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We recently developed a biomimetic robotic eye with six independent tendons, each controlled by their own rotatory motor, and with insertions on the eye ball that faithfully mimic the biomechanics of the human eye. We constructed an accurate physical computational model of this system, and learned to control its nonlinear dynamics by optimising a cost that penalised saccade inaccuracy, movement duration, and total energy expenditure of the motors. To speed up the calculations, the physical simulator was approximated by a recurrent neural network (NARX). We showed that the system can produce realistic eye movements that closely resemble human saccades in all directions: their nonlinear main-sequence dynamics (amplitude-peak eye velocity and duration relationships), cross-coupling of the horizontal and vertical movement components leading to approximately straight saccade trajectories, and the 3D kinematics that restrict 3D eye orientations to a plane (Listing’s law). Interestingly, the control algorithm had organised the motors into appropriate agonist-antagonist muscle pairs, and the motor signals for the eye resembled the well-known pulse-step characteristics that have been reported for monkey motoneuronal activity. We here fully analyse the eye-movement properties produced by the computational model across the entire oculomotor range and the underlying control signals. We argue that our system may shed new light on the neural control signals and their couplings within the final neural pathways of the primate oculomotor system, and that an optimal control principle may account for a wide variety of oculomotor behaviours. The generated data are publicly available at https://data.ru.nl/collections/di/dcn/DSC_626870_0003_600.

Abstract The midbrain superior colliculus is a crucial sensorimotor stage for programming and generating saccadic eye-head gaze shifts. Although it is well established that superior colliculus cells encode a neural command that specifies the amplitude and direction of the upcoming gaze-shift vector, there is controversy about the role of the firing-rate dynamics of these neurons during saccades. In our earlier work, we proposed a simple quantitative model that explains how the recruited superior colliculus population may specify the detailed kinematics (trajectories and velocity profiles) of head-restrained saccadic eye movements. We here show that the same principles may apply to a wide range of saccadic eye-head gaze shifts with strongly varying kinematics, despite the substantial nonlinearities and redundancy in programming and execute rapid goal-directed eye-head gaze shifts to peripheral targets. Our findings could provide additional evidence for an important role of the superior colliculus in the optimal control of saccades.

A cochlear implant (CI) is a neurotechnological device that restores total sensorineural hearing loss. It contains a sophisticated speech processor that analyzes and transforms the acoustic input. It distributes its time-enveloped spectral content to the auditory nerve as electrical pulsed stimulation trains of selected frequency channels on a multi-contact electrode that is surgically inserted in the cochlear duct. This remarkable brain interface enables the deaf to regain hearing and understand speech. However, tuning of the large (>50) number of parameters of the speech processor, so-called “device fitting,” is a tedious and complex process, which is mainly carried out in the clinic through ‘one-size-fits-all’ procedures. Current fitting typically relies on limited and often subjective data that must be collected in limited time. Despite the success of the CI as a hearing-restoration device, variability in speech-recognition scores among users is still very large, and mostly unexplained. The major factors that underly this variability incorporate three levels: (i) variability in auditory-system malfunction of CI-users, (ii) variability in the selectivity of electrode-to-auditory nerve (EL-AN) activation, and (iii) lack of objective perceptual measures to optimize the fitting. We argue that variability in speech recognition can only be alleviated by using objective patient-specific data for an individualized fitting procedure, which incorporates knowledge from all three levels. In this paper, we propose a series of experiments, aimed at collecting a large amount of objective (i.e., quantitative, reproducible, and reliable) data that characterize the three processing levels of the user’s auditory system. Machine-learning algorithms that process these data will eventually enable the clinician to derive reliable and personalized characteristics of the user’s auditory system, the quality of EL-AN signal transfer, and predictions of the perceptual effects of changes in the current fitting.

Abstract Previous studies have indicated that the location of a large neural population in the Superior Colliculus (SC) motor map specifies the amplitude and direction of the saccadic eye-movement vector, while the saccade trajectory and velocity profile are encoded by the population firing rates. We recently proposed a simple spiking neural network model of the SC motor map, based on linear summation of individual spike effects of each recruited neuron, which accounts for many of the observed properties of SC cells in relation to the ensuing eye movement. However, in the model, the cortical input was kept invariant across different saccades. Electrical microstimulation and reversible lesion studies have demonstrated that the saccade properties are quite robust against large changes in supra-threshold SC activation, but that saccade amplitude and peak eye-velocity systematically decrease at low input strengths. These features were not accounted for by the linear spike-vector summation model. Here we show that the model’s input projection strengths and intra-collicular lateral connections can be tuned to generate saccades and neural spiking patterns that closely follow the experimental results.

