Auditory evoked potential response and hearing loss: a review

Clinical Assessment Tools for the Detection of Cognitive Impairment and Hearing Loss in the Ageing Population: A Scoping Review

Objective

There is a strong association between cognitive impairment and hearing loss, both highly prevalent in the ageing population. Early detection of both hearing loss and cognitive impairment is essential in the management of these conditions to ensure effective and informed decisions on healthcare. The main objective was to identify existing and emerging cognitive and auditory assessment tools used in clinical settings (eg, memory clinics, audiology clinics), which manage the ageing population.

Methods

A scoping review of peer-reviewed publications and results were reported according to the PRISMA-ScR guidelines.

Results

A total of 289 articles were selected for data extraction. The majority of studies (76.1%) were conducted in 2017 or later. Tests of global cognitive function (ie, Mini-Mental State Exam, Montreal Cognitive Assessment) were the most commonly used method to detect cognitive impairment in hearing healthcare settings. Behavioral hearing testing (ie, pure-tone audiometry) was the most commonly used method to detect hearing loss in cognitive healthcare settings. Objective, physiological measures were seldom used across disciplines.

Conclusion

Preferences among clinicians for short, accessible tests likely explain the use of tests of global cognitive function and behavioral hearing tests. Rapidly evolving literature has identified inherent limitations of administering global cognitive function tests and pure-tone testing in an ageing population. Using electrophysiological measures as an adjunct to standard methods of assessment may provide more reliable information for clinical recommendations in those with cognitive and hearing impairment, and subsequently achieve better healthcare outcomes.

A multidimensional characterization of the neurocognitive architecture underlying age-related temporal speech processing

Healthy aging is often associated with speech comprehension difficulties in everyday life situations despite a pure-tone hearing threshold in the normative range. Drawing on this background, we used a multidimensional approach to assess the functional and structural neural correlates underlying age-related temporal speech processing while controlling for pure-tone hearing acuity. Accordingly, we combined structural magnetic resonance imaging and electroencephalography, and collected behavioral data while younger and older adults completed a phonetic categorization and discrimination task with consonant-vowel syllables varying along a voice-onset time continuum. The behavioral results confirmed age-related temporal speech processing singularities which were reflected in a shift of the boundary of the psychometric categorization function, with older adults perceiving more syllable characterized by a short voice-onset time as /ta/ compared to younger adults. Furthermore, despite the absence of any between-group differences in phonetic discrimination abilities, older adults demonstrated longer N100/P200 latencies as well as increased P200 amplitudes while processing the consonant-vowel syllables varying in voice-onset time. Finally, older adults also exhibited a divergent anatomical gray matter infrastructure in bilateral auditory-related and frontal brain regions, as manifested in reduced cortical thickness and surface area. Notably, in the younger adults but not in the older adult cohort, cortical surface area in these two gross anatomical clusters correlated with the categorization of consonant-vowel syllables characterized by a short voice-onset time, suggesting the existence of a critical gray matter threshold that is crucial for consistent mapping of phonetic categories varying along the temporal dimension. Taken together, our results highlight the multifaceted dimensions of age-related temporal speech processing characteristics, and pave the way toward a better understanding of the relationships between hearing, speech and the brain in older age.

Frequency and Time Domain Analysis of EEG Based Auditory Evoked Potentials to Detect Binaural Hearing in Noise

