Electrical, molecular and behavioral effects of interictal spiking in the rat.

OBJECTIVE: Epilepsy is a disease characterized by chronic seizures, but is associated with significant comorbidities between seizures including cognitive impairments, hyperactivity, and depression. To study this interictal state, we characterized the electrical, molecular, and behavior effects of chronic, neocortical interictal spiking in rats. METHODS: A single injection of tetanus toxin into somatosensory cortex generated chronic interictal spiking measured by long-term video EEG monitoring and was correlated with motor activity. The cortical pattern of biomarker activation and the effects of blocking MAPK signaling on interictal spiking and behavior were determined. RESULTS: Interictal spiking in this model increases in frequency, size, and becomes repetitive over time, but is rarely associated with seizures. Interictal spiking was sufficient to produce the same molecular and cellular pattern of layer 2/3-specific CREB activation and plasticity gene induction as is seen in the human interictal state. Increasing spike frequency was associated with hyperactivity, demonstrated by increased ambulatory activity and preferential circling toward the spiking hemisphere. Loud noises induced epileptic discharges, identical to spontaneous discharges. Treatment with a selective MAPK inhibitor prevented layer 2/3 CREB activation, reduced the frequency of epileptic discharges, and normalized behavioral abnormalities, but had no effect on seizures induced by electrical kindling. INTERPRETATION: These results provide insights into the development of interictal epileptic spiking, their relationship to behavior, and suggest that interictal and ictal activities utilize distinct molecular pathways. This model, that parallels recent observations in humans, will be useful to develop therapeutics against interictal spiking and its behavioral comorbidities.

Colon segmentation for prepless virtual colonoscopy.

A novel segmentation framework for a prepless virtual colonoscopy (VC) is presented, which reduces the necessity for colon cleansing before the CT scan. The patient is injected rectally with a water-soluble iodinated contrast medium using manual insufflators and a small rectal catheter. Compared to the air-based contrast medium, this technique can better preserve the color lumen and reduce the partial volume effect. However, the contrast medium, together with the fecal materials and air, makes colon wall segmentation challenging. Our solution makes no assumptions about the shape, size, and location of the fecal material in the colon. This generality allows us to label the fecal material accurately and extract the colon wall reliably. The accuracy of our technique has been verified on 60 human subjects. Compared with current VC technologies, our method is shown to be better in terms of both sensitivity and specificity. Further, in our experiments, the accuracy of the technique was comparable to that of optical colonoscopy results.

Evaluation of fiber bundles across subjects through brain mapping and registration of diffusion tensor data.

This paper presents a visualization and analysis framework for evaluating changes in structural organization of fiber bundles in human brain white matter. Statistical analysis of fiber bundle organization is conducted using an anisotropy measure, volume ratio (VR), which is ratio of anisotropic and isotropic components. Initially fiber bundles are tracked using a probabilistic algorithm starting from seed voxels. To ensure accurate selection of seed voxels and to prevent operator bias, a reference brain (MNI_152) is used when marking ROIs. Individual structural MRI brain scans are mapped to the reference using volumetric conformal parameterization. This mapping preserves topology and aligns features perfectly making it a robust and accurate registration technique. One-to-one mapping to the template allows ROI selection and subsequent transfer of ROI to structural MRI of subject. Affine registration coregisters structural MRI and DTI. Seed voxels are mapped to DTI using the resulting transformation parameters. To evaluate the proposed approach, MRI and DTI of 12 normal volunteers and 15 medial temporal lobe epilepsy patients are used. First, a statistical hypothesis testing is conducted to test for anisotropy changes in cingulum and fornix fiber bundles of epileptic patients. Experimental results reveal a 40% decrease in anisotropy levels of cingulum in patients compared to volunteers. They also show a 25% overall decrease in anisotropy of fornix. Secondly, shapes of the bundles are visualized in 3D illustrating that the bundles of epileptic patients are bumpy while those of normal volunteers are smooth.

Intra-patient supine-prone colon registration in CT colonography using shape spectrum.

CT colonography (CTC) is a minimally invasive screening technique for colorectal polyps and colon cancer. Since electronic colon cleansing (ECC) cannot completely remove the presence of pseudo-polyps, most CTC protocols acquire both prone and supine images to improve the visualization of the lumen wall and to reduce false positives. Comparisons between the prone and supine images can be facilitated by computerized registration between the scans. In this paper, we develop a fully automatic method for registering colon surfaces extracted from prone and supine images. The algorithm uses shape spectrum to extract the shape characteristics which are employed as the surface signature to find the correspondent regions between the prone and supine lumen surfaces. Our experimental results demonstrate an accuracy of 12.6 +/- 4.20 mm over 20 datasets. It also shows excellent potential in reducing the false positive when it is used to determine polyps through correspondences between prone and supine images.

Coclustering for cross-subject fiber tract analysis through diffusion tensor imaging.

One of the fundamental goals of computational neuroscience is the study of anatomical features that reflect the functional organization of the brain. The study of physical associations between neuronal structures and the examination of brain activity in vivo have given rise to the concept of anatomical and functional connectivity, which has been invaluable for our understanding of brain mechanisms and their plasticity during development. However, at present, there is no robust and accurate computational framework for the quantitative assessment of cortical connectivity patterns. In this paper, we present a quantitative analysis and modeling tool that is able to characterize anatomical connectivity patterns based on a newly developed coclustering algorithm, termed the business model-based coclustering algorithm (BCA). We apply BCA to diffusion tensor imaging (DTI) data in order to provide an automated and reproducible assessment of the connectivity patterns between different cortical areas in human brains. BCA not only partitions the cortical mantel into well-defined clusters, but also maximizes the connectivity strength between these clusters. Moreover, BCA is computationally robust and allows both outlier detection as well as parameter-independent determination of the number of clusters. Our coclustering results have showed good performance of BCA in identifying major white matter fiber bundles in human brains and facilitate the detection of abnormal connectivity patterns in patients suffering from various neurological diseases.

Abnormal fronto-striatal connectivity in children with histories of early deprivation: A diffusion tensor imaging study.

An Inattentive/Overactive (I/O) behavioral phenotype has been reported in a significant percentage of children raised from birth in orphanages. While a number of studies have identified both functional and structural brain abnormalities in children raised from birth in orphanages, no published studies have evaluated potential neural correlates of the I/O phenotype. We applied diffusion tensor imaging (DTI) to 15 pre-teen children raised in orphanages in Eastern Europe or Asia and later adopted to the US. Fiber tracts were constructed from DTI data using probabilistic fiber tracking and the cortical fiber distribution of fibers originating from the head of the caudate was compared between the early deprivation (ED) group and 12 age-matched controls. The ED group showed a more diffuse connectivity pattern, especially in the right hemisphere, potentially related to incomplete neuronal pruning during development. These structural abnormalities may be associated with inattention and overactivity encountered in children with ED.