Use of Functional Near-Infrared Spectroscopy to Predict and Measure Cochlear Implant Outcomes: A Scoping Review

Abstract

Outcomes following cochlear implantation vary widely for both adults and children, and behavioral tests are currently relied upon to assess this. However, these behavioral tests rely on subjective judgements that can be unreliable, particularly for infants and young children. The addition of an objective test of outcome following cochlear implantation is therefore desirable. The aim of this scoping review was to comprehensively catalogue the evidence for the potential of functional near infrared spectroscopy (fNIRS) to be used as a tool to objectively predict and measure cochlear implant outcomes. A scoping review of the literature was conducted following the PRISMA extension for scoping review framework. Searches were conducted in the MEDLINE, EMBASE, PubMed, CINAHL, SCOPUS, and Web of Science electronic databases, with a hand search conducted in Google Scholar. Key terms relating to near infrared spectroscopy and cochlear implants were used to identify relevant publications. Eight records met the criteria for inclusion. Seven records reported on adult populations, with five records only including post-lingually deaf individuals and two including both pre- and post-lingually deaf individuals. Studies were either longitudinal or cross-sectional, and all studies compared fNIRS measurements with receptive speech outcomes. This review identified and collated key work in this field. The homogeneity of the populations studied so far identifies key gaps for future research, including the use of fNIRS in infants. By mapping the literature on this important topic, this review contributes knowledge towards the improvement of outcomes following cochlear implantation.

Neural Activity During Audiovisual Speech Processing: Protocol For a Functional Neuroimaging Study

“…The available studies show contradictory findings. A recent review states that it is important to discuss the methodological aspects of such functional neuroimaging examinations [ 22 - 26 , 46 , 47 , 50 ]. One problem with measuring functional brain activation is that many variables must be considered.…”

“…A power analysis to test a 2-sided hypothesis at 95% significance and 80% power showed that we need at least 15 participants with normal hearing to detect auditory activations. In addition, we considered previous findings from auditory fNIRS studies [ 26 , 28 , 31 , 32 ]. We compared the size of their study cohorts, the fNIRS systems used, the optode arrangements used, and the reliability of their results.…”

“…According to a recent review on fNIRS measurements in CI patients, at the current stage, it is difficult to draw a general conclusion about the potential positive or negative effects of cortical reorganization. Instead, methodological aspects must first be clarified [ 26 ]. The effect of cross-modal plasticity may be more complex than suggested in previous studies.…”

Brightening the Study of Listening Effort with Functional Near-Infrared Spectroscopy: A Scoping Review

“…Furthermore, fNIRS is simple to implement over multiple testing sessions; so, it is ideal for longitudinal designs and may be an important tool to assess the efficacy of hearing devices over time (e.g., before and after cochlear implantation). 102 Sevy et al 103 were the first group to identify a reliable response to speech in auditory cortex for cochlear implant users. Bisconti et al 104 found overall similar activation patterns in auditory and nonauditory regions between cochlear implant users and normal-hearing adults during passive listening to speech, suggesting that hearing loss in adulthood does not significantly alter the neural organization of speech perception.…”

Neuroplasticity of speech-in-noise processing in older adults assessed by functional near-infrared spectroscopy (fNIRS)

“…As well as the pre-processing, channels with poor signal quality were detected despite the efforts to optimize optode contacts with the scalp. The scalp coupling index (SCI), which can effectively identify poor fNIRS signals in speech perception experiments (Pollonini et al, 2014;Mushtaq et al, 2019Mushtaq et al, , 2021Lawrence et al, 2021), were adopted. The signals with the two wavelengths were first bandpass filtered into 0.5-2.5 Hz that represents the cardiac elements captured by fNIRS and were correlated with each other.…”