Hearing loss is a prevalent health issue that affects individuals worldwide. Binaural hearing refers to the ability to integrate information received simultaneously from both ears, allowing individuals to identify, locate, and separate sound sources. Auditory evoked potentials (AEPs) refer to the electrical responses that are generated within any part of the auditory system in response to auditory stimuli presented externally. Electroencephalography (EEG) is a non-invasive technology used for the monitoring of AEPs. This research aims to investigate the use of audiometric EEGs as an objective method to detect specific features of binaural hearing with frequency and time domain analysis techniques. Thirty-five subjects with normal hearing and a mean age of 27.35 participated in the research. The stimuli used in the current study were designed to investigate the impact of binaural phase shifts of the auditory stimuli in the presence of noise. The frequency domain and time domain analyses provided statistically significant and promising novel findings. The study utilized Blackman windowed 18 ms and 48 ms pure tones as stimuli, embedded in noise maskers, of frequencies 125 Hz, 250 Hz, 500 Hz, 750 Hz, 1000 Hz in homophasic (the same phase in both ears) and antiphasic (180-degree phase difference between the two ears) conditions. The study focuses on the effect of phase reversal of auditory stimuli in noise of the middle latency response (MLR) and late latency response (LLR) regions of the AEPs. The frequency domain analysis revealed a significant difference in the frequency bands of 20 to 25 Hz and 25 to 30 Hz when elicited by antiphasic and homophasic stimuli of 500 Hz for MLRs and 500 Hz and 250 Hz for LLRs. The time domain analysis identified the Na peak of the MLR for 500 Hz, the N1 peak of the LLR for 500 Hz stimuli and the P300 peak of the LLR for 250 Hz as significant potential markers in detecting binaural processing in the brain.

Development of Machine-Learning Models for Tinnitus-Related Distress Classification Using Wavelet-Transformed Auditory Evoked Potential Signals and Clinical Data

Tinnitus is a highly prevalent condition, affecting more than 1 in 7 adults in the EU and causing negative effects on sufferers' quality of life. In this study, we utilised data collected within the "UNITI" project, the largest EU tinnitus-related research programme. Initially, we extracted characteristics from both auditory brainstem response (ABR) and auditory middle latency response (AMLR) signals, which were derived from tinnitus patients. We then combined these features with the patients' clinical data, and integrated them to build machine learning models for the classification of individuals and their ears according to their level of tinnitus-related distress. Several models were developed and tested on different datasets to determine the most relevant features and achieve high performances. Specifically, seven widely used classifiers were utilised on all generated datasets: random forest (RF), linear, radial, and polynomial support vector machines (SVM), naive bayes (NB), neural networks (NN), and linear discriminant analysis (LDA). Results showed that features extracted from the wavelet-scattering transformed AMLR signals were the most informative data. In combination with the 15 LASSO-selected clinical features, the SVM classifier achieved optimal performance with an AUC value, sensitivity, and specificity of 92.53%, 84.84%, and 83.04%, respectively, indicating high discrimination performance between the two groups.

Steady-state auditory motion based potentials evoked by intermittent periodic virtual sound source and the effect of auditory noise on EEG enhancement

Hearing is one of the most important human perception forms, and humans can capture the movement of sound in complex environments. On the basis of this phenomenon, this study explored the possibility of eliciting a steady-state brain response in an intermittent periodic motion sound source. In this study, a novel discrete continuous and orderly change of sound source positions stimulation paradigm was designed based on virtual sound using head-related transfer functions (HRTFs). And then the auditory motion stimulation paradigms with different noise levels were designed by changing the signal-to-noise ratio (SNR). The characteristics of brain response and the effects of different noises on brain response were studied by analyzing electroencephalogram (EEG) signals evoked by the proposed stimulation. Experimental results showed that the proposed paradigm could elicit a novel steady-state auditory evoked potential (AEP), i.e., steady-state motion auditory evoked potential (SSMAEP). And moderate noise could enhance SSMAEP amplitude and corresponding brain connectivity. This study enriches the types of AEPs and provides insights into the mechanism of brain processing of motion sound sources and the impact of noise on brain processing.

