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

Abstract

Listening effort is a long-standing area of interest in auditory cognitive neuroscience. Prior research has used multiple techniques to shed light on the neurophysiological mechanisms underlying listening during challenging conditions. Functional near-infrared spectroscopy (fNIRS) is growing in popularity as a tool for cognitive neuroscience research, and its recent advances offer many potential advantages over other neuroimaging modalities for research related to listening effort. This review introduces the basic science of fNIRS and its uses for auditory cognitive neuroscience. We also discuss its application in recently published studies on listening effort and consider future opportunities for studying effortful listening with fNIRS. After reading this article, the learner will know how fNIRS works and summarize its uses for listening effort research. The learner will also be able to apply this knowledge toward generation of future research in this area.

Keywords

fNIRS - listening effort - auditory cognitive neuroscience

Publication History

Article published online:
06 April 2023

• References

• 1 Mattys SL, Davis MH, Bradlow AR, Scott SK. Speech recognition in adverse conditions: a review. Lang Cogn Process 2012; 27 (7–8): 953-978
• 2 McGarrigle R, Munro KJ, Dawes P. et al. Listening effort and fatigue: what exactly are we measuring? A British Society of Audiology Cognition in Hearing Special Interest Group ‘white paper’. Int J Audiol 2014; 53 (07) 433-440
• 3 Ohlenforst B, Zekveld AA, Jansma EP. et al. Effects of hearing impairment and hearing aid amplification on listening effort: a systematic review. Ear Hear 2017; 38 (03) 267-281
• 4 Pichora-Fuller MK, Kramer SE, Eckert MA. et al. Hearing impairment and cognitive energy: the framework for understanding effortful listening (FUEL). Ear Hear 2016; 37 (Suppl. 01) 5S-27S
• 5 Hart SG, Staveland LE. Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv Psychol 1988; 52: 139-183
• 6 Seeman S, Sims R. Comparison of psychophysiological and dual-task measures of listening effort. J Speech Lang Hear Res 2015; 58 (06) 1781-1792
• 7 Johnson J, Xu J, Cox R, Pendergraft P. A comparison of two methods for measuring listening effort as part of an audiologic test battery. Am J Audiol 2015; 24 (03) 419-431
• 8 Koelewijn T, de Kluiver H, Shinn-Cunningham BG, Zekveld AA, Kramer SE. The pupil response reveals increased listening effort when it is difficult to focus attention. Hear Res 2015; 323: 81-90
• 9 Picou EM, Ricketts TA. Increasing motivation changes subjective reports of listening effort and choice of coping strategy. Int J Audiol 2014; 53 (06) 418-426
• 10 Sarampalis A, Kalluri S, Edwards B, Hafter E. Objective measures of listening effort: effects of background noise and noise reduction. J Speech Lang Hear Res 2009; 52 (05) 1230-1240
• 11 Desjardins JL, Doherty KA. The effect of hearing aid noise reduction on listening effort in hearing-impaired adults. Ear Hear 2014; 35 (06) 600-610
• 12 Pichora-Fuller MK, Schneider BA, Daneman M. How young and old adults listen to and remember speech in noise. J Acoust Soc Am 1995; 97 (01) 593-608
• 13 Keidser G, Best V, Freeston K, Boyce A. Cognitive spare capacity: evaluation data and its association with comprehension of dynamic conversations. Front Psychol 2015; 6: 597
• 14 Mishra S, Stenfelt S, Lunner T, Rönnberg J, Rudner M. Cognitive spare capacity in older adults with hearing loss. Front Aging Neurosci 2014; 6: 96
