Functional near-infrared spectroscopy (fNIRS) is an increasingly popular neuroimaging technique that measures cortical hemodynamic activity in a non-invasive and portable fashion. Although the fNIRS community has been successful in disseminating open-source processing tools and a standard file format (SNIRF), reproducible research and sharing of fNIRS data amongst researchers has been hindered by a lack of standards and clarity over how study data should be organized and stored. This problem is not new in neuroimaging, and it became evident years ago with the proliferation of publicly available neuroimaging datasets. To solve this critical issue, the neuroimaging community created the Brain Imaging Data Structure (BIDS) that specifies standards for how datasets should be organized to facilitate sharing and reproducibility of science. Currently, BIDS supports dozens of neuroimaging modalities including MRI, EEG, MEG, PET, and many others. In this paper, we present the extension of BIDS for NIRS data alongside tools that may assist researchers in organizing existing and new data with the goal of promoting public disseminations of fNIRS datasets.

Humans make use of small differences in the timing of sounds at the two ears-interaural time differences (ITDs)-to locate their sources. Despite extensive investigation, however, the neural representation of ITDs in the human brain is contentious, particularly the range of ITDs explicitly represented by dedicated neural detectors. Here, using magneto- and electro-encephalography (MEG and EEG), we demonstrate evidence of a sparse neural representation of ITDs in the human cortex. The magnitude of cortical activity to sounds presented via insert earphones oscillated as a function of increasing ITD-within and beyond auditory cortical regions-and listeners rated the perceptual quality of these sounds according to the same oscillating pattern. This pattern was accurately described by a population of model neurons with preferred ITDs constrained to the narrow, sound -frequency -dependent range evident in other mammalian species. When scaled for head size, the distribution of ITD detectors in the human cortex is remarkably like that recorded in vivo from the cortex of rhesus monkeys, another large primate that uses ITDs for source localization. The data solve a long-standing issue concerning the neural representation of ITDs in humans and suggest a representation that scales for head size and sound frequency in an optimal manner.

In neuroimaging research, efforts to enhance replication and reproducibility have increased the focus on improving transparency, particularly in the complex data analysis processes. We conducted a multi-lab collaborative study involving 38 international teams that analyzed two functional Near-Infrared Spectroscopy (fNIRS) datasets. These teams tested seven group-level and forty individual-level hypotheses, and they submitted detailed reports on their analysis pipelines and testing outcomes. The results showed significant variability in hypothesis testing outcomes due to differences in analytical approaches. There was greater consensus in group-level analyses compared to individual-level analyses. Factors such as the pruning method, hemodynamic response function model and estimation, and statistical analysis space partly account for the variability in hypothesis testing outcomes. Additionally, we have found higher similarity in hypothesis testing outcomes across the researchers who reported higher confidence in their analysis skills. This study underscores the importance of complying with best practices in fNIRS analysis methodologies and the need for standardized analysis protocols to improve reliability and credibility.

Sensory deprivation can lead to cross-modal cortical changes, whereby sensory brain regions deprived of input may be recruited to perform atypical function. Enhanced cross-modal responses to visual stimuli observed in auditory cortex of postlingually deaf cochlear implant (CI) users are hypothesized to reflect increased activation of cortical language regions, but it is unclear if this cross-modal activity is "adaptive" or "mal-adaptive" for speech understanding. To determine if increased activation of language regions is correlated with better speech understanding in CI users, we assessed task-related activation and functional connectivity of auditory and visual cortices to auditory and visual speech and non-speech stimuli in CI users (n = 14) and normal-hearing listeners (n = 17) and used functional near-infrared spectroscopy to measure hemodynamic responses. We used visually presented speech and non-speech to investigate neural processes related to linguistic content and observed that CI users show beneficial cross-modal effects. Specifically, an increase in connectivity between the left auditory and visual cortices-presumed primary sites of cortical language processing-was positively correlated with CI users' abilities to understand speech in background noise. Cross-modal activity in auditory cortex of postlingually deaf CI users may reflect adaptive activity of a distributed, multimodal speech network, recruited to enhance speech understanding.