Development and Evaluation of Automated Tools for Auditory-Brainstem and Middle-Auditory Evoked Potentials Waves Detection and Annotation

Auditory evoked potentials (AEPs) are brain-derived electrical signals, following an auditory stimulus, utilised to examine any obstructions along the brain neural-pathways and to diagnose hearing impairment. The clinical evaluation of AEPs is based on the measurements of the latencies and amplitudes of waves of interest; hence, their identification is a prerequisite for AEP analysis. This process has proven to be complex, as it requires relevant clinical experience, and the existing software for this purpose has little practical use. The aim of this study was the development of two automated annotation tools for ABR (auditory brainstem response)- and AMLR (auditory middle latency response)-tests. After the acquisition of 1046 raw waveforms, appropriate pre-processing and implementation of a four-stage development process were performed, to define the appropriate logical conditions and steps for each algorithm. The tools' detection and annotation results, regarding the waves of interest, were then compared to the clinicians' manual annotation, achieving match rates of at least 93.86%, 98.51%, and 91.51% respectively, for the three ABR-waves of interest, and 93.21%, 92.25%, 83.35%, and 79.27%, respectively, for the four AMLR-waves. The application of such tools in AEP analysis is expected to assist towards an easier interpretation of these signals.

Electrophysiological differences in distinct hearing threshold level individuals with and without tinnitus distress

Tinnitus is the perception of sound when no actual external noise is present. Tinnitus is highly prevalent, with more than 1 in 7 adults in the EU having tinnitus, and it causes negative effects on quality of life for many individuals. However, there is currently no cure for tinnitus and its pathophysiology and genesis are unknown. Auditory evoked potentials (AEPs) provide a non-invasive means by which the electrical signals evoked by the brain can be recorded, and constitute a useful indicator for the evaluation of auditory disorders such as tinnitus and hearing loss. The present study analyzed a total of 98 auditory middle evoked potential (AMLR) waveforms, a subtype of AEPs, from 49 participants with subjective tinnitus, attempting to identify differences in AMLR parameters between sufferers with and without tinnitus distress. The waveforms were divided into three categories according to the ear's hearing level, and comparisons were made between sufferers in the same hearing level category. The results of the analysis indicated some statistically significant differences in AMLR latencies and amplitudes between the compared groups. Clinical Relevance- Identification of the electro-physiological profile of subjective tinnitus sufferers based on the distress manifested by tinnitus using AMLRs.

A structured ICA-based process for removing auditory evoked potentials

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (EEG), reflect a combination of TMS-induced cortical activity and multi-sensory responses to TMS. The auditory evoked potential (AEP) is a high-amplitude sensory potential-evoked by the "click" sound produced by every TMS pulse-that can dominate the TEP and obscure observation of other neural components. The AEP is peripherally evoked and therefore should not be stimulation site specific. We address the problem of disentangling the peripherally evoked AEP of the TEP from components evoked by cortical stimulation and ask whether removal of AEP enables more accurate isolation of TEP. We hypothesized that isolation of the AEP using Independent Components Analysis (ICA) would reveal features that are stimulation site specific and unique individual features. In order to improve the effectiveness of ICA for removal of AEP from the TEP, and thus more clearly separate the transcranial-evoked and non-specific TMS-modulated potentials, we merged sham and active TMS datasets representing multiple stimulation conditions, removed the resulting AEP component, and evaluated performance across different sham protocols and clinical populations using reduction in Global and Local Mean Field Power (GMFP/LMFP) and cosine similarity analysis. We show that removing AEPs significantly reduced GMFP and LMFP in the post-stimulation TEP (14 to 400 ms), driven by time windows consistent with the N100 and P200 temporal characteristics of AEPs. Cosine similarity analysis supports that removing AEPs reduces TEP similarity between subjects and reduces TEP similarity between stimulation conditions. Similarity is reduced most in a mid-latency window consistent with the N100 time-course, but nevertheless remains high in this time window. Residual TEP in this window has a time-course and topography unique from AEPs, which follow-up exploratory analyses suggest could be a modulation in the alpha band that is not stimulation site specific but is unique to individual subject. We show, using two datasets and two implementations of sham, evidence in cortical topography, TEP time-course, GMFP/LMFP and cosine similarity analyses that this procedure is effective and conservative in removing the AEP from TEP, and may thus better isolate TMS-evoked activity. We show TEP remaining in early, mid and late latencies. The early response is site and subject specific. Later response may be consistent with TMS-modulated alpha activity that is not site specific but is unique to the individual. TEP remaining after removal of AEP is unique and can provide insight into TMS-evoked potentials and other modulated oscillatory dynamics.