• 15 McCoy SL, Tun PA, Cox LC, Colangelo M, Stewart RA, Wingfield A. Hearing loss and perceptual effort: downstream effects on older adults' memory for speech. Q J Exp Psychol A 2005; 58 (01) 22-33
• 16 Beatty J. Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychol Bull 1982; 91 (02) 276-292
• 17 Zekveld AA, Koelewijn T, Kramer SE. The pupil dilation response to auditory stimuli: current state of knowledge. Trends Hear 2018; 22: 2331216518777174
• 18 Winn MB, Wendt D, Koelewijn T, Kuchinsky SE. Best practices and advice for using pupillometry to measure listening effort: an introduction for those who want to get started. Trends Hear 2018; 22: 2331216518800869
• 19 Kramer SE, Kapteyn TS, Festen JM, Kuik DJ. Assessing aspects of auditory handicap by means of pupil dilatation. Audiology 1997; 36 (03) 155-164
• 20 Winn MB, Edwards JR, Litovsky RY. The impact of auditory spectral resolution on listening effort revealed by pupil dilation. Ear Hear 2015; 36 (04) e153-e165
• 21 Piquado T, Isaacowitz D, Wingfield A. Pupillometry as a measure of cognitive effort in younger and older adults. Psychophysiology 2010; 47 (03) 560-569
• 22 Mackersie CL, Cones H. Subjective and psychophysiological indexes of listening effort in a competing-talker task. J Am Acad Audiol 2011; 22 (02) 113-122
• 23 Mackersie CL, Calderon-Moultrie N. Autonomic nervous system reactivity during speech repetition tasks: heart rate variability and skin conductance. Ear Hear 2016; 37 (Suppl. 01) 118S-125S
• 24 Richter M. The moderating effect of success importance on the relationship between listening demand and listening effort. Ear Hear 2016; 37 (Suppl. 01) 111S-117S
• 25 Francis AL, MacPherson MK, Chandrasekaran B, Alvar AM. Autonomic nervous system responses during perception of masked speech may reflect constructs other than subjective listening effort. Front Psychol 2016; 7: 263
• 26 Bess FH, Gustafson SJ, Corbett BA, Lambert EW, Camarata SM, Hornsby BWY. Salivary cortisol profiles of children with hearing loss. Ear Hear 2016; 37 (03) 334-344
• 27 Kramer SE, Teunissen CE, Zekveld AA. Cortisol, chromogranin A, and pupillary responses evoked by speech recognition tasks in normally hearing and hard-of-hearing listeners: a pilot study. Ear Hear 2016; 37 (Suppl. 01) 126S-135S
• 28 Davis MH, Johnsrude IS. Hierarchical processing in spoken language comprehension. J Neurosci 2003; 23 (08) 3423-3431
• 29 Peelle JE, Johnsrude IS, Davis MH. Hierarchical processing for speech in human auditory cortex and beyond. Front Hum Neurosci 2010; 4: 51
• 30 Rodd JM, Longe OA, Randall B, Tyler LK. The functional organisation of the fronto-temporal language system: evidence from syntactic and semantic ambiguity. Neuropsychologia 2010; 48 (05) 1324-1335
• 31 Peelle JE. Listening effort: how the cognitive consequences of acoustic challenge are reflected in brain and behavior. Ear Hear 2018; 39 (02) 204-214
• 32 Sadaghiani S, D'Esposito M. Functional characterization of the cingulo-opercular network in the maintenance of tonic alertness. Cereb Cortex 2015; 25 (09) 2763-2773
• 33 Vaden Jr KI, Kuchinsky SE, Cute SL, Ahlstrom JB, Dubno JR, Eckert MA. The cingulo-opercular network provides word-recognition benefit. J Neurosci 2013; 33 (48) 18979-18986
• 34 Vaden Jr KI, Kuchinsky SE, Ahlstrom JB, Dubno JR, Eckert MA. Cortical activity predicts which older adults recognize speech in noise and when. J Neurosci 2015; 35 (09) 3929-3937
• 35 Botvinick MM, Cohen JD, Carter CS. Conflict monitoring and anterior cingulate cortex: an update. Trends Cogn Sci 2004; 8 (12) 539-546
• 36 Eckert MA, Teubner-Rhodes S, Vaden Jr KI. Is listening in noise worth it? The neurobiology of speech recognition in challenging listening conditions. Ear Hear 2016; 37, Suppl 1 (Suppl. 01) 101S-110S
