Neural Correlates of Binaural Interaction Using Aggregate-System Stimulation in Cochlear Implantees

The importance of binaural cues in auditory stream formation and sound source differentiation is widely accepted. When treating one ear with a cochlear implant (CI) the peripheral auditory system gets partially replaced and processing delays get added potentially, thus important interaural time encoding gets altered. This is a crucial problem because factors like the interaural time delay between the receiving ears are known to be responsible for facilitating such cues, e.g., sound source localization and separation. However, these effects are not fully understood, leaving a lack of systematic binaural fitting strategies with respect to an optimal binaural fusion. To gain new insights into such alterations, we suggest a novel method of free-field evoked auditory brainstem response (ABR) analysis in CI users. As a result, this method does not bypass the technically induced intrinsic delays of the hearing device while leaving the complete electrode array active, thus the most natural way of stimulation is provided and the comparable testing of real world stimuli gets facilitated. Unfortunately, ABRs acquired in CI users are additionally affected by the prominent artifact caused by their electrical stimulation, which severely distorts the desired neural response, thus challenging their analysis. To circumvent this problem, we further introduce a novel narrowband filtering CI artifact removal technique capable of obtaining neural correlates of ABRs in CI users. Consequently, we were able to compare brainstem-level responses collected of 12 CI users and 12 normal hearing listeners using two different stimuli (i.e., chirp and click) at four different intensities each, what comprises an adaption of the prominent brainstem evoked response audiometry serving as an additional evaluation criterion. We analyzed the responses using the average of 2,000 trials in combination with synchronized regularizations across them and found consistent results in their deflections and latencies, as well as in single trial relationships between both groups. This method provides a novel and unique perspective into the natural CI users’ brainstem-level responses and can be practical in future research regarding binaural interaction and fusion. Furthermore, the binaural interaction component (BIC), i.e., the arithmetical difference between the sum of both monaurally evoked ABRs and the binaurally evoked ABR, has been previously shown to be an objective indicator for binaural interaction. This component is unfortunately known to be rather fragile and as a result, a reliable, objective measure of binaural interaction in CI users does not exist to the present date. It is most likely that implantees would benefit from a reliable analysis of brainstem-level and subsequent higher-level binaural interaction, since this could objectively support fitting strategies with respect to a maximization of interaural integration. Therefore, we introduce a novel method capable of obtaining neural correlates of binaural interaction in bimodal CI users by combining recent advances in the field of fast, deconvolution-based ABR acquisitions with the introduced narrowband filtering technique. The proposed method shows a significant improvement in the magnitude of resulting BICs in 10 bimodal CI users and a control-group of 10 normal hearing subjects when compensating the interaural latency difference caused by the technical devices. In total, both proposed studies objectively demonstrate technical-driven interaural latency mismatches. Thus, they strongly emphasize potential benefits when balancing these interaural delays to improve binaural processing by significant increases in associated neural correlates of successful binaural interaction. These results and also the estimated latency differences should be investigated in larger group sizes to further consolidate the results, but confirm the demand for rather binaural solutions than treating hearing losses in an isolated monaural manner.Zusammenfassung Die Notwendigkeit binauraler Verarbeitungsprozesse in der auditorischen Wahrnehmung ist weitestgehend akzeptiert. Bei der Therapie eines Ohres mit einem Cochlea-Implantat (engl. cochlear implant (CI)) wird das periphere auditorische System teilweise ersetzt und verändert, sodass natürliche, interaurale Zeitauflösungen beeinflusst werden. Dieses Problem ist entscheidend, denn Faktoren wie interaurale Laufzeitunterschiede zwischen den aufnehmenden Ohren sind verantwortlich für die Umsetzung der erwähnten binauralen Verarbeitungsprozesse, z.B. Schallquellenlokalisation und -separation. Allerdings sind diese Effekte nicht ausreichend verstanden, weshalb bis heute binaurale Anpassstrategien mit Rücksicht auf eine optimale Fusionierung fehlen. Um neue Einsichten in solche zeitlichen Verzerrungen zu erhalten, schlagen wir ein neues Verfahren der Freifeld evozierten auditorischen Hirnstammpotentiale (engl. auditory brainstem response (ABR)) in CI-Nutzern vor. Diese Methode beinhaltet explizit technisch-induzierte Laufzeiten verwendeter Hörhilfen, sodass eine natürliche Stimulation unter Verwendung von realitätsnahen Stimuli ermöglicht wird. Unglücklicherweise sind ABRs von CI-Nutzern zusätzlich mit Stimulationsartefakten belastet, wodurch benötigte neurale Antworten weiter verzerrt werden und eine entsprechende Analyse der Signale deutlich erschwert wird. Um dieses Problem zu umgehen, schlagen wir eine neue Artefakt- Reduktionstechnik vor, welche auf spektraler Schmalbandfilterung basiert und somit den Erhalt entsprechender, neuraler ABR Korrelate ermöglicht. Diese Methoden erlaubten die Interpretation neuraler Korrelate auf Hirnstammebene unter Verwendung von zwei verschiedenen Stimuli (Chirps und Klicks) unter vier verschiedenen Lautstärken in 12 CI-Nutzern und 12 normalhörenden Probanden. Die beschriebene Prozedur adaptiert somit die weitläufig bekannte Hirnstammaudiometrie (engl. brainstem evoked response audiometry (BERA)), deren Ergebnisse zur zusätzlichen Evaluation des vorgestellten Verfahrens dienten. Die Untersuchung der aus 2000 Einzelantworten erhaltenen Mittelwerte in Kombination mit der Analyse synchronisierter Regularitäten über den Verlauf der Einzelantworten ergab dabei konsistente Beobachtungen in gefundenen Amplituden, Latenzen sowie in Abhängigkeiten zwischen Einzelantworten in beiden Gruppen. Das vorgestellte Verfahren erlaubt somit auf einzigartige Weise neue und ungesehene Einsichten in natürliche, neurale Antworten auf Hirnstammebene von CI-Nutzern, welche in zukünftigen Studien verwendet werden können, um binaurale Interaktionen und Fusionen weiter untersuchen zu können. Interessanterweise hat sich, die auf ABRs basierende, binaurale Interaktionskomponente (engl. binaural interaction component (BIC)) als objektiver Indikator binauraler Integration etabliert. Diese Komponente (d.h. die arithmetische Differenz zwischen der Summe der monauralen Antworten und der binauralen Antwort) ist leider sehr fragil, wodurch ein sicherer und objektiver Nachweis in CI-Nutzern bis heute nicht existiert. Dabei ist es sehr wahrscheinlich, dass gerade Implantatsträger von einer entsprechenden Analyse auf Hirnstammebene und höherrangigen Ebenen deutlich profitieren würden, da dies objektiv Anpassstrategien mit Rücksicht auf eine bestmögliche binaurale Integration ermöglichen könnte. Deshalb stellen wir ein weiteres, neuartiges Verfahren zum Erhalt von neuralen Korrelaten binauraler Interaktion in bimodal versorgten CI-Trägern vor, welches jüngste Erfolge im Bereich der schnellen, entfalltungsbasierten ABR Akquisition und der bereits vorgestellten Schmalband- filterung zur Reduktion von Stimulationsartefakten kombiniert. Basierend auf diesem Verfahren konnten signifikante Verbesserungen in der BIC-Amplitude in 10 bimodal versorgten Patienten sowie 10 normalhörenden Probanden, basierend auf umgesetzte, interaurale Laufzeitkompensationen technischer Hörhilfen, aufgezeigt werden. Insgesamt demonstrieren beide vorgestellten Studien technisch-induzierte, interaurale Laufzeitunterschiede und betonen demnach sehr deutlich potenzielle Vorteile in assoziierten neuralen Korrelaten binauraler Interaktionen, wenn solche Missverhältnisse zeitlich ausgeglichen werden. Die aufgezeigten Ergebnisse sowie die getätigte Abschätzungen technischer Laufzeiten sollte in größeren Gruppen weiter untersucht werden, um die Aussagekraft weiter zu steigern. Dennoch unterstreichen diese Einsichten das Verlangen nach binauralen Lösungsansätzen in der zukünftigen Hörrehabilitation, statt bisheriger isolierter und monauraler Therapien