The emergence of machine learning in auditory neural impairment: A systematic review

Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (EEG). The electrophysiological behaviour response emanated from EEG auditory evoked potential (AEP) requires highly trained professionals for analysis and interpretation. Reliable automated methods using techniques of machine learning would assist the auditory assessment process for informed treatment and practice. It is thus highly required to develop models that are more efficient and precise by considering the characteristics of brain signals. This study aims to provide a comprehensive review of several state-of-the-art techniques of machine learning that adopt EEG evoked response for the auditory assessment within the last 13 years. Out of 161 initially screened articles, 11 were retained for synthesis. The outcome of the review presented that the Support Vector Machine (SVM) classifier outperformed with over 80% accuracy metric and was recognized as the best suited model within the field of auditory research. This paper discussed the comprehensive iterative properties of the proposed computed algorithms and the feasible future direction in hearing impaired rehabilitation.

Hearing evaluation with ABR in pediatric patients with celiac disease

BACKGROUND/AIMS

Celiac disease (CD) is an autoimmune and genetic disease that is triggered by gluten intolerance. We aimed to investigate whether Celiac disease have any effect on Auditory Brainstem Response (ABR) waves compare to a healthy control group, and present its association with sensorineural hearing loss (SNHL).

MATERIALS AND METHODS

Thirty-eight patients aged 2 to 16 years old were included in the study. The patients had confirmed diagnosis of Celiac disease through duodenal biopsies and transglutaminase Antibody (Ab) (+). The control group consisted of 18 children aged 3 to 17 years old who were all admitted to the pediatric gastroenterology department due to complaints of constipation and transglutaminase Ab (-).All children underwent Auditory-Brain-Stem-Evoked Responses (ABR). The data were gathered using click stimulus at 10/s frequency 90dB HL.

RESULTS

The results of ABR examination did not show any difference between the patient group and control group as regards the latency of the waves I, III, V. No difference was observed between the two groups in the interpeak latecies I-III, I-V and III-V. None of the patients was observed to have clinical hearing loss.

DISCUSSION

The exact pathogenesis of neurological damages observed in Celiac disease is still unknown. Humoral immune mechanisms are the most frequently attributed cause.

CONCLUSION

Although no significant difference was found in hearing values between the study group and healthy control group, there is a need for further research on this subject.

The role and use of event-related potentials in aphasia: A scoping review

Event-related potentials (ERPs) can provide important insights into underlying language processes in both unimpaired and neurologically impaired populations and may be particularly useful in aphasia. This scoping review was conducted to provide a comprehensive summary of how ERPs have been used with people with aphasia (PWA), with the goal of exploring the potential clinical application of ERPs in aphasia assessment and treatment. We identified 117 studies that met inclusionary criteria, reflecting six thematic domains of inquiry that relate to understanding both unimpaired and aphasic language processing and the use of ERPs with PWA. In these studies, a wide variety of ERP components were reported. Inconsistencies in reporting of participant characteristics and study protocols limit our ability to generalize beyond the individual studies and understand implications for clinical applicability. We discuss the potential roles of ERPs in aphasia management and make recommendations for further developing ERPs for clinical utility in PWA.

Neural Mechanisms Underlying Human Auditory Evoked Responses Revealed By Human Neocortical Neurosolver

Auditory evoked fields (AEFs) are commonly studied, yet their underlying neural mechanisms remain poorly understood. Here, we used the biophysical modelling software Human Neocortical Neurosolver (HNN) whose foundation is a canonical neocortical circuit model to interpret the cell and network mechanisms contributing to macroscale AEFs elicited by a simple tone, measured with magnetoencephalography. We found that AEFs can be reproduced by activating the neocortical circuit through a layer specific sequence of feedforward and feedback excitatory synaptic drives, similar to prior simulation of somatosensory evoked responses, supporting the notion that basic structures and activation patterns are preserved across sensory regions. We also applied the modeling framework to develop and test predictions on neural mechanisms underlying AEF differences in the left and right hemispheres, as well as in hemispheres contralateral and ipsilateral to the presentation of the auditory stimulus. We found that increasing the strength of the excitatory synaptic cortical feedback inputs to supragranular layers simulates the commonly observed right hemisphere dominance, while decreasing the input latencies and simultaneously increasing the number of cells contributing to the signal accounted for the contralateral dominance. These results provide a direct link between human data and prior animal studies and lay the foundation for future translational research examining the mechanisms underlying alteration in this fundamental biomarker of auditory processing in healthy cognition and neuropathology.