• 37 Obleser J, Weisz N. Suppressed alpha oscillations predict intelligibility of speech and its acoustic details. Cereb Cortex 2012; 22 (11) 2466-2477
• 38 Obleser J, Wöstmann M, Hellbernd N, Wilsch A, Maess B. Adverse listening conditions and memory load drive a common α oscillatory network. J Neurosci 2012; 32 (36) 12376-12383
• 39 McMahon CM, Boisvert I, de Lissa P. et al. Monitoring alpha oscillations and pupil dilation across a performance-intensity function. Front Psychol 2016; 7: 745
• 40 Dimitrijevic A, Smith ML, Kadis DS, Moore DR. Neural indices of listening effort in noisy environments. Sci Rep 2019; 9 (01) 11278
• 41 Paul BT, Chen J, Le T, Lin V, Dimitrijevic A. Cortical alpha oscillations in cochlear implant users reflect subjective listening effort during speech-in-noise perception. PLoS One 2021; 16 (07) e0254162
• 42 Doelling KB, Arnal LH, Ghitza O, Poeppel D. Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing. Neuroimage 2014; 85 (0 2): 761-768
• 43 Etard O, Reichenbach T. Neural speech tracking in the theta and in the delta frequency band differentially encode clarity and comprehension of speech in noise. J Neurosci 2019; 39 (29) 5750-5759
• 44 Wisniewski MG. Indices of effortful listening can be mined from existing electroencephalographic data. Ear Hear 2017; 38 (01) e69-e73
• 45 Peelle JE, Gross J, Davis MH. Phase-locked responses to speech in human auditory cortex are enhanced during comprehension. Cereb Cortex 2013; 23 (06) 1378-1387
• 46 Obleser J, Kotz SA. Multiple brain signatures of integration in the comprehension of degraded speech. Neuroimage 2011; 55 (02) 713-723
• 47 Song J, Iverson P. Listening effort during speech perception enhances auditory and lexical processing for non-native listeners and accents. Cognition 2018; 179: 163-170
• 48 Kuchinsky SE, Vaden KI. Aging, hearing loss, and listening effort: imaging studies of the aging listener. In: Helfer KS, Bartlett EL, Popper AN, Fay RR, eds. Aging and Hearing, Springer Handbook of Auditory Research. Springer; 2020. 72. 231-256
• 49 Wu Y-H, Aksan N, Rizzo M, Stangl E, Zhang X, Bentler R. Measuring listening effort: driving simulator versus simple dual-task paradigm. Ear Hear 2014; 35 (06) 623-632
• 50 Kuruvilla-Mathew A, Purdy SC, Welch D. Cortical encoding of speech acoustics: effects of noise and amplification. Int J Audiol 2015; 54 (11) 852-864
• 51 Pinti P, Tachtsidis I, Hamilton A. et al. The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Ann N Y Acad Sci 2020; 1464 (01) 5-29
• 52 Sfareni R, Boffi A, Quaresima V, Ferrari M. Near infrared absorption spectra of human deoxy- and oxyhaemoglobin in the temperature range 20-40 degrees C. Biochim Biophys Acta 1997; 1340 (02) 165-169
• 53 Wray S, Cope M, Delpy DT, Wyatt JS, Reynolds EO. Characterization of the near infrared absorption spectra of cytochrome aa3 and haemoglobin for the non-invasive monitoring of cerebral oxygenation. Biochim Biophys Acta 1988; 933 (01) 184-192
• 54 Quaresima V, Bisconti S, Ferrari M. A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults. Brain Lang 2012; 121 (02) 79-89
• 55 Liang L-Y, Shewokis PA, Getchell N. Brain activation in the prefrontal cortex during motor and cognitive tasks in adults. J Behav Brain Sci 2016; 06 (12) 463-474
• 56 Pinti P, Scholkmann F, Hamilton A, Burgess P, Tachtsidis I. Current status and issues regarding pre-processing of fNIRS neuroimaging data: an investigation of diverse signal filtering methods within a general linear model framework. Front Hum Neurosci 2019; 12: 505
