Transforming Infant Hearing Care with Objective Neuroimaging Measures
Transforming Infant Hearing Care with Objective Neuroimaging Measures
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Developed innovative, non-invasive methods to objectively measure language development in infants, addressing a critical challenge in early hearing loss management. This work introduced functional near-infrared spectroscopy (fNIRS) as a practical tool for pediatric audiology, enabling accurate brain connectivity mapping without requiring active participation, ideal for babies under one year.
Validated protocols demonstrated that reliable connectivity assessment can be achieved with recordings as short as 3 minutes, achieving classification accuracy above 90%, making the approach feasible for real-world clinical workflows. Longer sessions (5-7 minutes) further improved stability, but the ability to deliver biologically meaningful insights from short recordings represents a major step toward routine clinical adoption.
A novel noise-reduction pipeline was developed to eliminate physiological artifacts such as heartbeat and breathing, significantly reducing false connectivity findings and improving confidence in interpretation. These enhancements could allow clinicians to obtain clear, objective measures of brain network organization in challenging infant cohorts.
This work established measurable developmental benchmarks: long-range connections between language regions strengthened progressively during the first year of life, and by six months, networks reorganized to support efficient speech processing. Preliminary analysis of hearing-impaired infants revealed altered connectivity patterns, highlighting the potential of these measures as early biomarkers for auditory deprivation.
The findings enable objective, clinic-friendly protocols for early diagnosis, personalized intervention, and post-treatment monitoring for infants and improve long-term language outcomes for young children receiving hearing aids or cochlear implants.
Reducing false discoveries in resting-state functional connectivity using short channel correction: an fNIRS study
Reducing false discoveries in resting-state functional connectivity using short channel correction: an fNIRS study
Functional near-infrared spectroscopy (fNIRS) connectivity analyses are often distorted by non-neuronal signals, leading to misleading interpretations of brain networks. This study evaluated whether removing these signals using short channel correction improves resting-state connectivity measures. Applying this approach significantly reduced spurious correlations and improved the ability to distinguish networks with known differences in connectivity. These findings show that short channel correction enhances the reliability and interpretability of resting‑state fNIRS connectivity analyses. [Full Paper]
Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS
Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS
This study examined how language‑related brain networks develop during the first year of life. By measuring resting‑state functional connectivity in normal‑hearing infants, we found that connectivity between key language regions—both across and within hemispheres—strengthens significantly with age. These findings map the early developmental trajectory of primary language areas and highlight the potential of functional connectivity measures to identify atypical brain development and better understand early language delays in infants with hearing impairment. [Full Paper]
Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study
Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study
This work investigated how infants’ language networks differ between resting silence and continuous speech. Using functional connectivity and network analysis, we found that infant language networks show a small‑world organization in both conditions, but with higher functional integration at rest and greater functional segregation during speech processing. These differences became more consistent after six months of age. The findings suggest that infants’ brains support more efficient distributed processing when not listening to speech, and shift to more specialized, localized processing when speech is present—insights that may help identify early network disruptions in hearing‑impaired infants. [Full Paper]
Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study
Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study
This work evaluated how connectivity measures and recording duration affect the reliability of resting‑state fNIRS—crucial when long, interruption‑free sessions are not feasible in clinical settings. Comparing three frequency‑domain approaches across 3-9‑minute segments shows that performance improves with longer data, while wavelet coherence consistently delivers the most dependable results with short, 3‑minute windows. The findings provide practical guidance on method selection when data are limited, supporting more scalable, time‑efficient protocols and increasing the clinical viability of resting‑state connectivity biomarkers. Overall, the study clarifies trade‑offs between accuracy and acquisition time and highlights a clear path to robust analyses in real‑world, time‑constrained environments. [Full Paper]
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