Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding

Abstract

Objective: The ultimate goal of reading is to understand written text. To accomplish this, children must first master decoding, the ability to translate printed words into sounds. Although decoding and reading comprehension are highly interdependent, some children struggle to decode but comprehend well, whereas others with good decoding skills fail to comprehend. The neural basis underlying individual differences in this discrepancy between decoding and comprehension abilities is virtually unknown.

Methods: We investigated the neural basis underlying reading discrepancy, defined as the difference between reading comprehension and decoding skills, in a three-part study: 1) The neuroanatomical basis of reading discrepancy in a cross-sectional sample of school-age children with a wide range of reading abilities (Experiment-1; n = 55); 2) Whether a discrepancy-related neural signature is present in beginning readers and predictive of future discrepancy (Experiment-2; n = 43); and 3) Whether discrepancy-related regions are part of a domain-general or a language specialized network, utilizing the 1000 Functional Connectome data and large-scale reverse inference from Neurosynth.org (Experiment-3).

Results: Results converged onto the left dorsolateral prefrontal cortex (DLPFC), as related to having discrepantly higher reading comprehension relative to decoding ability. Increased gray matter volume (GMV) was associated with greater discrepancy (Experiment-1). Region-of-interest (ROI) analyses based on the left DLPFC cluster identified in Experiment-1 revealed that regional GMV within this ROI in beginning readers predicted discrepancy three years later (Experiment-2). This region was associated with the fronto-parietal network that is considered fundamental for working memory and cognitive control (Experiment-3).

Interpretation: Processes related to the prefrontal cortex might be linked to reading discrepancy. The findings may be important for understanding cognitive resilience, which we operationalize as those individuals with greater higher-order reading skills such as reading comprehension compared to lower-order reading skills such as decoding skills. Our study provides insights into reading development, existing theories of reading, and cognitive processes that are potentially significant to a wide range of reading disorders.

Fig 1. Scatter-plot of decoding (DECODE; WRMT-WA SS) and reading comprehension scores (COMP; WRMT-PC SS).

Participants from Experiment-1 are displayed in red. DECODE and COMP measures showed a significant positive correlation (r = 0.67, p < 0.001). The discrepancy index (DiscInd; i.e., COMP “minus (-)” DECODE) was greater than 10 SS (Standard Score) for 27.3% of the participants (triangles) i.e., they were better at comprehending than decoding. Discrepancy was in the opposite direction and negative for 21.8% of the participants, i.e., less than -10 SS and they were better at decoding than comprehending (squares). Participants that did not belong to either group are those without a large discrepancy between DECODE and COMP (50.9% of the participants, circles). Participants from Experiment-2 at Time 2 are displayed in green. DiscInd was greater than 10 SS for 20.9% (triangles), less than -10 SS for 41.9% (squares), and non-discrepant (between -10 and 10 SS) for 37.2% of the participants (circles).

Fig 2. The neural correlates of decoding, reading comprehension and DiscInd.

A. Experiment-1. Association between GMV and behavioral measures of decoding (DECODE) and reading comprehension scores (COMP). A-1. Association between GMV with COMP (blue) and DECODE (pink). A-2. Association between GMV with COMP partialling out DECODE (cyan). There were no regions that correlated between GMV and DECODE when COMP was partialled out. B. Experiment-1 and Experiment-2. Association between GMV and DiscInd, i.e., a score subtracting DECODE from COMP. B-1. The cluster that shows association between GMV and DiscInd in school-age children from Experiment-1 whole brain analysis is shown in red. In Experiment-2, the cluster that shows association between GMV of beginning readers and DiscInd 3 years later within the cluster obtained from Experiement-1 using ROI small volume correction is shown in green. B-2. Mean values extracted from the clusters in B-1 are plotted as scatterplots to show that the positive relationships between DiscInd scores and left dorsolateral prefrontal cortex (DLPFC) GMV are not driven by children with dyslexia in Experiment-1 (red full circle) or from the children with a family history of dyslexia in Experiment-2 (green full circle).

Fig 3. Reverse inference results in Experiment-3.

A. Resting state functional connectivity (rsFC) from the left DLPFC cluster’s center of gravity (COG) as seed (MNI x = -40, y = 38, z = 16) using the 1000 Functional Connectome data using threshold of r > 0.30 B. The voxel-by-voxel values from the resulting rsFC map and reverse inference map for each term were correlated. The resulting correlation values are plotted against each key term with threshold of r > 0.1.

Fig 4. Description of the Reading System Framework and contributions of the current study to this Framework.

The Reading System Framework by Perfetti is represented in blue lines. It emphasizes the lexical component that mediates decoding, reading comprehension and the integration between language knowledge with reading processes. Current findings are represented in red lines. They indicate that the left DLPFC network, and possibly by inference, cognitive control and working memory, influence reading comprehension (single-lined red arrow), also strongly modify the strength of the relation between the two (double-lined red arrow).