Abstract Several studies have proposed that an optimal speed-accuracy tradeoff underlies the stereotyped relationship between amplitude, duration and peak velocity of saccades (main sequence). To test this theory, we asked 8 participants to make saccades to Gaussian-blurred spots and manipulated the task’s accuracy constraints by varying target size (1, 3, and 5°). The largest targets indeed yielded more endpoint scatter (and lower gains) than the smallest targets, although this effect subsided with target eccentricity. The main sequence depended on several interacting factors: saccade latency, saccade gain and target size. Early saccades, which were faster than amplitude-matched late saccades, followed the target-size dependency one would expect from a speed-accuracy tradeoff process. They had higher peak velocities and shorter durations for larger targets than for smaller targets. For late saccades, however, the opposite was found. Deviations from the main sequence also covaried with saccade gain, in line with the idea that motor noise underlies part of the endpoint variability. Thus, our data provide partial evidence that the saccadic system weighs the detrimental effects of motor noise on saccade accuracy against movement duration and speed, but other factors also modulate the kinematics. We discuss the possible involvement of parallel saccade pathways to account for our findings.

IntroductionTo reorient gaze (the eye’s direction in space) towards a target is an overdetermined problem, as infinitely many combinations of eye- and head movements can specify the same gaze-displacement vector. Yet, behavioral measurements show that the primate gaze-control system selects a specific contribution of eye- and head movements to the saccade, which depends on the initial eye-in-head orientation. Single-unit recordings in the primate superior colliculus (SC) during head-unrestrained gaze shifts have further suggested that cells may encode the instantaneous trajectory of a desired straight gaze path in a feedforward way by the total cumulative number of spikes in the neural population, and that the instantaneous gaze kinematics are thus determined by the neural firing rates. The recordings also indicated that the latter is modulated by the initial eye position. We recently proposed a conceptual model that accounts for many of the observed properties of eye-head gaze shifts and on the potential role of the SC in gaze control.MethodsHere, we extend and test the model by incorporating a spiking neural network of the SC motor map, the output of which drives the eye-head motor control circuitry by linear cumulative summation of individual spike effects of each recruited SC neuron. We propose a simple neural mechanism on SC cells that explains the modulatory influence of feedback from an initial eye-in-head position signal on their spiking activity. The same signal also determines the onset delay of the head movement with respect to the eye. Moreover, the downstream eye- and head burst generators were taken to be linear, as our earlier work had indicated that much of the non-linear main-sequence kinematics of saccadic eye movements may be due to neural encoding at the collicular level, rather than at the brainstem.Results and discussionWe investigate how the spiking activity of the SC population drives gaze to the intended target location within a dynamic local gaze-velocity feedback circuit that yields realistic eye- and head-movement kinematics and dynamic SC gaze-movement fields.

Abstract The latency of the auditory steady-state response (ASSR) may provide valuable information regarding the integrity of the auditory system, as it could potentially reveal the presence of multiple intracerebral sources. To estimate multiple latencies from high-order ASSRs, we propose a novel two-stage procedure that consists of a nonparametric estimation method, called apparent latency from phase coherence (ALPC), followed by a heuristic sequential forward selection algorithm (SFS). Compared with existing methods, ALPC-SFS requires few prior assumptions, and is straightforward to implement for higher-order nonlinear responses to multi-cosine sound complexes with their initial phases set to zero. It systematically evaluates the nonlinear components of the ASSRs by estimating multiple latencies, automatically identifies involved ASSR components, and reports a latency consistency index. To verify the proposed method, we performed simulations for several scenarios: two nonlinear subsystems with different or overlapping outputs. We compared the results from our method with predictions from existing, parametric methods. We also recorded the EEG from ten normal-hearing adults by bilaterally presenting superimposed tones with four frequencies that evoke a unique set of ASSRs. From these ASSRs, two major latencies were found to be stable across subjects on repeated measurement days. The two latencies are dominated by low-frequency (LF) (near 40 Hz, at around 41–52 ms) and high-frequency (HF) (> 80 Hz, at around 21–27 ms) ASSR components. The frontal-central brain region showed longer latencies on LF components, but shorter latencies on HF components, when compared with temporal-lobe regions. In conclusion, the proposed nonparametric ALPC-SFS method, applied to zero-phase, multi-cosine sound complexes is more suitable for evaluating embedded nonlinear systems underlying ASSRs than existing methods. It may therefore be a promising objective measure for hearing performance and auditory cortex (dys)function.

The cochlear implant (CI) allows profoundly deaf individuals to partially recover hearing. Still, due to the coarse acoustic information provided by the implant, CI users have considerable difficulties in recognizing speech, especially in noisy environments. CI users therefore rely heavily on visual cues to augment speech recognition, more so than normal-hearing individuals. However, it is unknown how attention to one (focused) or both (divided) modalities plays a role in multisensory speech recognition. Here we show that unisensory speech listening and reading were negatively impacted in divided-attention tasks for CI users—but not for normal-hearing individuals. Our psychophysical experiments revealed that, as expected, listening thresholds were consistently better for the normal-hearing, while lipreading thresholds were largely similar for the two groups. Moreover, audiovisual speech recognition for normal-hearing individuals could be described well by probabilistic summation of auditory and visual speech recognition, while CI users were better integrators than expected from statistical facilitation alone. Our results suggest that this benefit in integration comes at a cost. Unisensory speech recognition is degraded for CI users when attention needs to be divided across modalities. We conjecture that CI users exhibit an integration-attention trade-off. They focus solely on a single modality during focused-attention tasks, but need to divide their limited attentional resources in situations with uncertainty about the upcoming stimulus modality. We argue that in order to determine the benefit of a CI for speech recognition, situational factors need to be discounted by presenting speech in realistic or complex audiovisual environments.

