Changes in functional connectivity related to direct training and generalization effects of a word finding treatment in chronic aphasia

Abstract

The neural mechanisms that underlie generalization of treatment-induced improvements in word finding in persons with aphasia (PWA) are currently poorly understood. This study aimed to shed light on changes in functional network connectivity underlying generalization in aphasia. To this end, we used fMRI and graph theoretic analyses to examine changes in functional connectivity after a theoretically-based word-finding treatment in which abstract words were used as training items with the goal of promoting generalization to concrete words. Ten right-handed native English-speaking PWA (7 male, 3 female) ranging in age from 47 to 75 (mean=59) participated in this study. Direct training effects coincided with increased functional connectivity for regions involved in abstract word processing. Generalization effects coincided with increased functional connectivity for regions involved in concrete word processing. Importantly, similarities between training and generalization effects were noted as were differences between participants who generalized and those who did not.

Keywords: Aphasia; Functional connectivity; Generalization; Neuroplasticity; Treatment; fMRI.

Copyright © 2015 Elsevier Inc. All rights reserved.

Figures

Fig. 1

Experiment details.

Fig. 2

Treatment results. The abstract effect size is related to direct training, the concrete effect size is related to generalization. Note that P7 did not respond to treatment (ES

Fig. 3

Changes in BOLD signal from pre- to post-treatment for abstract and concrete words at the group level. Red spheres indicate peaks of activation for the one-sample t-test of the [post-treatment abstract > pre-treatment abstract] contrast for the group of responders (n = 9). Blue spheres indicate peaks of activation for the one-sample t-test of the [post-treatment concrete > pre-treatment concrete] contrast for the group of generalizers (n = 7). All results shown are significant at the uncorrected p < 0.001 level. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4

Comparison of node degree of fROIs between the control and treatment periods in the abstract and concrete change networks. This figure illustrates the average node degree for increases in connectivity after the control and treatment periods for fROIs in the abstract difference network (top panel) and the concrete difference network (bottom panel) for the three participants who served as their own controls. The size of each sphere represents the number of participants who show significant increases in connectivity for that region, while the color of the sphere represents the average node degree. Higher values are more purple, lower values are more turquoise. The bar graphs highlight the differences between the control (green) and treatment (purple) periods for the majority (at least 2/3) of control participants. The number of participants who showed increased connectivity for each region is provided to the right of each bar. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

Node degree of fROIs in the trained abstract network, generalized concrete network, and non-generalized concrete network. This figure illustrates the average node degree for increases in connectivity for fROIs in the trained abstract network (top panel), generalized concrete network (middle panel), and non-generalized concrete network (bottom panel). The size of each sphere represents the number of participants who show significant increases in connectivity for that region, while the color of the sphere represents the average node degree. Higher values are more purple, lower values are more turquoise. The bar graphs highlight the regions with the highest node degree for the majority (at least 2/3) of participants. The number of participants who showed increased connectivity for each region is provided to the right of each bar. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 6

Laterality of changes and cross-network comparison of node degree. Panel (A) illustrates the comparison of the bilaterality index between generalizers and nongeneralizers for the trained abstract network and the (non)generalized concrete network. Panel (B) illustrates the comparison of the laterality index between generalizers and non-generalizers for the trained abstract network and the (non)generalized concrete network. Panel (C) illustrates the comparison of the average node degree for increases in connectivity for fROIs among change networks for the majority (at least 2/3) of participants.