A Model for Electrical Communication Between Cochlear Implants and the Brain

In the last thirty years, cochlear implants have become an invaluable instrument in the treatment of severe-to-profound hearing impairment. An important aspect of research in the continued development of cochlear implants is the in vivo assessment of signal processing algorithms intended to improve perception of speech and other auditory signals. In trying to determine how closely cochlear implant recipients process sound relative to the processing done by a normal auditory system, various assessment techniques have been applied. The most common technique has been measurement of auditory evoked potentials (AEPs), which involves the recording of neural responses to auditory stimulation. Depending on the latency of the observed response, the evoked potential indicates neural activity at various ascending neurological structures of the auditory system. Although there have been a number of publications on the topic of AEPs in cochlear implant subjects, there is a need for better measurement and research techniques to obtain more in-depth information to facilitate research on effectiveness of signal processing approaches in cochlear implants. The research presented herein explored the use of MatLab for the purpose of developing a model for electrically evoked auditory brainstem responses (EABRs). The EABR is commonly measured in hearing-impaired patients who have cochlear implants, via electrical stimulation delivered from electrodes in the implanted array. The simulation model developed in this study took as its input the stimulus current intensity level, and used function vectors and equations derived from measured EABRs, to generate an approximation of the evoked surface potentials. A function vector was used to represent the combined firing of the neurons of the auditory nervous system that are needed to elicit a measurable response. Equations were derived to represent the latency and stimulus amplitude scaling functions. The simulation also accounted for other neural activity that can be present in and contaminate an ABR recording, and reduced it through time-locked averaging of the simulated response. Predicted waveforms from the MatLab model were compared both to published waveforms from a cochlear implant recipient, and a series of EABR waveforms measured by the author in other cochlear implant recipients. Measurement of the EABRs required specialized interfacing of a commercial recording system with the signal processors of the patients\u27 cochlear implants. A novel measurement technique was also used to obtain more frequency-specific information than usually obtained. Although the nonlinearities normally present in the auditory system were not considered in this MatLab simulation, the model nevertheless performed well and delivered results comparing favorably with the results measured from the research subjects