Auditory agnosia with anosognosia

A 66-year-old right-handed female medical doctor suffered two consecutive cardioembolic strokes, initially affecting the right frontal lobe and the right insula, followed by a lesion in the left temporal lobe. The patient presented with distinctive phenomenology of general auditory agnosia with anosognosia for the deficit. She did not understand verbal requests and her answers to oral questions were fluent but unrelated to the topic. However, she was able to correctly answer written questions, name objects, and fluently describe their purpose, which is characteristic for verbal auditory agnosia. She was also unable to recognise environmental sounds or to recognise and repeat any melody. These inabilities represent environmental sound agnosia and amusia, respectively. Surprisingly, she was not aware of the problem, not asking any questions regarding her symptoms, and avoiding discussing her inability to understand spoken language, which is indicative of anosognosia. The deficits in our patient followed a distinct pattern of recovery. The verbal auditory agnosia was the first to resolve, followed by environmental sound agnosia. Amusia persisted the longest. The patient was clinically assessed from the first day of symptom onset and the evolution of symptoms was video documented. We give a detailed account of the patient's behaviour and provide results of audiological and neuropsychological evaluations. We discuss the anatomy of auditory agnosia and anosognosia relevant to the case. This case study may serve to better understand auditory agnosia in clinical settings. It is important to distinguish auditory agnosia from Wernicke's aphasia, because use of written language may enable normal communication.

Quantification of stroke lesion volume using epidural EEG in a cerebral ischaemic rat model

Precise monitoring of the brain after a stroke is essential for clinical decision making. Due to the non-invasive nature and high temporal resolution of electroencephalography (EEG), it is widely used to evaluate real-time cortical activity. In this study, we investigated the stroke-related EEG biomarkers and developed a predictive model for quantifying the structural brain damage in a focal cerebral ischaemic rat model. We enrolled 31 male Sprague-Dawley rats and randomly assigned them to mild stroke, moderate stroke, severe stroke, and control groups. We induced photothrombotic stroke targeting the right auditory cortex. We then acquired EEG signal responses to sound stimuli (frequency linearly increasing from 8 to 12 kHz with 750 ms duration). Power spectral analysis revealed a significant correlation of the relative powers of alpha, theta, delta, delta/alpha ratio, and (delta + theta)/(alpha + beta) ratio with the stroke lesion volume. The auditory evoked potential analysis revealed a significant association of amplitude and latency with stroke lesion volume. Finally, we developed a multiple regression model combining EEG predictors for quantifying the ischaemic lesion (R2 = 0.938, p value < 0.001). These findings demonstrate the potential application of EEG as a valid modality for monitoring the brain after a stroke.

Deep Learning Convolutional Neural Networks Discriminate Adult ADHD From Healthy Individuals on the Basis of Event-Related Spectral EEG

