Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia

Abstract

In this study, we examined regions in the left and right hemisphere language network that were altered in terms of the underlying neural activation and effective connectivity subsequent to language rehabilitation. Eight persons with chronic post-stroke aphasia and eight normal controls participated in the current study. Patients received a 10 week semantic feature-based rehabilitation program to improve their skills. Therapy was provided on atypical examples of one trained category while two control categories were monitored; the categories were counterbalanced across patients. In each fMRI session, two experimental tasks were conducted: (a) picture naming and (b) semantic feature verification of trained and untrained categories. Analysis of treatment effect sizes revealed that all patients showed greater improvements on the trained category relative to untrained categories. Results from this study show remarkable patterns of consistency despite the inherent variability in lesion size and activation patterns across patients. Across patients, activation that emerged as a function of rehabilitation on the trained category included bilateral IFG, bilateral SFG, LMFG, and LPCG for picture naming; and bilateral IFG, bilateral MFG, LSFG, and bilateral MTG for semantic feature verification. Analysis of effective connectivity using Dynamic Causal Modeling (DCM) indicated that LIFG was the consistently significantly modulated region after rehabilitation across participants. These results indicate that language networks in patients with aphasia resemble normal language control networks and that this similarity is accentuated by rehabilitation.

Keywords: aphasia; dynamic causal modeling; effective connectivity; fMRI activations; language recovery; naming; rehabilitation; stroke.

Figure 1

Lesion overlap of all the eight patients.

Figure 2

Picture naming (top) and Semantic feature task (bottom).

Figure 3

(A) Overlap activation maps of the eight healthy controls for picture naming task. (B) Overlap activation maps of the eight healthy controls for the semantic feature verification task. The voxels are at threshold based on T > 3.10, p = 0.001. See Tables 4, 5 for individual thresholded activation.

Figure 4

(A) Connectivity patterns for controls for the picture naming task. (B) Connectivity patterns for controls for the semantic feature verification task. For both tasks, average modulation for eight controls are shown. Oval shapes are the VOI's selected for model space, ranging from lowest (red) to highest (blue) modulation strengths. Intrinsic connections are shown in black arrows.

Figure 5

Series of images showing individual patients' activation maps for the picture naming task illustrating the [post-rehabilitation (picture-scrambled)]–[pre-rehabilitation (picture-scrambled)] contrast for the trained category at p = 0.001 uncorrected. Voxels above a threshold of T > 3.10 are shown.

Figure 6

Series of images showing individual patients' activation maps for the semantic feature verification task illustrating the [post-rehabilitation (picture-scrambled)]–[pre-rehabilitation (picture-scrambled)] contrast for the trained category at p = 0.001 uncorrected. Voxels above a threshold of T > 3.10 are shown.

Figure 7

Series of images show individual patients' connectivity networks as a function of rehabilitation for the trained category on the picture naming task. Regions with significant modulations are shown in blue ovals while regions with non-significant modulations are shown in white ovals. Intrinsic connections are shown in black arrows while connections with significant modulations are shown in red arrows.

Figure 8

Series of images showing individual patients' connectivity networks as a function of rehabilitation for the trained category on the semantic feature verification task. Regions with significant modulations are shown in blue ovals while regions with non-significant modulations are shown in white ovals. Intrinsic connections are shown in black arrows while connections with significant modulations are shown in red arrows.