Improved whole-brain reconfiguration efficiency reveals mechanisms of speech rehabilitation in cleft lip and palate patients: an fMRI study

Abstract

Introduction: Cleft lip and/or palate (CLP) patients still have severe speech disorder requiring speech rehabilitation after surgical repair. The clarity of language rehabilitation is evaluated clinically by the Language Rehabilitation Scale. However, the pattern and underlying mechanisms of functional changes in the brain are not yet clear. Recent studies suggest that the brain's reconfiguration efficiency appears to be a key feature of its network dynamics and general cognitive abilities. In this study, we compared the association between rehabilitation effects and reconfiguration efficiency.

Methods: We evaluated CLP patients with speech rehabilitation (n = 23) and without speech rehabilitation (n = 23) and normal controls (n = 25). Assessed CLP patients on the Chinese Speech Intelligibility Test Word Lists and collected fMRI data and behavioral data for all participants. We compared behavioral data and task activation levels between participants for between-group differences and calculated reconfiguration efficiencies for each task based on each participant. In patients, we correlated reconfiguration efficiency with task performance and measured the correlation between them.

Results: Behaviorally, CLP patients with rehabilitation scored significantly higher than those without rehabilitation on the Chinese Speech Intelligibility Test Word Lists. Rehabilitation caused local brain activation levels of CLP patients to converge toward those of controls, indicating rehabilitative effects on brain function. Analysis of reconfiguration efficiency across tasks at the local and whole-brain levels identified underlying recovery mechanisms. Whole-brain reconfiguration efficiency was significantly and positively correlated with task performance.

Conclusion: Our results suggest that speech rehabilitation can improve the level of language-related brain activity in CLP patients, and that reconfiguration efficiency can be used as an assessment index of language clarity to evaluate the effectiveness of brain rehabilitation in CLP patients, a finding that can provide a better understanding of the degree of brain function recovery in patients.

Keywords: CLP; biomarker; fMRI; functional connectivity; reconfiguration efficiency; speech rehabilitation.

FIGURE 1

Experimental design and sequence. (A) The experimental design used a block design with a task block and resting block that alternated three times. Each block lasted 33 s. In the resting block, the “+” sign appeared for 33 s, requiring the participants to look at the “+” in the center of the screen and to keep the head stationary. (B) Subvocalization task: started with the appearance of a picture of an eye that lasted 3 s, and was followed by alternating presentations of a Chinese character and “+” that repeated 10 times. The participants were asked to press the response key after mentally reading the character as clearly as possible. (C) Reading task: started with the appearance of a picture of lips, followed by Chinese characters and “+,” repeated 10 times. The participants were required to read the Chinese characters as clearly as possible and then pressed the response key as soon as possible.

FIGURE 2

Rationale for evaluating the efficiency of FC network architecture reconfiguration. (A) We hypothesized that CLP patients with speech rehabilitation in the Aclp group had a higher similarity between resting-state FC and task-based FC, had a more efficient FC update efficiency, and were closer to normal participants than CLP patients without speech rehabilitation in the Bclp group. This conceptual diagram illustrated our assumptions about the reconfiguration efficiency in different groups. (B) In this study, mean time series were extracted from the AAL-1024 atlas, and paired correlations were calculated between each participant’s resting and task states. The reconfiguration efficiency was then computed by calculating the similarity between the task-based FC and the resting-state FC.

FIGURE 3

Group-level activation results and selection of ROIs for the three groups of participants based on performance in different tasks. (A) Plots a, b, and c show the group-level activation results in the three groups of participants during the reading task; plot d shows the 12 ROIs selected by an F test of differentially activated brain regions. (B) Plots a, b, and c show the group-level activation results in the three groups of participants during the subvocalization task; plot d shows the eight ROIs selected by an F test of differentially activated brain regions.

FIGURE 4

Percent signal change in ROIs for the three groups of participants. (A) The percent signal change observed in the participants during the reading task for 12 ROIs based on F tests of differentially activated brain regions. (B) Percent signal change observed in participants during the subvocalization task for eight ROIs based on F tests of differentially activated brain regions. Error lines in the figure represent the standard error of the mean (SEM).

FIGURE 5

Reconfiguration efficiency in the three groups of participants in different tasks. (A) Reconfiguration efficiency in three groups in the reading task-activated brain network, and there are significant differences only between the Bclp and the Aclp group (p < 0.05). (B) Reconfiguration efficiency in the three groups in the subvocalization task-activated brain network, and the results show significant differences between the Bclp and the Aclp group and between the Bclp and the Norm group (p < 0.05). (C) Reconfiguration efficiency in the three groups in the reading task based on AAL-1024 atlas, and the results show that the reconfiguration efficiency in the Bclp and Aclp group and in the Bclp and Norm group were significantly different (p < 0.01), with no significant difference between the Aclp and Norm groups. (D) Reconfiguration efficiency in the three groups in the subvocalization task based on AAL-1024 atlas, and the results show that there were no significant differences in reconfiguration efficiency among the three groups. Error lines in the figure represent standard deviations (SDs). *p < 0.05; **p < 0.01.

FIGURE 6

Correlations between patients’ reconfiguration efficiency based on a whole-brain anatomical network or task-based functional networks and task performance in the reading task. (A) Correlation between reconfiguration efficiency in the task-based regional network and task behavior performance scores in the Bclp group. (B) Correlation between reconfiguration efficiency in the task-based regional network and task behavior performance scores in the Aclp group. (C) Correlation between reconfiguration efficiency based on the whole-brain anatomical network and task behavior performance scores in the Bclp group. (D) Correlation of reconfiguration efficiency based on the whole-brain anatomical network and task behavior performance scores in the Aclp group. Error lines in the figure are standard deviations (SDs).