Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Dec:223:105042.
doi: 10.1016/j.bandl.2021.105042. Epub 2021 Oct 22.

Abnormally weak functional connections get stronger in chronic stroke patients who benefit from naming therapy

Jeffrey P Johnson  1 , Erin L Meier  2 , Yue Pan  2 , Swathi Kiran  2
Affiliations

Abnormally weak functional connections get stronger in chronic stroke patients who benefit from naming therapy

Jeffrey P Johnson et al. Brain Lang. 2021 Dec.

Abstract

Language recovery in aphasia is likely supported by a network of brain regions, but few studies have investigated treatment-related changes in functional connectivity while controlling for the absence of treatment. We examined functional connectivity in a 38-region picture-naming network in 30 patients with chronic aphasia who did or did not receive naming therapy. Compared to healthy controls, patients had abnormally low connectivity in a subset of connections from the naming network. Linear mixed models showed that the connectivity of abnormal connections increased significantly in patients who benefited from therapy, but not in those who did not benefit from or receive therapy. Changes in responders were specific to abnormal connections and did not extend to the larger network. Thus, successful naming therapy was associated with increased connectivity in connections that were abnormal prior to treatment. The potential to strengthen such connections may be a prerequisite for a successful treatment response.

Keywords: Aphasia; Functional connectivity; Naming therapy; Rehabilitation; Stroke.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest

None of the authors have a financial conflict of interest with respect to the work reported here.

Declaration of interests

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Swathi Kiran is an advisor to and owns ownership stock in Constant Therapy Health. There is no scientific overlap with this study. Dr. Kiran is also an Action Editor for Brain & Language.

None of the other authors have competing interests to declare.

Figures

Figure 1.
Figure 1.
Participant enrollment and study stages (A); overview of naming treatment activities (B) and the fMRI naming task (C).
Figure 2.
Figure 2.
The abnormal connectome revealed by comparisons between patients and healthy controls. On the left, functional connectivity was significantly lower in patients than controls in all 31 connections shown; the color bar represents t values, with darker shades indicative of a greater difference between groups. On the right is a list of all regions in the abnormal connectome, their abbreviations, and the number of connections in which they were involved.
Figure 3.
Figure 3.
Mean functional connectivity in the abnormal connectome at pre- and post-treatment/hold in (A) treated (TX) and untreated (UN) patients, and (B) responders (R), nonresponders (N), and untreated patients (U). Error bars represent standard error derived from the respective regression models. Dashed horizontal significance lines refer to the effect of time (i.e., in A, change in treated patients from pre to post and in B, change in responders from pre to post); the curved significance lines in B refer to the group-by-time interactions (i.e., changes from pre to post in responders vs nonresponders and responders vs. untreated patients). *p < .05; **p = .01; ***p < .001. (C-E) Histograms of t statistics from the abnormal- and random-connectome models for effects associated with changes in functional connectivity from pre to post in (C) responders, (D) responders vs. untreated patients, and (E) responders vs. nonresponders (i.e., follow-up analysis 2). The t statistics from random-connectome models are shown in gray; t statistics from the abnormal-connectome model are shown in black and surrounded by a red box.
See this image and copyright information in PMC

References

    1. Bates D, Mächler M, Bolker B, & Walker S (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1). 10.18637/jss.v067.i01 - DOI
    1. Beeson PM, & Robey RR (2006). Evaluating single-subject treatment research: Lessons learned from the aphasia literature. Neuropsychology Review, 16(4), 161–169. 10.1007/s11065-006-9013-7 - DOI - PMC - PubMed
    1. Behzadi Y, Restom K, Liau J, & Liu TT (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37(1), 90–101. 10.1016/j.neuroimage.2007.04.042 - DOI - PMC - PubMed
    1. Binder JR, Desai RH, Graves WW, & Conant LL (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 2767–2796. 10.1093/cercor/bhp055 - DOI - PMC - PubMed
    1. Birn RM, Cox RW, & Bandettini PA (2004). Experimental designs and processing strategies for fMRI studies involving overt verbal responses. NeuroImage, 23(3), 1046–1058. 10.1016/j.neuroimage.2004.07.039 - DOI - PubMed

Publication types