• 57 Zhang Y, Zhu C. Assessing brain networks by resting-state dynamic functional connectivity: an fNIRS-EEG study. Front Neurosci 2020; 13: 1430
• 58 Hu Z, Liu G, Dong Q, Niu H. Applications of resting-state fNIRS in the developing brain: a review from the connectome perspective. Front Neurosci 2020; 14: 476
• 59 Zhang X, Noah JA, Dravida S, Hirsch J. Optimization of wavelet coherence analysis as a measure of neural synchrony during hyperscanning using functional near-infrared spectroscopy. Neurophotonics 2020; 7 (01) 015010
• 60 Hoshi Y, Tamura M. Dynamic multichannel near-infrared optical imaging of human brain activity. J Appl Physiol 1993; 75 (04) 1842-1846
• 61 Villringer A, Planck J, Hock C, Schleinkofer L, Dirnagl U. Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults. Neurosci Lett 1993; 154 (1-2): 101-104
• 62 Kato T, Kamei A, Takashima S, Ozaki T. Human visual cortical function during photic stimulation monitoring by means of near-infrared spectroscopy. J Cereb Blood Flow Metab 1993; 13 (03) 516-520
• 63 Meek JH, Elwell CE, Khan MJ. et al. Regional changes in cerebral haemodynamics as a result of a visual stimulus measured by near infrared spectroscopy. Proc Biol Sci 1995; 261 (1362): 351-356
• 64 Villringer A, Chance B. Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci 1997; 20 (10) 435-442
• 65 Watanabe E, Yamashita Y, Maki A, Ito Y, Koizumi H. Non-invasive functional mapping with multi-channel near infra-red spectroscopic topography in humans. Neurosci Lett 1996; 205 (01) 41-44
• 66 Miyai I, Tanabe HC, Sase I. et al. Cortical mapping of gait in humans: a near-infrared spectroscopic topography study. Neuroimage 2001; 14 (05) 1186-1192
• 67 Ferrari M, Quaresima V. A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage 2012; 63 (02) 921-935
• 68 Scholkmann F, Kleiser S, Metz AJ. et al. A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage 2014; 85 (Pt 1): 6-27
• 69 Zhao H, Cooper RJ. Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system. Neurophotonics 2018; 5 (01) 011012
• 70 Pinti P, Aichelburg C, Gilbert S. et al. A review on the use of wearable functional near-infrared spectroscopy in naturalistic environments. Jpn Psychol Res 2018; 60 (04) 347-373
• 71 Wheelock MD, Culver JP, Eggebrecht AT. High-density diffuse optical tomography for imaging human brain function. Rev Sci Instrum 2019; 90 (05) 051101
• 72 Frijia EM, Billing A, Lloyd-Fox S. et al. Functional imaging of the developing brain with wearable high-density diffuse optical tomography: a new benchmark for infant neuroimaging outside the scanner environment. Neuroimage 2021; 225: 117490
• 73 Peelle JE. Methodological challenges and solutions in auditory functional magnetic resonance imaging. Front Neurosci 2014; 8: 253
• 74 Rovetti J, Goy H, Nurgitz R, Russo FA. Comparing verbal working memory load in auditory and visual modalities using functional near-infrared spectroscopy. Behav Brain Res 2021; 402: 113102
• 75 Schumacher EH, Lauber E, Awh E, Jonides J, Smith EE, Koeppe RA. PET evidence for an amodal verbal working memory system. Neuroimage 1996; 3 (02) 79-88
• 76 Crottaz-Herbette S, Anagnoson RT, Menon V. Modality effects in verbal working memory: differential prefrontal and parietal responses to auditory and visual stimuli. Neuroimage 2004; 21 (01) 340-351
• 77 Rodriguez-Jimenez R, Avila C, Garcia-Navarro C. et al. Differential dorsolateral prefrontal cortex activation during a verbal n-back task according to sensory modality. Behav Brain Res 2009; 205 (01) 299-302