Significance: Functional near-infrared spectroscopy (fNIRS) is a popular neuroimaging technique with proliferating hardware platforms, analysis approaches, and software tools. There has not been a standardized file format for storing fNIRS data, which has hindered the sharing of data as well as the adoption and development of software tools. Aim: We endeavored to design a file format to facilitate the analysis and sharing of fNIRS data that is flexible enough to meet the community's needs and sufficiently defined to be implemented consistently across various hardware and software platforms. Approach: The shared NIRS format (SNIRF) specification was developed in consultation with the academic and commercial fNIRS community and the Society for functional Near Infrared Spectroscopy. Results: The SNIRF specification defines a format for fNIRS data acquired using continuous wave, frequency domain, time domain, and diffuse correlation spectroscopy devices. Conclusions: We present the SNIRF along with validation software and example datasets. Support for reading and writing SNIRF data has been implemented by major hardware and software platforms, and the format has found widespread use in the fNIRS community. (c) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular neuroimaging technique that measures cortical hemodynamic activity in a non-invasive and portable fashion. Although the fNIRS community has been successful in disseminating several open-source processing tools and a standard file format (SNIRF), the development of reproducible research and sharing of fNIRS data amongst researchers has been hindered by a lack of standards and clarity over how study data should be organized and stored. This problem is not new in neuroimaging (and science in general), and it became evident years ago with the proliferation of publicly available functional magnetic resonance imaging (fMRI) datasets.To solve this critical issue, the neuroimaging community created the Brain Imaging Data Structure (BIDS) that specifies standards for how datasets should be organized to facilitates sharing and reproducibility of science. Since then, BIDS has been extended to dozens of neuroimaging modalities including EEG, MEG, PET and many others.In this paper, we present the extension of BIDS for fNIRS data alongside tools that may assist researchers in formatting existing and new data with the goal of promoting public disseminations of fNIRS datasets.

We investigated the cortical representation of emotional prosody in normal-hearing listeners using functional near-infrared spectroscopy and behavourial assessments. Consistent with previous reports, listeners relied most heavily on F0 cues when recognizing emotion cues; performance was relatively poor—and highly variable between listeners—when only intensity and speech-rate cues were available. Using functional near-infrared spectroscopy (fNIRS) to image cortical activity to speech utterances containing natural and reduced prosodic cues, we found right superior temporal gyrus (STG) to be most sensitive to emotional prosody, but no emotion-specific cortical activations, suggesting that whilst fNIRS might be suited to investigating cortical mechanisms supporting speech processing it is less suited to investigating cortical haemodynamic responses to individual vocal emotions. Manipulating emotional speech to render F0 cues less informative, we found the amplitude of the haemodynamic response in right STG to be significantly correlated with listeners’ abilities to recognise vocal emotions with uninformative F0 cues. Specifically, listeners more able to assign emotions to speech with degraded F0 cues showed lower haemodynamic responses to these degraded signals. This suggests a potential objective measure of behavioural sensitivity to vocal emotions that might benefit neurodiverse populations less sensitive to emotional prosody or hearing-impaired listeners, many of whom rely on listening technologies such as hearing aids and cochlear implants—neither of which restore, and often further degrade, the F0 cues essential to parsing emotional prosody conveyed in speech.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Sounds reach the ears as a mixture of energy generated by different sources. Listeners extract cues that distinguish different sources from one another, including how similar sounds arrive at the two ears, the interaural coherence (IAC). Here, we find listeners cannot reliably distinguish two completely interaurally coherent sounds from a single sound with reduced IAC. Pairs of sounds heard toward the front were readily confused with single sounds with high IAC, whereas those heard to the sides were confused with single sounds with low IAC. Sounds that hold supra-ethological spatial cues are perceived as more diffuse than can be accounted for by their IAC, and this is accounted for by a computational model comprising a restricted, and sound-frequency dependent, distribution of auditory-spatial detectors. We observed elevated cortical hemodynamic responses for sounds with low IAC, suggesting that the ambiguity elicited by sounds with low interaural similarity imposes elevated cortical load.