Attention deficit hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder that affects 5% of the pediatric and adult population worldwide. The diagnosis remains essentially clinical, based on history and exam, with no available biomarkers. In this paper, we describe a convolutional neural network (CNN) with a four-layer architecture combining filtering and pooling, which we train using stacked multi-channel EEG time-frequency decompositions (spectrograms) of electroencephalography data (EEG), particularly of event-related potentials (ERP) from ADHD patients (n = 20) and healthy controls (n = 20) collected during the Flanker Task, with 2800 samples for each group. We treat the data as in audio or image classification approaches, where deep networks have proven successful by exploiting invariances and compositional features in the data. The model reaches a classification accuracy of 88% ± 1.12%, outperforming the Recurrent Neural Network and the Shallow Neural Network used for comparison, and with the key advantage, compared with other machine learning approaches, of avoiding the need for manual selection of EEG spectral or channel features. The event-related spectrograms also provide greater accuracy compared to resting state EEG spectrograms. Finally, through the use of feature visualization techniques such as DeepDream, we show that the main features exciting the CNN nodes are a decreased power in the alpha band and an increased power in the delta-theta band around 100 ms for ADHD patients compared to healthy controls, suggestive of attentional and inhibition deficits, which have been previously suggested as pathophyisiological signatures of ADHD. While confirmation with larger clinical samples is necessary, these results suggest that deep networks may provide a useful tool for the analysis of EEG dynamics even from relatively small datasets, highlighting the potential of this methodology to develop biomarkers of practical clinical utility.

Cortical Auditory Evoked Potentials in 2-Year-Old Subjects

Introduction  Cortical auditory evoked potentials (CAEPs) can be used to evaluate both peripheral and cortical components of auditory function, and contribute to the assessment of functional sensitivity and auditory thresholds, especially in neonates and infants. Auditory evoked potentials reflect auditory maturity and precede the acquisition of more complex auditory and cognitive skills, and are therefore crucial for speech and language development.

Objective  The aim of the present study was to determine the presence, latency and amplitude of CAEP components in response to verbal stimuli in children aged 2 years old.

Methods  The sample consisted of 19 subjects, 10 of whom were male while 9 were female. All of the participants were 24 months old at the time of assessment.

Results  A total of 17 of the participants displayed all components of the CAEP. Additionally, no significant differences were observed between genders or ears in the present sample. The presence of all components of the CAEP in subjects aged 2 years old confirms the existence of a critical period for the maturation of auditory pathways in the first 2 years of life.

Conclusion  In the present study, in addition to the P1/N1 components, it was possible to observe the presence of the CAEP P2/N2 components in individuals aged 24 months, confirming the existence of a critical period for the maturation of the auditory pathways in the first 2 years of life.

Refined Auditory Brainstem Response Measurement Identified Potential Models of Congenital Deafness in Laboratory Mouse Strains

Introduction

To detect congenital hearing loss in mice, an objective measure is needed other than mouse behavioral observation. This study aimed to refine the methodology of auditory brainstem response measurement and identify potential congenital hearing loss models in laboratory mouse strains.

Methods

Mice were anesthetized and fitted with head electrodes. Each mouse underwent four ABR measurements according to four testing conditions: A - no chamber; conventional tone; B - chamber; conventional tone; C - no chamber; short tone; D - chamber; short tone. Potential congenital hearing loss models were identified using 10 mice from each strain (C57BL, BALB/c, CH3, ICR, and ddY) through sound-attenuated ABR measurements with short-tone bursts. Potential congenital hearing loss models exhibited hearing thresholds ≥30 dB in both ears. Data were analyzed for normal distribution and variance homogeneity using the D'Agostino-Pearson/Kolmogorov-Smirnov and F value tests, respectively. One-way analysis of variance (ANOVA), with the Tukey-Kramer test, was used to conduct parametric analysis, and the Kruskal-Wallis/Friedman test, with a Dunn's test for post hoc analysis, was used to perform non-parametric analysis.

Results

The simultaneous use of a sound-attenuating chamber and short-tone bursts provided clearly defined wave patterns, even at lower sound intensities. Inbred strains, especially C57BL/6 sub-strains, constitute suitable congenital hearing loss models.

Conclusions

Our study shows that environmental factors should be addressed in animal studies of hearing function. Potential congenital hearing loss models may be found amongst commercially available inbred strains.

Automated cortical auditory evoked potentials threshold estimation in neonates

Introduction

The evaluation of cortical auditory evoked potential has been the focus of scientific studies in infants. Some authors have reported that automated response detection is effective in exploring these potentials in infants, but few have reported their efficacy in the search for thresholds.

