Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke

Abstract

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1-2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits.

Keywords: dementia; functional connectivity; motor control; neglect; stroke.

The behavioural specificity of abnormalities in resting state functional connectivity (rs-FC) after stroke is unclear. Baldassarre et al. provide evidence for a double dissociation: Attentional deficits correlate with disruption of inter-hemispheric FC in the dorsal attention network, whereas motor impairments relate to disruption of inter-hemispheric FC in the motor network.

Figure 1

Lesion topography and behavioural results. (A) Lesion density in the sample of patients (n = 44) for right hemisphere lesions only. The colour bar indicates the number of patients with a lesion in a given voxel. (B) The scatter plot displays the correlation between the scores of the motor deficit (upper extremity plus lower extremity) component (x-axis) and attention deficit component (y-axis) from the PCA (r = 0.39, P < 0.001).

Figure 2

Dorsal attention and motor networks. Lateral, dorsal and medial view of dorsal attention (DAN) and motor (MN) networks projected onto an inflated representation of the PALS (population-average, landmark, and surface-based) atlas (Van Essen, 2005). Voxels in red and black belong to the dorsal attention and motor network, respectively. Voxels in white indicate the overlap between the dorsal attention and motor networks. Circles indicate the regions of interest (ROIs) belonging to the dorsal attention (red) and motor networks (black). RH = right hemisphere.

Figure 3

Flowchart of steps involved in computing partial correlation between behavioural deficit and interhemispheric FC. The figure displays the pipeline for computing the four interhemispheric FC-behaviour partial correlation scores (see ‘Materials and methods’ section). (A–J) Panels display real data and refer to a single patient, K shows simulated data rather than real data and refers to the whole sample (n = 43). A shows the dorsal view of a single patient voxel-wise functional connectivity (FC) map derived from a region of interest (ROI), e.g. left frontal eye field (L FEF, red circle), belonging to the left dorsal attention network (DAN). Orange-yellow colours indicate voxels with positive FC with the region of interest; blue-cyan colours indicate negative FC. LH = left hemisphere; RH = right hemisphere. (B) The dorsal view of a single-patient network-based FC map obtained by averaging the region of interest-based FC maps of the left DAN. Colour scale and labels as in A. Panel C displays a network mask retaining voxels (relatively) uniquely belonging to the right DAN, i.e. DAN_mask (red colour). D shows the single-patient network-based FC map (i.e. left DAN, B) masked with the network mask (derived from young controls, explained in ‘Materials and methods’ section) displayed in C. Accordingly, the map shows the values of FC between the left DAN regions of interest and the target voxels (relatively) uniquely belonging to the DAN in the right hemisphere. Colour scale and labels as in A and B. (E–H) The same procedure as in A–D is illustrated, starting from a region of interest of the right hemisphere e.g. right frontal eye field (E) and applying the network mask in the left hemisphere e.g. left DAN_mask (G). Colour scale and labels in E–F and H as in A, B and D. (I) The interhemispheric summary FC is shown of the DAN obtained by averaging the FC scores over the voxels retained within the masked maps in D and H. Panel J displays the functional connectivity (FC) #2. The white bar indicates the interhemispheric summary FC of motor network, obtained in a representative patient. Panel K displays simulated data of the partial correlation coefficient obtained by correlating Behaviour #1, e.g. attention deficit for all patients (n = 43), and the interhemispheric FC summary score of DAN (I), statistically removing effects of Behaviour #2, e.g. motor deficit and FC #2 (J) derived from the motor network.

Figure 4

Partial correlations between behavioural deficits and interhemispheric FC. The bar graph plots four FC-behaviour partial correlation coefficients (r Pearson) derived from the interhemispheric FC of the DAN (black) and motor network (white). Bars 1–2 and 3–4 indicate correlations involving the attention deficit and motor deficit, respectively. Each correlation coefficient, e.g. bar 1, is obtained by correlating a given behaviour, e.g. attention deficit, with the FC derived from a given network, e.g. DAN FC, by statistically removing the other behaviour, e.g. motor deficit, as well as the FC derived from the other network, e.g. the motor network FC.