Sensory deprivation causes structural and functional changes in the human brain. Cochlear implantation delivers immediate reintroduction of auditory sensory information. Previous reports have indicated that over a year is required for the brain to reestablish canonical cortical processing patterns after the reintroduction of auditory stimulation. We utilized functional near-infrared spectroscopy (fNIRS) to investigate brain activity to natural speech stimuli directly after cochlear implantation. We presented 12 cochlear implant recipients, who each had a minimum of 12 months of auditory deprivation, with unilateral auditoryand visual-speech stimuli. Regardless of the side of implantation, canonical responses were elicited primarily on the contralateral side of stimulation as early as 1 h after device activation. These data indicate that auditory pathway connections are sustained during periods of sensory deprivation in adults, and that typical cortical lateralization is observed immediately following the reintroduction of auditory sensory input.

Objective To develop and validate an Australian version of a behavioural test for assessing listening task difficulty at high speech intelligibility levels. Design In the SWIR-Aus test, listeners perform two tasks: identify the last word of each of seven sentences in a list and recall the identified words after each list. First, the test material was developed by creating seven-sentence lists with similar final-word features. Then, for the validation, participant's performance on the SWIR-Aus test was compared when a binary mask noise reduction algorithm was on and off. Study sample All participants in this study had normal hearing thresholds. Nine participants (23.8-56.0 years) participated in the characterisation of the speech material. Another thirteen participants (18.4-59.1 years) participated in a pilot test to determine the SNR to use at the validation stage. Finally, twenty-four new participants (20.0-56.9 years) participated in the validation of the test. Results The results of the validation of the test showed that recall and identification scores were significantly better when the binary mask noise reduction algorithm was on compared to off. Conclusions The SWIR-Aus test was developed using Australian speech material and can be used for assessing task difficulty at high speech intelligibility levels.

OverviewSignificanceMayer waves are spontaneous oscillations in arterial blood pressure that can mask cortical hemodynamic responses associated with neural activity of interest.AimTo characterize the properties of oscillations in the fNIRS signal generated by Mayer waves in a large sample of fNIRS recordings. Further, we aim to determine the impact of short-channel correction for the attenuation of these unwanted signal components.ApproachMayer wave oscillation parameters were extracted from 310 fNIRS measurements using the Fitting Oscillations & One-Over-F (FOOOF) method to compute normative values. The effect of short-channel correction on Mayer wave oscillation power was quantified on 222 measurements. The practical benefit of the short-channel correction approach for reducing Mayer waves and improving response detection was also evaluated on a subgroup of 17 fNIRS measurements collected during a passive auditory speech detection experiment.ResultsMayer-wave oscillations had a mean frequency of 0.108 Hz, bandwidth of 0.04 Hz, and power of 3.5 μM2/Hz. The distribution of oscillation signal power was positively skewed, with some measurements containing large Mayer waves. Short-channel correction significantly reduced the amplitude of these undesired signals; greater attenuation was observed for measurements containing larger Mayer-wave oscillations.ConclusionsA robust method for quantifying Mayer-wave oscillations in the fNIRS signal spectrum was presented and used to provide normative parameterization. Short-channel correction is recommended as an approach for attenuating Mayer waves, particularly in participants with large oscillations.

Continuous-wave functional near-infrared spectroscopy (fNIRS) neuroimaging provides an estimate of relative changes in oxygenated and de-oxygenated hemoglobin content, from which regional neural activity is inferred. The relation between both signals is governed by neurovascular coupling mechanisms. However, the magnitude of concentration changes and the contribution of noise sources to each chromophore is unique. Subsequently, it is not apparent if either chromophore signal practically provides greater information about the underlying neural state and relation to an experimental condition. To assess this question objectively, we applied a machine-learning approach to four datasets and evaluated which hemoglobin signal best differentiated between experimental conditions. To further ensure the objective nature of the analysis, the algorithm utilized all samples from the epoched data rather than pre-selected features. Regardless of experimental task, brain region, or stimulus, the oxygenated hemoglobin signal was better able to differentiate between conditions than the de-oxygenated signal. Incorporating both signals into the analysis provided no additional improvement over oxygenated hemoglobin alone. These results indicate that oxyhemoglobin is the most informative fNIRS signal in relation to experimental condition.