• 78 Toronov V, Walker S, Gupta R. et al. The roles of changes in deoxyhemoglobin concentration and regional cerebral blood volume in the fMRI BOLD signal. Neuroimage 2003; 19 (04) 1521-1531
• 79 Huppert TJ, Hoge RD, Diamond SG, Franceschini MA, Boas DA. A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. Neuroimage 2006; 29 (02) 368-382
• 80 Ogawa S, Menon RS, Tank DW. et al. Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophys J 1993; 64 (03) 803-812
• 81 Kim SG, Richter W, Uğurbil K. Limitations of temporal resolution in functional MRI. Magn Reson Med 1997; 37 (04) 631-636
• 82 Harrison SC, Hartley DE. Shedding light on the human auditory cortex: a review of the advances in near infrared spectroscopy (NIRS). Rep Med Ins. 2019; 12: 31-42
• 83 Hebden JC, Cooper RJ, Gibson A, Everdell N, Austin T. Simultaneous EEG and diffuse optical imaging of seizure-related hemodynamic activity in the newborn infant brain. In: Popp J, Drexler W, Tuchin VV, Matthews DL, eds. Proceedings of SPIE. Published online June 1, 2012
• 84 Leamy DJ, Ward TE. A novel co-locational and concurrent fNIRS/EEG measurement system: design and initial results. Annu Int Conf IEEE Eng Med Biol Soc 2010; 2010: 4230-4233
• 85 Habermehl C, Holtze S, Steinbrink J. et al. Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography. Neuroimage 2012; 59 (04) 3201-3211
• 86 Toronov V, Webb A, Choi JH. et al. Investigation of human brain hemodynamics by simultaneous near-infrared spectroscopy and functional magnetic resonance imaging. Med Phys 2001; 28 (04) 521-527
• 87 Zhang X, Toronov VY, Fabiani M, Gratton G, Webb AG. The study of cerebral hemodynamic and neuronal response to visual stimulation using simultaneous NIR optical tomography and BOLD fMRI in humans. Proc SPIE Int Soc Opt Eng 2005; 5686 (115) 566-572
• 88 Seki Y, Miyashita T, Kandori A, Maki A, Koizumi H. Simultaneous measurement of neuronal activity and cortical hemodynamics by unshielded magnetoencephalography and near-infrared spectroscopy. J Biomed Opt 2012; 17 (10) 107001
• 89 Steinmetzger K, Shen Z, Riedel H, Rupp A. Auditory cortex activity measured using functional near-infrared spectroscopy (fNIRS) appears to be susceptible to masking by cortical blood stealing. Hear Res 2020; 396: 108069
• 90 Pringle J, Roberts C, Kohl M, Lekeux P. Near infrared spectroscopy in large animals: optical path length and influence of hair covering and epidermal pigmentation. Vet J 1999; 158 (01) 48-52
• 91 Wassenaar EB, Van den Brand JGH. Reliability of near-infrared spectroscopy in people with dark skin pigmentation. J Clin Monit Comput 2005; 19 (03) 195-199
• 92 Couch L, Roskosky M, Freedman BA, Shuler MS. Effect of skin pigmentation on near infrared spectroscopy. Am J Anal Chem 2015; 06 (12) 911-916
• 93 Papasideris M, Ayaz H, Hall PA. Medial prefrontal brain activity correlates with emerging symptoms of anxiety and depression in late adolescence: a fNIRS study. Dev Psychobiol 2021; 63 (07) e22199
• 94 Ohnishi M, Kusakawa N, Masaki S. et al. Measurement of hemodynamics of auditory cortex using magnetoencephalography and near infrared spectroscopy. Acta Otolaryngol Suppl 1997; 532: 129-131
• 95 Sakatani K, Chen S, Lichty W, Zuo H, Wang YP. Cerebral blood oxygenation changes induced by auditory stimulation in newborn infants measured by near infrared spectroscopy. Early Hum Dev 1999; 55 (03) 229-236
• 96 Zaramella P, Freato F, Amigoni A. et al. Brain auditory activation measured by near-infrared spectroscopy (NIRS) in neonates. Pediatr Res 2001; 49 (02) 213-219
• 97 Blasi A, Lloyd-Fox S, Johnson MH, Elwell C. Test-retest reliability of functional near infrared spectroscopy in infants. Neurophotonics 2014; 1 (02) 025005
