review addresses these challenges and concludes that rodent sleep studies are useful in observing the functional roles of sleep and how they are affected by epilepsy.

Differentiation of High-Grade Glioma and Intracranial Metastasis Using Volumetric Diffusion Tensor Imaging Tractography.

OBJECTIVE: A reliable, noninvasive method to differentiate high-grade glioma (HGG) and intracranial metastasis (IM) has remained elusive. The aim of this study was to differentiate between HGG and IM using tumoral and peritumoral diffusion tensor imaging characteristics. METHODS: A semiautomated script generated volumetric regions of interest (ROIs) for the tumor and a peritumoral shell at a predetermined voxel thickness. ROI differences in diffusion tensor imaging-related metrics between HGG and IM groups were estimated, including fractional anisotropy, mean diffusivity, total fiber tract counts, and tract density. RESULTS: The HGG group (n = 46) had a significantly higher tumor-to-brain volume ratio than the IM group (n = 35) (P < 0.001). The HGG group exhibited significantly higher mean fractional anisotropy and significantly lower mean diffusivity within peritumoral ROI than the IM group (P < 0.05). The HGG group exhibited significantly higher total tract count and higher tract density in tumoral and peritumoral ROIs than the IM group (P < 0.05). Tumoral tract count and peritumoral tract density were the most optimal metrics to differentiate the groups based on receiver operating characteristic curve analysis. Predictive analysis using receiver operating characteristic curve thresholds was performed on 13 additional participants. Compared with correct clinical diagnoses, the 2 thresholds exhibited equal specificities (66.7%), but the tumoral tract count (85.7%) seemed more sensitive in differentiating the 2 groups. CONCLUSIONS: Tract count and tract density were significantly different in tumoral and peritumoral regions between HGG and IM. Differences in microenvironmental interactions between the tumor types may cause these tract differences.

High-grade Gliomas Exhibit Higher Peritumoral Fractional Anisotropy and Lower Mean Diffusivity than Intracranial Metastases.

Differentiating high-grade gliomas and intracranial metastases through non-invasive imaging has been challenging. Here, we retrospectively compared both intratumoral and peritumoral fractional anisotropy (FA), mean diffusivity (MD), and fluid-attenuated inversion recovery (FLAIR) measurements between high-grade gliomas and metastases. Two methods were utilized to select peritumoral region of interest (ROI). The first method utilized the manual placement of four ROIs adjacent to the lesion. The second method utilized a semiautomated and proprietary MATLAB script to generate an ROI encompassing the entire tumor. The average peritumoral FA, MD, and FLAIR values were determined within the ROIs for both methods. Forty patients with high-grade gliomas and 44 with metastases were enrolled in this study. Thirty-five patients with high-grade glioma and 30 patients with metastases had FLAIR images. There was no significant difference in age, gender, or race between the two patient groups. The high-grade gliomas had a significantly higher tumor-to-brain area ratio compared to the metastases. There were no differences in average intratumoral FA, MD, and FLAIR values between the two groups. Both the manual sample method and the semiautomated peritumoral ring method resulted in significantly higher peritumoral FA and significantly lower peritumoral MD in high-grade gliomas compared to metastases (p < 0.05). No significant difference was found in FLAIR values between the two groups peritumorally. Receiver operating curve analysis revealed FA to be a more sensitive and specific metric to differentiate high-grade gliomas and metastases than MD. The differences in the peritumoral FA and MD values between high-grade gliomas and metastases seemed due to the infiltration of glioma to the surrounding brain parenchyma.

MATSAP: An automated analysis of stretch-attend posture in rodent behavioral experiments.

Stretch-attend posture (SAP) occurs during risk assessment and is prevalent in common rodent behavioral tests. Measuring this behavior can enhance behavioral tests. For example, stretch-attend posture is a more sensitive measure of the effects of anxiolytics than traditional spatiotemporal indices. However, quantifying stretch-attend posture using human observers is time consuming, somewhat subjective, and prone to errors. We have developed MATLAB-based software, MATSAP, which is a quick, consistent, and open source program that provides objective automated analysis of stretch-attend posture in rodent behavioral experiments. Unlike human observers, MATSAP is not susceptible to fatigue or subjectivity. We assessed MATSAP performance with videos of male Swiss mice moving in an open field box and in an elevated plus maze. MATSAP reliably detected stretch-attend posture on par with human observers. This freely-available program can be broadly used by biologists and psychologists to accelerate neurological, pharmacological, and behavioral studies.

Gradient Index Microlens Implanted in Prefrontal Cortex of Mouse Does Not Affect Behavioral Test Performance over Time.

Implanted gradient index lenses have extended the reach of standard multiphoton microscopy from the upper layers of the mouse cortex to the lower cortical layers and even subcortical regions. These lenses have the clarity to visualize dynamic activities, such as calcium transients, with subcellular and millisecond resolution and the stability to facilitate repeated imaging over weeks and months. In addition, behavioral tests can be used to correlate performance with observed changes in network function and structure that occur over time. Yet, this raises the questions, does an implanted microlens have an effect on behavioral tests, and if so, what is the extent of the effect? To answer these questions, we compared the performance of three groups of mice in three common behavioral tests. A gradient index lens was implanted in the prefrontal cortex of experimental mice. We compared their performance with mice that had either a cranial window or a sham surgery. Three presurgical and five postsurgical sets of behavioral tests were performed over seven weeks. Behavioral tests included rotarod, foot fault, and Morris water maze. No significant differences were found between the three groups, suggesting that microlens implantation did not affect performance. The results for the current study clear the way for combining behavioral studies with gradient index lens imaging in the prefrontal cortex, and potentially other regions of the mouse brain, to study structural, functional, and behavioral relationships in the brain.