Objective

To analyze the latency, amplitude and thresholds of cortical auditory evoked potential using an automatic response detection device in a neonatal population.

Methods

This is a cross-sectional, observational study. Cortical auditory evoked potentials were recorded in response to pure-tone stimuli of the frequencies 500, 1000, 2000 and 4000 Hz presented in an intensity range between 0 and 80 dB HL using a single channel recording. P1 was performed in an exclusively automated fashion, using Hotelling's T² statistical test. The latency and amplitude were obtained manually by three examiners. The study comprised 39 neonates up to 28 days old of both sexes with presence of otoacoustic emissions and no risk factors for hearing loss.

Results

With the protocol used, cortical auditory evoked potential responses were detected in all subjects at high intensity and thresholds. The mean thresholds were 24.8 ± 10.4 dB NA, 25 ± 9.0 dB NA, 28 ± 7.8 dB NA and 29.4 ± 6.6 dB HL for 500, 1000, 2000 and 4000 Hz, respectively.

Conclusion

Reliable responses were obtained in the assessment of cortical auditory potentials in the neonates assessed with a device for automatic response detection.

Functional near-infrared spectroscopy as a tool for assessing speech and spoken language processing in pediatric and adult cochlear implant users

Much of what is known about the course of auditory learning in following cochlear implantation is based on behavioral indicators that users are able to perceive sound. Both prelingually deafened children and postlingually deafened adults who receive cochlear implants display highly variable speech and language processing outcomes, although the basis for this is poorly understood. To date, measuring neural activity within the auditory cortex of implant recipients of all ages has been challenging, primarily because the use of traditional neuroimaging techniques is limited by the implant itself. Functional near-infrared spectroscopy (fNIRS) is an imaging technology that works with implant users of all ages because it is non-invasive, compatible with implant devices, and not subject to electrical artifacts. Thus, fNIRS can provide insight into processing factors that contribute to variations in spoken language outcomes in implant users, both children and adults. There are important considerations to be made when using fNIRS, particularly with children, to maximize the signal-to-noise ratio and to best identify and interpret cortical responses. This review considers these issues, recent data, and future directions for using fNIRS as a tool to understand spoken language processing in children and adults who hear through a cochlear implant.

Study of brainstem auditory evoked potentials in early diagnosis of congenital toxoplasmosis

INTRODUCTION

Congenital toxoplasmosis is an infectious disease with high prevalence in tropical countries. It is characterized by neurological, ophthalmological and auditory sequelae.

OBJECTIVE

The aim of this study was to evaluate and describe the brainstem auditory evoked potential in infants aged 1-3 months diagnosed with congenital toxoplasmosis and to compare them with infants of the same age group without the infection.

METHODS

This is an observational, analytical and cross-sectional study in which brainstem auditory evoked potential was investigated in infants with congenital toxoplasmosis. The following audiological exams were performed: transient-evoked otoacoustic emissions, clinical and automatic brainstem auditory evoked potential.

RESULTS

100 children participated in the study, but the final sample consisted of 76 children. Of the 37 children with toxoplasmosis included in the study, 28 completed the neurological imaging evaluation, and of these, 3 (10.7%) showed an altered neurological examination. At the brainstem auditory evoked potential assessment, two children without toxoplasmosis and 10 children with congenital toxoplasmosis had results suggestive of alterations in the brainstem auditory pathway maturation.

CONCLUSION

10 (27%) children were identified with a possible unilateral alteration in the electrophysiological assessment. There was a 5-fold higher risk for a child between 1 and 3 months of age with toxoplasmosis to have an altered brainstem auditory evoked potential compared to a child of the same age range without the infection.