• 98 Hong K-S, Santosa H. Decoding four different sound-categories in the auditory cortex using functional near-infrared spectroscopy. Hear Res 2016; 333: 157-166
• 99 Yoo S-H, Santosa H, Kim C-S, Hong K-S. Decoding multiple sound-categories in the auditory cortex by neural networks: an fNIRS study. Front Hum Neurosci 2021; 15: 636191
• 100 Oghalai JS. Functional neuroimaging of speech perception in cochlear implant recipients. Volta Review 2017; 116 (01) 95-102
• 101 Bortfeld H. Functional near-infrared spectroscopy as a tool for assessing speech and spoken language processing in pediatric and adult cochlear implant users. Dev Psychobiol 2019; 61 (03) 430-443
• 102 Harrison SC, Lawrence R, Hoare DJ, Wiggins IM, Hartley DEH. Use of functional near-infrared spectroscopy to predict and measure cochlear implant outcomes: a scoping review. Brain Sci 2021; 11 (11) 1439
• 103 Sevy ABG, Bortfeld H, Huppert TJ, Beauchamp MS, Tonini RE, Oghalai JS. Neuroimaging with near-infrared spectroscopy demonstrates speech-evoked activity in the auditory cortex of deaf children following cochlear implantation. Hear Res 2010; 270 (1-2): 39-47
• 104 Bisconti S, Shulkin M, Hu X, Basura GJ, Kileny PR, Kovelman I. Functional near-infrared spectroscopy brain imaging investigation of phonological awareness and passage comprehension abilities in adult recipients of cochlear implants. J Speech Lang Hear Res 2016; 59 (02) 239-253
• 105 Olds C, Pollonini L, Abaya H. et al. Cortical activation patterns correlate with speech understanding after cochlear implantation. Ear Hear 2016; 37 (03) e160-e172
• 106 Zhou X, Seghouane A-K, Shah A. et al. Cortical speech processing in postlingually deaf adult cochlear implant users, as revealed by functional near-infrared spectroscopy. Trends Hear 2018; 22: 2331216518786850
• 107 Sherafati A, Dwyer N, Bajracharya A. et al. Dorsolateral prefrontal cortex supports speech perception in listeners with cochlear implants. bioRxiv (Preprint posted online October 16, 2021)
• 108 Rovetti J, Goy H, Pichora-Fuller MK, Russo FA. Functional near-infrared spectroscopy as a measure of listening effort in older adults who use hearing aids. Trends Hear 2019; 23: 2331216519886722
• 109 Bell L, Peng ZE, Pausch F. et al. fNIRS assessment of speech comprehension in children with normal hearing and children with hearing aids in virtual acoustic environments: pilot data and practical recommendations. Children (Basel) 2020; 7 (11) 219
• 110 Dewey RS, Hartley DEH. Cortical cross-modal plasticity following deafness measured using functional near-infrared spectroscopy. Hear Res 2015; 325: 55-63
• 111 Anderson CA, Lazard DS, Hartley DEH. Plasticity in bilateral superior temporal cortex: effects of deafness and cochlear implantation on auditory and visual speech processing. Hear Res 2017; 343: 138-149
• 112 Chen L-C, Sandmann P, Thorne JD, Bleichner MG, Debener S. Cross-modal functional reorganization of visual and auditory cortex in adult cochlear implant users identified with fNIRS. Neural Plast 2016; 2016: 4382656
• 113 Chen L-C, Stropahl M, Schönwiesner M, Debener S. Enhanced visual adaptation in cochlear implant users revealed by concurrent EEG-fNIRS. Neuroimage 2017; 146: 600-608
• 114 Anderson CA, Wiggins IM, Kitterick PT, Hartley DEH. Adaptive benefit of cross-modal plasticity following cochlear implantation in deaf adults. Proc Natl Acad Sci U S A 2017; 114 (38) 10256-10261
• 115 Anderson CA, Wiggins IM, Kitterick PT, Hartley DEH. Pre-operative brain imaging using functional near-infrared spectroscopy helps predict cochlear implant outcome in deaf adults. J Assoc Res Otolaryngol 2019; 20 (05) 511-528
