BACKGROUND AND PURPOSE: In malignant infarction, brain edema leads to secondary neurological deterioration and poor outcome. We sought to determine whether swelling is associated with outcome in smaller volume strokes.
In this paper we analyze the properties of the well-known segmentation fusion algorithm STAPLE, using a novel inference technique that analytically marginalizes out all model parameters. We demonstrate both theoretically and empirically that when the number of raters is large, or when consensus regions are included in the model, STAPLE devolves into thresholding the average of the input segmentations.
Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition.
Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations.
BACKGROUND AND PURPOSE: Alberta Stroke Program Early Computed Tomographic Score (ASPECTS) has been used to estimate diffusion-weighted imaging (DWI) lesion volume in acute stroke. We aimed to assess correlations of DWI-ASPECTS with lesion volume in different middle cerebral artery (MCA) subregions and reproduce existing ASPECTS thresholds of a malignant profile defined by lesion volume ≥100 mL.
PURPOSE: To enable fast reconstruction of quantitative susceptibility maps with total variation penalty and automatic regularization parameter selection.
METHODS: ℓ(1) -Regularized susceptibility mapping is accelerated by variable splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and fast Fourier transforms. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization.
BACKGROUND: Clues to the etiology and pathophysiology of schizophrenia can be examined in their first-degree relatives because they are genetically related to an ill family member, and have few confounds like medications. Brain abnormalities observed in young relatives are neurobiological indicators of vulnerability to illness. We examined the hypothesis that the hippocampus and parahippocampus are structurally abnormal and are related to default mode network (DMN) function and cognitive abnormalities in relatives of probands.
Placebo and nocebo effects are essential components of medical practice and efficacy research, and can be regarded as a special case of context learning. A fundamental function of the central nervous system is to configure the way in which previous learned context becomes linked to corresponding responses. These responses could be either automatic procedures with little flexibility or highly adaptive procedures modified by associated contexts and consequences.
We investigated a triple transgene Alzheimer's disease (AD) mouse model that recapitulates many of the neurochemical, anatomic, pathologic and behavioral defects seen in human AD. We studied the mice as a function of age and brain region and investigated potential therapy with the non-steroidal anti-inflammatory drug ibuprofen. Magnetic resonance spectroscopy (MRS) showed alterations characteristic of AD (i.e. increased myo-inositol and decreased N-acetylaspartate (NAA)).