Neurocomputing systems for auditory processing

This thesis studies neural computation models and neuromorphic implementations of the auditory pathway with applications to cochlear implants and artificial auditory sensory and processing systems. Very low power analogue computation is addressed through the design of micropower analogue building blocks and an auditory preprocessing module targeted at cochlear implants. The analogue building blocks have been fabricated and tested in a standard Complementary Metal Oxide Silicon (CMOS) process. The auditory pre-processing module design is based on the cochlea signal processing mechanisms and low power microelectronic design methodologies. Compared to existing preprocessing techniques used in cochlear implants, the proposed design has a wider dynamic range and lower power consumption. Furthermore, it provides the phase coding as well as the place coding information that are necessary for enhanced functionality in future cochlear implants. The thesis presents neural computation based approaches to a number of signal-processing problems encountered in cochlear implants. Techniques that can improve the performance of existing devices are also presented. Neural network based models for loudness mapping and pattern recognition based channel selection strategies are described. Compared with state—of—the—art commercial cochlear implants, the thesis results show that the proposed channel selection model produces superior speech sound qualities; and the proposed loudness mapping model consumes substantially smaller amounts of memory. Aside from the applications in cochlear implants, this thesis describes a biologically plausible computational model of the auditory pathways to the superior colliculus based on current neurophysiological findings. The model encapsulates interaural time difference, interaural spectral difference, monaural pathway and auditory space map tuning in the inferior colliculus. A biologically plausible Hebbian-like learning rule is proposed for auditory space neural map tuning, and a reinforcement learning method is used for map alignment with other sensory space maps through activity independent cues. The validity of the proposed auditory pathway model has been verified by simulation using synthetic data. Further, a complete biologically inspired auditory simulation system is implemented in software. The system incorporates models of the external ear, the cochlea, as well as the proposed auditory pathway model. The proposed implementation can mimic the biological auditory sensory system to generate an auditory space map from 3—D sounds. A large amount of real 3-D sound signals including broadband White noise, click noise and speech are used in the simulation experiments. The efiect of the auditory space map developmental plasticity is examined by simulating early auditory space map formation and auditory space map alignment with a distorted visual sensory map. Detailed simulation methods, procedures and results are presented

Brainstem Auditory Evoked Potentials And Network Dysfunction In Mild Traumatic Brain Injury

Brainstem Auditory Evoked Potentials and Network Dysfunction in Mild Traumatic Brain Injury Theresa L. Williamson BS1,2, Amanda R. Rabinowitz PhD1, Victoria E. Johnson MD1, John A. Wolf PhD1, Michael L. McGarvey MD3, Douglas H. Smith MD1 University of Pennsylvania Department of Neurosurgery Philadelphia, PA 191041, Yale School of Medicine New Haven, CT 065112, University of Pennsylvania Department of Neurology Philadelphia, PA 191043 Introduction: Mild traumatic brain injury (mTBI) challenges clinicians as symptoms do not map in a lesion-specific manner and there is no objective diagnostic measure. Diffuse axonal injury is a main mechanism of injury in mTBI [1, 2]. Injury to axons is proposed to alter the brain\u27s networks and underlie common symptoms such as slow processing speed, poor concentration and memory. Clinical studies show that the auditory network is also commonly disrupted in mTBI and therefore the auditory pathway is a useful surrogate for study to understand network dysfunction as it relates to axonal pathology and signal processing speed. Methods: Decades of research using a rotational acceleration injury model in pigs scaled to the known mechanical loading conditions in humans demonstrates multi-focal swelling of axons [1]. This study utilizes a known model of mTBI to relate diffuse axonal injury to the physiologic functioning of a network. The technique is to record latency, amplitude and morphology of the auditory evoked potential response before, immediately after, and three days after injury as well as conduct a histopathologic investigation of the brainstem auditory pathway for evidence of axonal injury. Results: We have identified increased latency and morphologic changes of the brainstem auditory evoked potential waveforms in swine following injury that correspond to pathology in regions in the upper brainstem, immediately after and at three days post-injury as compared to a pre-injury control measurements. Additionally, we have identified axonal pathology, indicated by amyloid precursor protein positive axonal swellings, in the region of the lateral lemniscus and inferior colliculus. Conclusions: This data shows that in a clinically relevant model of mild traumatic brain injury, damage to axons in a pathway corresponds to functional delay in the pathway\u27s processing. Identifying a link between axonal pathology and function in the auditory pathway is useful to represent network injury throughout the brain shedding light on mTBI\u27s diffuse nature that underlies a group of symptoms that are both difficult to diagnose and treat