Active brainwave pattern generation for brain-to-machine communication

Over the years of research, Electroencephalogram (EEG) signal study has grown to give promising outcomes. A lot of research has been done on implementing brain-computer-interfaces, and the brain-computer interface (BCI) algorithm as well as the study of the effects of different stimuli on brain signals. This paper intends to make progress toward that goal by developing a responsive real-time EEG-based brain-to-machine communication system by generating distinct EEG signals at will and identification of the explicit pattern that they reflect for the presented self-induced internal visual and auditory stimuli. The brain-to-machine communication system delivers the real-time capture, analysis, and visualization of the brain signal patterns that can be used for smart medical applications such as rehabilitation robotic control, smart wheelchair, etc.

Characterization of Volume-Based Changes in Cortical Auditory Evoked Potentials and Prepulse Inhibition

The auditory evoked startle reflex is a conserved response resulting in neurological and motor activity. The presence of a mild prepulse immediately before the main pulse inhibits startle responses, though the mechanism for this remains unknown. In this study, the electroencephalography (EEG) data recorded from 15 subjects was analyzed to study the N1 and P2 components of cortical auditory evoked potentials (CAEPs) evoked by 70, 80, 90, 100, and 110 dB stimuli both in the presence and absence of 70 dB prepulses. Results without a prepulse showed an evolution of N1 amplitudes, increasing with stimulus intensity and showing largely significant differences. Results from prepulse trials only showed noteworthy changes in peak-to-peak amplitude in the 100 dB condition. Prepulse and non-prepulse conditions were then compared using peak amplitudes and theta power. Prepulse conditions significantly decreased the amplitude for both components in the 110 dB condition, i.e., pre-pulse inhibition, but significantly increased the N1 amplitude in the 70 dB condition, i.e., pre-pulse facilitation. Similarly theta band power significantly increased in the 70 dB prepulse condition and significantly decreased in the 110 dB prepulse condition. These results expand the basis of knowledge regarding how CAEPs change and elaborate on their neural function and representation.

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG.

A Comparison of Commercially Available Auditory Brainstem Response Stimuli at a Neurodiagnostic Intensity Level

iChirp-evoked auditory brainstem responses (ABRs) yield a larger wave V amplitude at low intensity levels than traditional broadband click stimuli, providing a reliable estimation of hearing sensitivity. However, advantages of iChirp stimulation at high intensity levels are unknown. We tested to see if high-intensity (i.e., 85 dBnHL) iChirp stimulation results in larger and more reliable ABR waveforms than click. Using the commercially available Intelligent Hearing System SmartEP platform, we recorded ABRs from 43 normal hearing young adults. We report that absolute peak latencies were more variable for iChirp and were ~3 ms longer: the latter of which is simply due to the temporal duration of the signal. Interpeak latencies were slightly shorter for iChirp and were most evident between waves I-V. Interestingly, click responses were easier to identify and peak-to-trough amplitudes for waves I, III and V were significantly larger than iChirp. These differences were not due to residual noise levels. We speculate that high intensity iChirp stimulation reduces neural synchrony and conclude that for retrocochlear evaluations, click stimuli should be used as the standard for ABR neurodiagnostic testing.

Music in Research and Rehabilitation of Disorders of Consciousness: Psychological and Neurophysiological Foundations

According to a prevailing view, the visual system works by dissecting stimuli into primitives, whereas the auditory system processes simple and complex stimuli with their corresponding features in parallel. This makes musical stimulation particularly suitable for patients with disorders of consciousness (DoC), because the processing pathways related to complex stimulus features can be preserved even when those related to simple features are no longer available. An additional factor speaking in favor of musical stimulation in DoC is the low efficiency of visual stimulation due to prevalent maladies of vision or gaze fixation in DoC patients. Hearing disorders, in contrast, are much less frequent in DoC, which allows us to use auditory stimulation at various levels of complexity. The current paper overviews empirical data concerning the four main domains of brain functioning in DoC patients that musical stimulation can address: perception (e.g., pitch, timbre, and harmony), cognition (e.g., musical syntax and meaning), emotions, and motor functions. Music can approach basic levels of patients' self-consciousness, which may even exist when all higher-level cognitions are lost, whereas music induced emotions and rhythmic stimulation can affect the dopaminergic reward-system and activity in the motor system respectively, thus serving as a starting point for rehabilitation.