Overview Significance fNIRS is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies complicates interpretation of data. Aim To assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, whether averaging or GLM-based analyses generate different experimental conclusions, when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design was employed, comprising sounds of 5-s duration, and 10–20 s silent intervals. Results Both analysis procedures generated similar response morphologies and amplitude estimates, and both also indicated responses to speech to be significantly greater than to noise and silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

As an alternative to fMRI, functional near-infrared spectroscopy (fNIRS) is a relatively new tool for observing cortical activation. However, spatial resolution is reduced compared to fMRI and often the exact locations of fNIRS optodes and specific anatomical information is not known. The aim of this study was to explore the location and range of specific regions of interest that are sensitive to detecting cortical activation using fNIRS in response to auditory- and visual-only connected speech. Two approaches to a priori region-of-interest selection were explored. First, broad regions corresponding to the auditory cortex and occipital lobe were analysed. Next, the fNIRS Optode Location Decider (fOLD) tool was used to divide the auditory and visual regions into two subregions corresponding to distinct anatomical structures. The Auditory-A and -B regions corresponded to Heschl's gyrus and planum temporale, respectively. The Visual-A region corresponded to the superior occipital gyrus and the cuneus, and the Visual-B region corresponded to the middle occipital gyrus. The experimental stimulus consisted of a connected speech signal segmented into 12.5-sec blocks and was presented in either an auditory-only or visual-only condition. Group-level results for eight normal-hearing adult participants averaged over the broad regions of interest revealed significant auditory-evoked activation for both the left and right broad auditory regions of interest. No significant activity was observed for any other broad region of interest in response to any stimulus condition. When divided into subregions, there was a significant positive auditory-evoked response in the left and right Auditory-A regions, suggesting activation near the primary auditory cortex in response to auditory-only speech. There was a significant positive visual-evoked response in the Visual-B region, suggesting middle occipital gyrus activation in response to visual-only speech. In the Visual-A region, however, there was a significant negative visual-evoked response. This result suggests a significant decrease in oxygenated hemoglobin in the superior occipital gyrus as well as the cuneus in response to visual-only speech. Distinct response characteristics, either positive or negative, in adjacent subregions within the temporal and occipital lobes were fairly consistent on the individual level. Results suggest that temporal regions near Heschl's gyrus may be the most advantageous location in adults for identifying hemodynamic responses to complex auditory speech signals using fNIRS. In the occipital lobe, regions corresponding to the facial processing pathway may prove advantageous for measuring positive responses to visual speech using fNIRS.

The AuditoryStimuli.jl software package provides researchers with a framework to generate real-time audio signals in the Julia programming language. The package is designed for use in auditory research programs, neurofeedback applications, and audio signal processing development. The package is developed on top of the SampledSignals library (Russell, 2016) to provide auditory specific functionality and encourage best practices in real-time audio generation. As such, modules are provided to generate auditory signals, modify these signals, and output the resulting waveforms. The package can be used to generate offline audio signals, but when used as a real-time audio system, it provides safe guards for common mistakes which can cause signal distortions and undesired auditory percepts.

