Nurturing the reading brain: home literacy practices are associated with children's neural response to printed words through vocabulary skills

The study investigates whether and how the home literacy environment (HLE)—the literacy-related interactions, resources, and attitudes experienced at home—relates to neural mechanisms supporting word-level reading in children. Prior work shows HLE associates with children’s vocabulary and reading, and proposes vocabulary as a mediator between HLE and reading outcomes. Neuroimaging research links socioeconomic status (a proxy often related to HLE) and HLE measures to structural and functional differences in left perisylvian regions, especially the left inferior frontal gyrus (IFG). However, direct evidence connecting HLE frequency to brain activity during visual word recognition in reading children is lacking. This study tests whether the frequency of home literacy practices relates to fMRI-measured neural adaptation to repeated printed words in 8-year-olds, and whether children’s vocabulary mediates this relationship. A control digit-adaptation task assesses specificity to word recognition.

Two complementary literatures motivate the work: (1) SES and the brain: SES correlates with differences in language input and HLE, and with structural/functional differences in left perisylvian regions (e.g., cortical thickness and surface area differences; reduced left IFG specialization). These relations may be mediated by pre-reading skills such as vocabulary. (2) HLE and the brain: Parental questionnaires and home recordings link home reading exposure and shared reading quality to white-matter integrity and left perisylvian activation in preschoolers during auditory story listening; conversational turn-taking relates to surface area, structural connectivity, and left IFG activity. Structural connectivity of left perisylvian areas relates to both HLE and vocabulary. More supportive HLE also relates to increased left IFG activity during phonological tasks in young children. Nevertheless, prior work either examined structural measures in readers or functional measures in pre-readers using auditory tasks; direct links between HLE and functional responses to printed words in reading children remained to be tested. The authors hypothesize that vocabulary mediates the relation between HLE and both reading and neural adaptation to words, and that effects are specific to words rather than general symbolic processing (digits).

Design and participants: Cross-sectional study with two sessions. Behavioral sample: 66 right-handed, French-speaking children (ages 7.52–9.22; mean 8.46) and a parent completed lab tests and questionnaires. fMRI sample: 44 of these children (ages 8.02–9.14; mean 8.49) with usable word and digit adaptation runs; exclusions for incomplete data or excessive motion. SES varied from relatively low to high. All were native French speakers; 89% of participating parents were mothers. Ethical approval obtained; families compensated.

Measures: Children completed the Alouette-R test (reading speed and accuracy) and the NEMI-2 Vocabulary subtest; composite IQ from NEMI-2. Parents completed the Alouette-R (as a proxy for parental reading skill) and a detailed electronic questionnaire on HLE frequency over the past month.

Home literacy practices questionnaire: 18 items adapted from prior HLE instruments, spanning informal activities (e.g., talking about school day, reading environmental print), and formal activities of basic and advanced complexity (e.g., listening to child read aloud; asking questions during reading; spelling/grammar teaching). Frequency rated on a six-point scale; options to indicate past occurrence or child-initiated activity. Subscores computed for informal, formal-basic, formal-advanced; a composite HLE score summed these three. Parents also rated perceived child reading skill.

Experimental tasks: fMRI adaptation paradigm adapted from Perrachione et al. (2016, Exp. 2B). Two tasks: (1) Word adaptation: blocks of monosyllabic French nouns (3–5 letters). (2) Control digit adaptation: Arabic digits 1–8. In each task, adaptation blocks repeated the same stimulus eight times; no-adaptation blocks presented eight different stimuli. Each task had two runs with 10 adaptation, 10 no-adaptation, and 10 fixation blocks per run; block duration 9.6 s; stimulus on-screen 700 ms with 500 ms ISI. A target detection (rocket) event encouraged attention; participants pressed a button on targets.

fMRI acquisition: Siemens Prisma 3T; BOLD EPI TR=2000 ms, TE=24 ms, flip angle 80°, matrix 128×120, FOV 220×206 mm, 32 slices, thickness 3 mm (0.48 mm gap). T1-weighted anatomical: TR=3500 ms, TE=2.24 ms, flip angle 8°, matrix 256×256, FOV 224×224 mm, slice thickness 0.9 mm, 192 slices.

Preprocessing and first-level modeling: SPM12. First four volumes discarded; slice-time correction; realignment; spatial smoothing (Gaussian 4×4×7 mm FWHM). Outlier detection and interpolation (ArtRepair) for volumes exceeding 3 SD global intensity or >2 mm motion; participants with >20% repaired volumes excluded. Normalization to adult MNI space via unified segmentation; normalized voxel size 2×2×3.5 mm. GLM modeled adaptation and no-adaptation blocks (epochs 9.6 s) convolved with canonical HRF; high-pass filter 1/128 Hz; AR(1) serial correlation.

Analytic strategy: Word adaptation effect defined as no-adaptation > adaptation. (A) Whole-brain one-sample t-tests with FDR-corrected cluster-level threshold p<0.05 (voxel p<0.001 or p<0.002) to compare with Perrachione et al. network. (B) ROI analyses using 6-mm spheres centered on Perrachione et al. (2016) typical-reader peaks: left posterior inferior frontal sulcus (pIFS), left posterior dorsal superior temporal sulcus (pdSTS), left pre-SMA, left occipital cortex (OC), left posterior temporal fusiform gyrus (pTF; anterior VWFA), left putamen, right putamen. Tested for word adaptation in each ROI (Bonferroni-corrected). In ROIs with significant adaptation effects across participants (excluding putamen due to inconsistent effects), correlated adaptation magnitudes with composite HLE frequency; partial correlations controlled for parental income and education (SES). Mediation analysis (M3 toolbox, 10,000 bootstrap samples) assessed whether vocabulary mediated HLE–adaptation relations in significant ROIs, controlling SES. Directional hypotheses guided one-sided p-values unless otherwise noted. Control analyses assessed: (1) specificity using digit adaptation; (2) attention using target-detection rates; (3) parental perception of child reading skill; (4) parental reading skill as genetic proxy.

