The motor deficits in Parkinson's disease (PD) have been primarily associated with internally guided (IG), but not externally guided (EG), tasks. This study investigated the functional mechanisms underlying this phenomenon using genetically-matched twins. Functional magnetic resonance images were obtained from a monozygotic twin pair discordant for clinical PD. Single-photon emission computed tomography neuroimaging using [(123)I](-)-2-beta-carboxymethoxy-3-beta-(4-iodophenyl)tropane confirmed their disease-discordant status by demonstrating a severe loss of transporter binding in the PD-twin, whereas the non-PD-twin was normal. Six runs of functional magnetic resonance imaging (fMRI) data were acquired from each twin performing EG and IG right-hand finger sequential tasks. The percentage of voxels activated in each of several regions of interest (ROI) was calculated. Multiple analysis of variance was used to compare each twin's activity in ROIs constituting the striato-thalamo-cortical motor circuits [basal ganglia (BG)-cortical circuitry, but including the globus pallidus/putamen, thalamus, supplementary motor area, and primary motor cortex] and cerebello-thalamo-cortical circuits (cerebellar-cortical circuitry, including the cerebellum, thalamus, somatosensory cortex, and lateral premotor cortex). During the EG task, there were no significant differences between the twins in bilateral BG-cortical pathways, either basally or after levodopa, whereas the PD-twin had relatively increased activity in the cerebellar-cortical pathways basally that was normalized by levodopa. During the IG task, the PD-twin had less activation than the non-PD-twin in ROIs of the bilateral BG-cortical and cerebellar-cortical pathways. Levodopa normalized the hypoactivation in the contralateral BG-cortical pathway, but "over-corrected" the activation in the ipsilateral BG-cortical and bilateral cerebellar-cortical pathways. In this first fMRI study of twins discordant for PD, the data support the hypothesis that BG-cortical and cerebellar-cortical pathways are task-specifically influenced by PD. The levodopa-induced "over-activation" of BG-cortical and cerebellar-cortical pathways, and its relevance to both compensatory changes in PD and the long-term effects of levodopa in PD, merit further exploration.
An approach to modeling the impact of disturbances in an agricultural production network is presented. A stochastic model and its approximate deterministic model for averages over sample paths of the stochastic system are developed. Simulations, sensitivity and generalized sensitivity analyses are given. Finally, it is shown how diseases may be introduced into the network and corresponding simulations are discussed.Keywords: Agricultural production networks, stochastic and deterministic models, sensitivity and generalized sensitivity functions, foot and mouth disease Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.
Brain activity is accompanied by changes in cerebral blood flow (CBF) and the differential blood oxygenation that are detectable using functional magnetic resonance imaging (fMRI). The process of identifying brain activation regions can be facilitated by estimating the hemodynamic response function (HRF). There have been some remarkable new developments in statistics to handle this problem. In this paper, we introduce a novel procedure which is capable of adapting itself to any of the existing methods by improving its performance through the application of a penalized smoothing technique. Using a computer experiment and a real fMRI data set, the proposed procedure is assessed by comparing its performance very favorably to the popular SPM based method.
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