• 116 Mushtaq F, Wiggins IM, Kitterick PT, Anderson CA, Hartley DEH. The benefit of cross-modal reorganization on speech perception in pediatric cochlear implant recipients revealed using functional near-infrared spectroscopy. Front Hum Neurosci 2020; 14: 308
• 117 Pollonini L, Olds C, Abaya H, Bortfeld H, Beauchamp MS, Oghalai JS. Auditory cortex activation to natural speech and simulated cochlear implant speech measured with functional near-infrared spectroscopy. Hear Res 2014; 309: 84-93
• 118 Vannasing P, Florea O, González-Frankenberger B. et al. Distinct hemispheric specializations for native and non-native languages in one-day-old newborns identified by fNIRS. Neuropsychologia 2016; 84: 63-69
• 119 Giordano V, Alexopoulos J, Spagna A. et al. Accent discrimination abilities during the first days of life: an fNIRS study. Brain Lang 2021; 223: 105039
• 120 van de Rijt LPH, van Opstal AJ, Mylanus EAM. et al. Temporal cortex activation to audiovisual speech in normal-hearing and cochlear implant users measured with functional near-infrared spectroscopy. Front Hum Neurosci 2016; 10: 48
• 121 Altvater-Mackensen N, Grossmann T. The role of left inferior frontal cortex during audiovisual speech perception in infants. Neuroimage 2016; 133: 14-20
• 122 Shader MJ, Luke R, Gouailhardou N, McKay CM. The use of broad vs restricted regions of interest in functional near-infrared spectroscopy for measuring cortical activation to auditory-only and visual-only speech. Hear Res 2021; 406: 108256
• 123 Santosa H, Hong MJ, Hong K-S. Lateralization of music processing with noises in the auditory cortex: an fNIRS study. Front Behav Neurosci 2014; 8: 418
• 124 Bigliassi M, León-Domínguez U, Altimari LR. How does the prefrontal cortex “listen” to classical and techno music? A functional near-infrared spectroscopy (fNIRS) study. Psychol Neurosci 2015; 8 (02) 246-256
• 125 Bicciato G, Keller E, Wolf M. et al. Increase in low-frequency oscillations in fNIRS as cerebral response to auditory stimulation with familiar music. Brain Sci 2021; 12 (01) 42
• 126 Ferreri L, Aucouturier J-J, Muthalib M, Bigand E, Bugaiska A. Music improves verbal memory encoding while decreasing prefrontal cortex activity: an fNIRS study. Front Hum Neurosci 2013; 7: 779
• 127 Ferreri L, Bigand E, Perrey S, Muthalib M, Bard P, Bugaiska A. Less effort, better results: how does music act on prefrontal cortex in older adults during verbal encoding? An fNIRS study. Front Hum Neurosci 2014; 8: 301
• 128 Ferreri L, Bigand E, Bard P, Bugaiska A. The influence of music on prefrontal cortex during episodic encoding and retrieval of verbal information: a multichannel fNIRS study. Behav Neurol 2015; 2015: 707625
• 129 Plichta MM, Gerdes ABM, Alpers GW. et al. Auditory cortex activation is modulated by emotion: a functional near-infrared spectroscopy (fNIRS) study. Neuroimage 2011; 55 (03) 1200-1207
• 130 Gruber T, Debracque C, Ceravolo L. et al. Human discrimination and categorization of emotions in voices: a functional near-infrared spectroscopy (fNIRS) study. Front Neurosci 2020; 14: 570
• 131 Zhang D, Zhou Y, Yuan J. Speech prosodies of different emotional categories activate different brain regions in adult cortex: an fNIRS study. Sci Rep 2018; 8 (01) 218
• 132 Zhang D, Zhou Y, Hou X, Cui Y, Zhou C. Discrimination of emotional prosodies in human neonates: a pilot fNIRS study. Neurosci Lett 2017; 658: 62-66
• 133 Hirsch J. An fNIRS Approach to Two-person Neuroscience. Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN). Published online 2020.
