Pattern Of Brain Changes Research Articles

Computational analysis of cerebral cortex

Magnetic resonance imaging (MRI) has been used in many in vivo anatomical studies of the brain. Computational neuroanatomy is an expanding field of research, and a number of automated, unbiased, objective techniques have been developed to characterize structural changes in the brain using structural MRI without the need for time-consuming manual measurements. Voxel-based morphometry is one of the most widely used automated techniques to examine patterns of brain changes. Cortical thickness analysis is also becoming increasingly used as a tool for the study of cortical anatomy. Both techniques can be relatively easily used with freely available software packages. MRI data quality is important in order for the processed data to be accurate. In this review, we describe MRI data acquisition and preprocessing for morphometric analysis of the brain and present a brief summary of voxel-based morphometry and cortical thickness analysis.

Longitudinal pattern of regional brain volume change differentiates normal aging from MCI

Neuroimaging measures have potential as surrogate markers of disease through identification of consistent features that occur prior to clinical symptoms. Despite numerous investigations, especially in relation to the transition to clinical impairment, the regional pattern of brain changes in clinically normal older adults has not been established. We predict that the regions that show early pathologic changes in association with Alzheimer disease will show accelerated volume loss in mild cognitive impairment (MCI) compared to normal aging. Through the Baltimore Longitudinal Study of Aging, we prospectively evaluated 138 nondemented individuals (age 64-86 years) annually for up to 10 consecutive years. Eighteen participants were diagnosed with MCI over the course of the study. Mixed-effects regression was used to compare regional brain volume trajectories of clinically normal individuals to those with MCI based on a total of 1,017 observations. All investigated volumes declined with normal aging (p < 0.05). Accelerated change with age was observed for ventricular CSF (vCSF), frontal gray matter, superior, middle, and medial frontal, and superior parietal regions (p < or = 0.04). The MCI group showed accelerated changes compared to normal controls in whole brain volume, vCSF, temporal gray matter, and orbitofrontal and temporal association cortices, including the hippocampus (p < or = 0.04). Although age-related regional volume loss is apparent and widespread in nondemented individuals, mild cognitive impairment is associated with a unique pattern of structural vulnerability reflected in differential volume loss in specific regions. Early identification of patterns of abnormality is of fundamental importance for detecting disease onset and tracking progression.

Computational biology for visualization of brain structure

The complexity and variability of human brain (as well as other species) across subjects is so great that reliance on maps and atlases is essential to effectively manipulate, analyze and interpret brain data. Central to these tasks is the construction of averages, templates and models to describe how the brain and its component parts are organized. Design of appropriate reference systems and visualization strategies for human brain data presents considerable challenges, since these systems must capture how brain structure and function vary in large populations, across age and gender, in different disease states, across imaging modalities and even across species. This paper will describe the application of brain maps to a variety of questions and problems in health and disease. It includes a brief survey of different types of maps, including those that capture dynamic patterns of brain change over time.

Staging of Alzheimer-Related Cortical Destruction

Currently used criteria for neuropathological diagnosis of Alzheimer's disease (AD) allow only the distinction of fully developed AD or ill-defined cases with less severe pathologic alterations. There is a need for a staging procedure that is able to supplement the currently used criteria, to allow for sufficient differentiation between the initial and intermediate stages of the illness, and to provide a characterization of the degree of involvement in the brain tissue of "nondemented, age-related controls." The destructive process underlying AD is characterized by a typical distribution pattern of brain changes that is specific with respect to area, lamina, and even cell type. The most conspicuous change is the progressive deposition of abnormal proteins, both between and within the nerve cells. Conventional staining methods to identify these deposits lack sensitivity and specificity. Silver methods (specifically the Gallyas silver-iodide technique for neurofibrillary changes and the Campbell-Switzer silver-pyridin technique for brain amyloid) are by far the best suited to diagnostic work. They are inexpensive, simple to use, and far more reliable. This article describes the patterns of staining typically found with each of these techniques in the brains of patients with progressively severe AD and describes how the specific changes observed can be used as a staging system for diagnostic purposes.

Pattern of brain morphology in patients with schizophrenia and large cavum septi pellucidi.

Cavum septi pellucidi (CSP) is a midline developmental anomaly shown to have increased incidence in patients with schizophrenia. The etiology of CSP may involve dysgenesis of the temporal lobes. This study evaluated the pattern of brain changes in three groups: 1) normal control subjects, 2) schizophrenic subjects without large CSP, and 3) schizophrenic subjects with large CSP. Patients without large CSP had decreased total brain, frontal, and temporal lobe volumes; patients with the anomaly had more pronounced right > left asymmetry and volume decrement limited to the left temporal lobe. These findings indicate that patients with schizophrenia and large CSP may show a different pattern of disturbed brain morphology than patients without this abnormality.