Power: Based on prior effect sizes (r≈0.40–0.60) for HLE–brain/behavior relations, n=44 provided ≥88% power for directional correlations (α=0.05, one-tailed). Monte Carlo simulations indicated ~86% power for mediation paths using comparable parameters.

Behavioral associations (n=66; partial correlations controlling SES):

• Composite HLE frequency positively related to child vocabulary: partial r(64)=0.250, p=0.023. Relations were similar across HLE subtypes (informal r=0.187, p=0.070; formal-basic r=0.182, p=0.075; formal-advanced r=0.240, p=0.028).
• No significant positive relation with reading accuracy: partial r(64)=0.148, p=0.126; or reading speed: partial r(64)=0.121, p=0.174.

Task replication and word adaptation network (n=44):

• Whole-brain analyses showed left-lateralized word adaptation in inferior frontal (pars triangularis/orbitalis), temporal (superior, middle, inferior), and occipital cortices, broadly matching Perrachione et al. (2016).
• ROI-level word adaptation significant (Bonferroni-corrected) in: left pIFS (t(43)=2.698, Pcorr=0.035, d=0.407), left pdSTS (t(43)=3.794, Pcorr<0.002, d=0.572), left pTF/VWFA-anterior (t(43)=4.613, Pcorr<0.001, d=0.695). Partial/weak effects in putamen; non-significant in pre-SMA and OC.

HLE and neural adaptation to words:

• HLE frequency positively related to word adaptation magnitude specifically in left pIFS: r(42)=0.322, Pcorr=0.048; remained significant controlling SES: partial r(42)=0.302, p=0.026. No relations in pdSTS (r=0.052) or pTF (r=-0.056).

Vocabulary and neural adaptation; mediation (left pIFS):

• Vocabulary positively related to word adaptation (controlling SES): partial r(42)=0.317, p=0.020.
• Mediation analysis (controlling SES): • Total effect HLE→pIFS adaptation (path c): β=0.063, SE=0.033, 95% CI Lower=0.011, p=0.024. • HLE→Vocabulary (path a): β=0.427, SE=0.198, 95% CI Lower=0.063, p=0.024. • Vocabulary→pIFS adaptation (path b), controlling HLE: β=0.036, SE=0.026, 95% CI Lower=-0.003, p=0.062 (trend). • Indirect effect (ab): β=0.015, SE=0.014, 95% CI Lower=0.001, p=0.046 (significant mediation). • Direct effect (c′): β=0.048, SE=0.031, 95% CI Lower=-0.001, p=0.052 (ns after accounting for vocabulary).

Specificity and controls:

• No positive relations between digit adaptation and either HLE or vocabulary in any ROI (all r<0.188, all p>0.117), including pIFS.
• Target detection rates (~89% in both tasks) were not correlated with HLE or vocabulary; no task differences.
• Parental perception of child reading skill correlated with child reading accuracy and speed, but not with vocabulary, HLE, or pIFS adaptation; controlling for this perception did not alter HLE–vocabulary or HLE–pIFS relations.
• Controlling for parental reading accuracy/speed (genetic proxy) did not change HLE–vocabulary association (partial r(64)=0.248, p=0.022).

Findings show that the frequency of home literacy practices relates to children’s neural sensitivity to repeated printed words in the left posterior inferior frontal sulcus, part of the anterior reading network, and that this association is influenced by vocabulary skills. The results extend prior HLE and SES literatures by directly linking HLE to functional brain responses during visual word recognition in reading children. Contrary to expectations, no association was observed in visual word-form regions (VWFA), suggesting that at around 8 years, HLE may exert more influence on higher-level phonological/semantic processes supported by IFG than on visual word processing per se. Behavioral links between HLE and reading fluency were not detected, potentially due to measurement sensitivity (Alouette test) in typically developing readers or developmental stage, whereas vocabulary showed the expected association. The paradigm replicated a robust left-lateralized word adaptation network consistent with earlier adult findings, supporting task reliability across languages and ages. Control analyses indicated that effects were not attributable to general symbolic processing (digit task), attentional engagement, parental perception biases, or parental reading skill proxies, supporting specificity to word-level reading and the proposed mediation via vocabulary.

Home literacy practices are associated with neural mechanisms supporting word recognition in 8-year-old children, specifically enhanced neural adaptation to printed words in left pIFS, with children’s vocabulary mediating this relationship. These results support models positing that HLE affects reading-related brain function through precursor skills such as vocabulary. Given the cross-sectional design and modest effect sizes, future longitudinal and interventional studies should test causality, examine younger age ranges when visual word form areas are emerging, and assess broader reading processes such as comprehension using varied tasks.

• Cross-sectional design precludes causal inference; alternative models (e.g., HLE adapting to child skill) are possible.
• HLE measured via parent questionnaire is subject to recall and social desirability biases.
• Modest sample size, restricted age range, and focus on a word-recognition adaptation task limit generalizability to other reading components (e.g., comprehension) and ages.
• ROI-focused approach increases power but may miss effects elsewhere in the brain.
• Reading fluency assessment (Alouette-R) may lack sensitivity to detect variance in typical readers at this age.