This study tested the hypothesis that diffusion tensor imaging (DTI) can detect alteration in microscopic integrity of white matter (WM) and basal ganglia (BG) regions known to be involved in Parkinson's disease (PD) pathology. It was also hypothesized that there is an association between the DTI abnormality and PD severity and subtype. DTI at 4 Tesla was obtained in 12 PD and 20 control subjects. The DTI measures of fractional anisotropy (FA) and mean diffusivity (MD) were evaluated using both region of interest (ROI) and voxel-based methods. Movement deficits in PD subjects were assessed using Motor Subscale (Part III) of the Unified Parkinson's Disease Rating Scale (UPDRS). Subtype determination of movement deficits was derived based upon results of subjects’ UPDRS ratings. Reduced FA (p<0.05, corrected) was found in PD subjects in a number of regions, including the precentral gyrus, substantia nigra, putamen, posterior striatum, frontal WM, and in regions related to the supplementary motor areas. Reduced FA in the substantia nigra correlated (p<0.05, corrected) with increased UPDRS motor scores. Significant spatial correlations between FA alterations in putamen and other PD-affected regions were also found in the context of PD subtypes index analysis. Our data suggest that microstructural alterations detected with DTI might serve as a potential biomarker for PD.

In peripheral vision, objects in clutter are difficult to identify. The exact cause of this "crowding" effect is unclear. To perceive coherent shapes in clutter, the visual system must integrate certain local features across receptive fields while preventing others from being combined. It is believed that this selective feature integration-segmentation process is impaired in peripheral vision, leading to crowding. We used functional magnetic resonance imaging (fMRI) to investigate the neural origin of crowding. We found that crowding was associated with suppressed fMRI signal as early as V1, regardless of whether attention was directed toward or away from a target stimulus. This suppression in early visual cortex was greatest for stimuli that produced the strongest crowding. In contrast, the pattern of activity was mixed in higher level visual areas, such as the lateral occipital cortex. These results support the view that the deficiency in feature integration and segmentation in peripheral vision is present at the earliest stages of cortical processing.

Efficient neural processing depends on regulating responses through suppression and facilitation of neural activity. Utilizing a well-known visual motion paradigm that evokes behavioral suppression and facilitation, and combining 5 different methodologies (behavioral psychophysics, computational modeling, functional MRI, pharmacology, and magnetic resonance spectroscopy), we provide evidence that challenges commonly held assumptions about the neural processes underlying suppression and facilitation. We show that: 1) both suppression and facilitation can emerge from a single, computational principle -divisive normalization; there is no need to invoke separate neural mechanisms, 2) neural suppression and facilitation in the motion-selective area MT mirror perception, but strong suppression also occurs in earlier visual areas, and 3) suppression is not driven by GABA-mediated inhibition. Thus, while commonly used spatial suppression paradigms may provide insight into neural response magnitudes in visual areas, they cannot be used to infer neural inhibition.

Efficient neural processing depends on regulating responses through suppression and facilitation of neural activity. Utilizing a well-known visual motion paradigm that evokes behavioral suppression and facilitation, and combining five different methodologies (behavioral psychophysics, computational modeling, functional MRI, pharmacology, and magnetic resonance spectroscopy), we provide evidence that challenges commonly held assumptions about the neural processes underlying suppression and facilitation. We show that: (1) both suppression and facilitation can emerge from a single, computational principle – divisive normalization; there is no need to invoke separate neural mechanisms, (2) neural suppression and facilitation in the motion-selective area MT mirror perception, but strong suppression also occurs in earlier visual areas, and (3) suppression is not primarily driven by GABA-mediated inhibition. Thus, while commonly used spatial suppression paradigms may provide insight into neural response magnitudes in visual areas, they should not be used to infer neural inhibition.