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Background. Motor recovery after stroke is predicted only moderately by clinical variables, implying that there is still a substantial amount of unexplained, biologically meaningful variability in recovery. Regression diagnostics can indicate whether this is associated simply with Gaussian error or instead with multiple subpopulations that vary in their relationships to the clinical variables. Objective. To perform regression diagnostics on a linear model for recovery versus clinical predictors. Methods. Forty-one patients with ischemic stroke were studied. Impairment was assessed using the upper extremity Fugl-Meyer Motor Score. Motor recovery was defined as the change in the upper extremity Fugl-Meyer Motor Score from 24 to 72 hours after stroke to 3 or 6 months later. The clinical predictors in the model were age, gender, infarct location (subcortical vs cortical), diffusion weighted imaging infarct volume, time to reassessment, and acute upper extremity Fugl-Meyer Motor Score. Regression diagnostics included a Kolmogorov-Smirnov test for Gaussian errors and a test for outliers using Studentized deleted residuals. Results. In the random sample, clinical variables explained only 47% of the variance in recovery. Among the patients with the most severe initial impairment, there was a set of regression outliers who recovered very poorly. With the outliers removed, explained variance in recovery increased to 89%, and recovery was well approximated by a proportional relationship with initial impairment (recovery ≅ 0.70 × initial impairment). Conclusions. Clinical variables only moderately predict motor recovery. Regression diagnostics demonstrated the existence of a subpopulation of outliers with severe initial impairment who show little recovery. When these outliers were removed, clinical variables were good predictors of recovery among the remaining patients, showing a tight proportional relationship to initial impairment.

The human striatum is functionally organized into limbic, associative, and sensorimotor subdivisions, which process information related to emotional, cognitive, and motor function. Dopamine projections ascending from the midbrain provide important modulatory input to these striatal subregions. The aim of this study was to compare activation of dopamine D2 receptors after amphetamine administration in the functional subdivisions of the human striatum. D2 receptor availability (V3″) was measured with positron emission tomography and [11C]raclopride in 14 healthy volunteers under control conditions and after the intravenous administration of amphetamine (0.3 mg/kg). For each condition, [11C]raclopride was administered as a priming bolus followed by constant infusion, and measurements of D2 receptor availability were obtained under sustained binding equilibrium conditions. Amphetamine induced a significantly larger reduction in D2 receptor availability (ΔV3″) in limbic (ventral striatum, −15.3 ± 11.8%) and sensorimotor (postcommissural putamen, −16.1 ± 9.6%) regions compared with associative regions (caudate and precommissural putamen, −8.1 ± 7.2%). Results of this region-of-interest analysis were confirmed by a voxel-based analysis. Correction for the partial volume effect showed even greater differences in ΔV3″ between limbic (−17.8 ± 13.8%), sensorimotor (−16.6 ± 9.9%), and associative regions (−7.5 ± 7.5%). The increase in euphoria reported by subjects after amphetamine was associated with larger ΔV3″ in the limbic and sensorimotor regions, but not in the associative regions. These results show significant differences in the dopamine response to amphetamine between the functional subdivisions of the human striatum. The mechanisms potentially accounting for these regional differences in amphetamine-induced dopamine release within the striatum remain to be elucidated, but may be related to the asymmetrical feed-forward influences mediating the integration of limbic, cognitive, and sensorimotor striatal function via dopamine cell territories in the ventral midbrain.