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. 2010 Mar;67(3):365-75.
doi: 10.1002/ana.21905.

Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke

Affiliations

Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke

Alex R Carter et al. Ann Neurol. 2010 Mar.

Abstract

Objective: Focal brain lesions can have important remote effects on the function of distant brain regions. The resulting network dysfunction may contribute significantly to behavioral deficits observed after stroke. This study investigates the behavioral significance of changes in the coherence of spontaneous activity in distributed networks after stroke by measuring resting state functional connectivity (FC) using functional magnetic resonance imaging.

Methods: In acute stroke patients, we measured FC in a dorsal attention network and an arm somatomotor network, and determined the correlation of FC with performance obtained in a separate session on tests of attention and motor function. In particular, we compared the behavioral correlation with intrahemispheric FC to the behavioral correlation with interhemispheric FC.

Results: In the attention network, disruption of interhemispheric FC was significantly correlated with abnormal detection of visual stimuli (Pearson r with field effect = -0.624, p = 0.002). In the somatomotor network, disruption of interhemispheric FC was significantly correlated with upper extremity impairment (Pearson r with contralesional Action Research Arm Test = 0.527, p = 0.036). In contrast, intrahemispheric FC within the normal or damaged hemispheres was not correlated with performance in either network. Quantitative lesion analysis demonstrated that our results could not be explained by structural damage alone.

Interpretation: These results suggest that lesions cause state changes in the spontaneous functional architecture of the brain, and constrain behavioral output. Clinically, these results validate using FC for assessing the health of brain networks, with implications for prognosis and recovery from stroke, and underscore the importance of interhemispheric interactions.

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Conflict of interest statement

Disclosures The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Dorsal attention and somatomotor networks identified by resting state functional connectivity MRI
(A and B) Selected sections of the functional connectivity map for the (A) dorsal attention network and (B) the somatomotor network that highlight the nodes in each network in healthy controls. The full map is presented in Supplementary Figure 2. (C) One-way ANOVA with neuronal network as the within subjects factor, and FC score as the dependent variable, shows that the FC within networks was significantly greater than across networks (F(3, 30) = 145.85, p < 0.001), and post-hoc comparisons with paired t-tests indicated a significant difference between each score within a network and the FC score across networks (p < 0.001); pIPS = posterior intraparietal sulcus; vIPS = ventral intraparietal sulcus; FEF = frontal eye field; MT+ = middle temporal complex; CS = central sulcus; SMA = supplemental motor area; Put = putamen; Thal = thalamus; Cbl = cerebellum; error bars are S.E.M.; *** = p < 0.001.
Figure 2
Figure 2. Correlation between the Field Effect and FC scores in four homologous ROI pairs in the dorsal attention network
A) Significant correlation between the Field Effect and most homologous pairs in the dorsal attention network was observed. A significant Field Effect reflects an increase in reaction times (RTs) and increase in % misses when targets are presented to the contralesional side as compared to when they are presented to the ipsilesional side. B) A negative correlation between left-right resting connectivity in the posterior intraparietal sulcus and Field Effect indicates that as FC decreases, the amplitude of the Field Effect RT (left panel) and percent misses (right panel) increases. pIPS = posterior intraparietal sulcus; vIPS = ventral intraparietal sulcus; FEF = frontal eye fields; MT+ = middle temporal complex; L =left; R =right; RT = reaction time; * = p < 0.05.
Figure 3
Figure 3. Inter-hemispheric connectivity in the dorsal attention network predicts attentional deficits
A) Strength of resting connectivity scores for four patterns of connectivity in the dorsal attention network. Repeated measures ANOVA followed by multiple paired t-test shows that homologous resting connectivity is greater than other connectivity patterns. B) The Field Effect RT and % misses are significantly correlated with homologous FC scores but not with ipsilesional or contralesional FC scores. C) Scatter plots demonstrate that this correlation is specific to inter-hemispheric (upper panel) and not intra-hemispheric (lower panel) connectivity. pIPS = posterior intraparietal sulcus; vIPS = ventral intraparietal sulcus; FEF = frontal eye field; MT+ = middle temporal complex; homo = homologous; hetero = heterologous; ipsi = ipsilesional; contra = contralesional; RT =reaction time; * = p < 0.05; *** = p < 0.001.
Figure 4
Figure 4. Correlation between motor function and resting connectivity in the six homologous ROI pairs in the somatomotor network
Grasp, Grip, Pinch, and Gross are all subtests of the action research arm test (ARA test). Pegs/sec = performance measure on nine hole peg test; FIM = Functional Independence Measure; flex = flexion; ext = extension; CS = central sulcus; Put = putamen; Thal = thalamus; SMA = supplementary motor area; CB = cerebellum; * = p < 0.05.
Figure 5
Figure 5. Homolgous inter-hemispheric FC in the somatomotor network predicts arm performance
A) Strength of resting connectivity scores for four patterns of connectivity in the arm somatomotor network. Repeated measures ANOVA followed by multiple paired t-tests shows that homologous resting connectivity is greater than other connectivity patterns. B) Four out of five measures of arm function are significantly correlated specifically with homologous FC scores. Neither of the two measures of leg function is significantly correlated. Homo = homologous connectivity; hetero = heterologous connectivity; contra = contralesional connectivity; ipsi = ipsilesional connectivity. ARA = action research arm test; FIM = functional independence measure; Flex = flexion; Ext = extension; contra = Contralesional; * = p < 0.05; *** = p < 0.001.
Figure 6
Figure 6. Differential specificity of FC-behavior correlations in the somatomotor network compared to the attention network
Homologous FC scores in the somatomotor network are correlated with measures of hand function (total ARAT score, 9 Hole Peg Test (NHPT)), but not with measures of leg function (walking speed, FIM walk), nor with measures of visuo-spatial attention (FE RT, FE % misses). Homologous FC scores in the dorsal attention network on the other hand are significantly correlated with all the measures shown. ARA = action research arm test; FIM Walk = Functional Independence Measure walk item; NHPT = nine hole peg test; FE = Field Effect; RT = reaction time; * = p < 0.05; ** = p < 0.01.
Figure 7
Figure 7. Lesion distribution and ROI damage
A) Distribution of stroke lesions in 22 subjects. Color scale indicates number of subjects with lesioned voxel. B) Percentage of the total voxels in each ROI lesioned by infarct. ROI labels are same as in Figure 1. L = left; R = right; n = 22; error bars = SEM.
Figure 8
Figure 8. Effect of ROI size and asymmetry on FC-behavior correlations
Repeat analysis using spherical uniform ROIs did not affect FC-behavior correlations in the somatomotor network. Homologous intra-hemispheric FC remained predictive of scores on the ARA, Grip strength, 9 hole peg, and wrist extension tests. The two measures of leg function remained uncorrelated. Homo = homologous connectivity; hetero = heterologous connectivity; contra = contralesional connectivity; ipsi = ipsilesional connectivity. ARA = action research arm test; FIM = functional independence measure; Flex = flexion; Ext = extension; contra = Contralesional; * = p < 0.05.

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