• 134 Hirsch J, Adam Noah J, Zhang X, Dravida S, Ono Y. A cross-brain neural mechanism for human-to-human verbal communication. Soc Cogn Affect Neurosci 2018; 13 (09) 907-920
• 135 Ono Y, Zhang X, Noah JA, Dravida S, Hirsch J. Bidirectional connectivity between Broca's area and Wernicke's area during interactive verbal communication. Brain Connect 2022; 12 (03) 210-222
• 136 Wijayasiri P, Hartley DEH, Wiggins IM. Brain activity underlying the recovery of meaning from degraded speech: a functional near-infrared spectroscopy (fNIRS) study. Hear Res 2017; 351: 55-67
• 137 Shannon RV, Zeng F-G, Kamath V, Wygonski J, Ekelid M. Speech recognition with primarily temporal cues. Science 1995; 270 (5234): 303-304
• 138 Wild CJ, Yusuf A, Wilson DE, Peelle JE, Davis MH, Johnsrude IS. Effortful listening: the processing of degraded speech depends critically on attention. J Neurosci 2012; 32 (40) 14010-14021
• 139 Lawrence RJ, Wiggins IM, Anderson CA, Davies-Thompson J, Hartley DEH. Cortical correlates of speech intelligibility measured using functional near-infrared spectroscopy (fNIRS). Hear Res 2018; 370: 53-64
• 140 Lawrence RJ, Wiggins IM, Hodgson JC, Hartley DEH. Evaluating cortical responses to speech in children: a functional near-infrared spectroscopy (fNIRS) study. Hear Res 2021; 401: 108155
• 141 Mushtaq F, Wiggins IM, Kitterick PT, Anderson CA, Hartley DEH. Investigating cortical responses to noise-vocoded speech in children with normal hearing using functional near-infrared spectroscopy (fNIRS). J Assoc Res Otolaryngol 2021; 22 (06) 703-717
• 142 Defenderfer J, Kerr-German A, Hedrick M, Buss AT. Investigating the role of temporal lobe activation in speech perception accuracy with normal hearing adults: an event-related fNIRS study. Neuropsychologia 2017; 106: 31-41
• 143 Defenderfer J, Forbes S, Wijeakumar S, Hedrick M, Plyler P, Buss AT. Frontotemporal activation differs between perception of simulated cochlear implant speech and speech in background noise: an image-based fNIRS study. Neuroimage 2021; 240: 118385
• 144 Rowland SC, Hartley DEH, Wiggins IM. Listening in naturalistic scenes: What can functional near-infrared spectroscopy and intersubject correlation analysis tell us about the underlying brain activity?. Trends Hear 2018; 22: 2331216518804116
• 145 Rovetti J, Goy H, Zara M, Russo FA. Reduced semantic context and signal-to-noise ratio increase listening effort as measured using functional near-infrared spectroscopy. Ear Hear 2022; 43 (03) 836-848
• 146 White BE, Langdon C. The cortical organization of listening effort: new insight from functional near-infrared spectroscopy. Neuroimage 2021; 240: 118324
• 147 Corbetta M, Patel G, Shulman GL. The reorienting system of the human brain: from environment to theory of mind. Neuron 2008; 58 (03) 306-324
• 148 Vossel S, Geng JJ, Fink GR. Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist 2014; 20 (02) 150-159
• 149 Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 2002; 3 (03) 201-215
• 150 Hickok G, Poeppel D. The cortical organization of speech processing. Nat Rev Neurosci 2007; 8 (05) 393-402
• 151 Strand JF, Ray L, Dillman-Hasso NH, Villanueva J, Brown VA. Understanding speech amid the jingle and jangle: recommendations for improving measurement practices in listening effort research. Audit Percept Cogn 2020; 3 (04) 169-188
• 152 Botvinik-Nezer R, Holzmeister F, Camerer CF. et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020; 582 (7810): 84-88