Objectives: Cochlear implants (CIs) restore functional hearing in persons with a severe hearing impairment. Despite being one of the most successful bionic prosthesis, performance with CI (in particular speech understanding in noise) varies considerably across its users. The ability of the auditory pathway to encode temporal envelope modulations (TEMs) and the effect of degenerative processes associated with hearing loss on TEM encoding is assumed to be one of the reasons underlying the large intersubject differences in CI performance. The objective of the present study was to investigate how TEM encoding of the stimulated neural ensembles of human CI recipients is related to speech perception in noise (SPIN). Design: We used electroencephalography as a noninvasive electrophysiological measure to assess TEM encoding in the auditory pathway of CI users by means of the 40-Hz electrically evoked auditory steady state response (EASSR). Nine CI users with a wide range of SPIN outcome were included in the present study. TEM encoding was assessed for each stimulation electrode of each subject and new metrics; the CI neural modulation transmission difference (CIMTD) and the CI neural modulation transmission index (CIMTI) were developed to quantify the amount of variability in TEM encoding across the stimulated neural ensembles of the CI electrode array. Results: EASSR patterns varied across the CI electrode array and subjects. We found a strong correlation ( r = 0.89, p = 0.001) between the SPIN outcomes and the variability in EASSR amplitudes across the array as assessed with CIMTD/CIMTI. Conclusions: The results of the present study show that the 40-Hz EASSR can be used to objectively assess the neural encoding of TEMs in human CI recipients. Overall reduced or largely variable TEM encoding of the neural ensembles across the electrode array, as quantified with the CIMTD/CIMTI, is highly correlated with speech perception in noise outcome with a CI.

A novel approach to multi-microphone acoustic source localisation based on spiking neural networks is presented. We demonstrate that a two microphone system connected to a spiking neural network can be used to localise acoustic sources based purely on inter microphone timing differences, with no need for manually configured delay lines. A two sensor example is provided which includes 1) a front end which converts the acoustic signal to a series of spikes, 2) a hidden layer of spiking neurons, 3) an output layer of spiking neurons which represents the location of the acoustic source. We present details on training the network, and evaluation of its performance in quiet and noisy conditions. The system is trained on two locations, and we show that the lateralisation accuracy is 100% when presented with previously unseen data in quiet conditions. We also demonstrate the network generalises to modulation rates and background noise on which it was not trained.

In this paper we will explore current advances and the future directions of nerve regeneration implants. We will discuss the challenges of developing implants which can be chronically implanted for long-term nerve regeneration and stimulation. We will also discuss the need for developing such implants to be low-power and minimally invasive. We will compare solutions proposed in the literature as well as develop some criteria which we believe will maximize the success of future implant development.

Objectives: Auditory steady state responses (ASSRs) are used in clinical practice for objective hearing assessments. The response is called steady state because it is assumed to be stable over time, and because it is evoked by a stimulus with a certain periodicity, which will lead to discrete frequency components that are stable in amplitude and phase overtime. However, the stimuli commonly used to evoke ASSRs are also known to be able to induce loudness adaptation behaviorally. Researchers and clinicians using ASSRs assume that the response remains stable over time. This study investigates (1) the stability of ASSR amplitudes over time, within one recording, and (2) whether loudness adaptation can be reflected in ASSRs. Design: ASSRs were measured from 14 normal-hearing participants. The ASSRs were evoked by the stimuli that caused the most loudness adaptation in a previous behavioral study, that is, mixed-modulated sinusoids with carrier frequencies of either 500 or 2000 Hz, a modulation frequency of 40 Hz, and a low sensation level of 30 dB SL. For each carrier frequency and participant, 40 repetitions of 92 sec recordings were made. Two types of analyses were used to investigate the ASSR amplitudes over time: with the more traditionally used Fast Fourier Transform and with a novel Kalman filtering approach. Robust correlations between the ASSR amplitudes and behavioral loudness adaptation ratings were also calculated. Results: Overall, ASSR amplitudes were stable. Over all individual recordings, the median change of the amplitudes over time was -0.0001 mu V/s. Based on group analysis, a significant but very weak decrease in amplitude over time was found, with the decrease in amplitude over time around -0.0002 mu V/s. Correlation coefficients between ASSR amplitudes and behavioral loudness adaptation ratings were significant but low to moderate, with r = 0.27 and r = 0.39 for the 500 and 2000 Hz carrier frequency, respectively. Conclusions: The decrease in amplitude of ASSRs over time (92sec) is small. Consequently, it is safe to use ASSRs in clinical practice, and additional correction factors for objective hearing assessments are not needed. Because only small decreases in amplitudes were found, loudness adaptation is probably not reflected by the ASSRs.