Several studies have demonstrated the advantages of the bilateral vs. unilateral cochlear implantation in listeners with bilateral severe to profound hearing loss. However, it remains unclear to what extent bilaterally implanted listeners have access to binaural cues, e.g., accurate processing of interaural timing differences (ITDs) for low-frequency sounds (3 kHz). We tested 25 adult listeners, bilaterally implanted with MED-EL cochlear implant (CI) devices, with and without fine-structure (FS) temporal processing as encoding strategy in the low-frequency channels. In order to assess whether the ability to process binaural cues was affected by fine-structure processing, we performed psychophysical ILD and ITD sensitivity measurements and free-field sound localization experiments. We compared the results of the bilaterally implanted listeners with different numbers of FS channels. All CI listeners demonstrated good sensitivity to ILDs, but relatively poor to ITD cues. Although there was a large variability in performance, some bilateral CI users showed remarkably good localization skills. The FS coding strategy for bilateral CI hearing did not improve fine-structure ITD processing for spatial hearing on a group level. However, some CI listeners were able to exploit weakly informative temporal cues to improve their low-frequency spatial perception.

We assessed how synchronous speech listening and lipreading affects speech recognition in acoustic noise. In simple audiovisual perceptual tasks, inverse effectiveness is often observed, which holds that the weaker the unimodal stimuli, or the poorer their signal-to-noise ratio, the stronger the audiovisual benefit. So far, however, inverse effectiveness has not been demonstrated for complex audiovisual speech stimuli. Here we assess whether this multisensory integration effect can also be observed for the recognizability of spoken words. To that end, we presented audiovisual sentences to 18 native-Dutch normal-hearing participants, who had to identify the spoken words from a finite list. Speech-recognition performance was determined for auditory-only, visual-only (lipreading), and auditory-visual conditions. To modulate acoustic task difficulty, we systematically varied the auditory signal-to-noise ratio. In line with a commonly observed multisensory enhancement on speech recognition, audiovisual words were more easily recognized than auditory-only words (recognition thresholds of −15 and −12 dB, respectively). We here show that the difficulty of recognizing a particular word, either acoustically or visually, determines the occurrence of inverse effectiveness in audiovisual word integration. Thus, words that are better heard or recognized through lipreading, benefit less from bimodal presentation. Audiovisual performance at the lowest acoustic signal-to-noise ratios (45%) fell below the visual recognition rates (60%), reflecting an actual deterioration of lipreading in the presence of excessive acoustic noise. This suggests that the brain may adopt a strategy in which attention has to be divided between listening and lipreading.

This study describes sound localization and speech-recognition-in-noise abilities of a cochlear-implant user with electro-acoustic stimulation (EAS) in one ear, and a hearing aid in the contralateral ear. This listener had low-frequency, up to 250 Hz, residual hearing within the normal range in both ears. The objective was to determine how hearing devices affect spatial hearing for an individual with substantial unaided low-frequency residual hearing. Sound-localization performance was assessed for three sounds with different bandpass characteristics: low center frequency (100–400 Hz), mid center frequency (500–1,500 Hz) and high frequency broad-band (500–20,000 Hz) noise. Speech recognition was assessed with the Dutch Matrix sentence test presented in noise. Tests were performed while the listener used several on-off combinations of the devices. The listener localized low-center frequency sounds well in all hearing conditions, but mid-center frequency and high frequency broadband sounds were localized well almost exclusively in the completely unaided condition (mid-center frequency sounds were also localized well with the EAS device alone). Speech recognition was best in the fully aided condition with speech presented in the front and noise presented at either side. Furthermore, there was no significant improvement in speech recognition with all devices on, compared to when the listener used her cochlear implant only. Hearing aids and cochlear implant impair high frequency spatial hearing due to improper weighing of interaural time and level difference cues. The results reinforce the notion that hearing symmetry is important for sound localization. The symmetry is perturbed by the hearing devices for higher frequencies. Speech recognition depends mainly on hearing through the cochlear implant and is not significantly improved with the added information from hearing aids. A contralateral hearing aid provides benefit when the noise is spatially separated from the speech. However, this benefit is explained by the head shadow in that ear, rather than by an ability to spatially segregate noise from speech, as sound localization was perturbed with all devices in use.

Bilateral cochlear-implant (CI) users and single-sided deaf listeners with a CI are less effective at localizing sounds than normal-hearing (NH) listeners. This performance gap is due to the degradation of binaural and monaural sound localization cues, caused by a combination of device-related and patient-related issues. In this study, we targeted the device-related issues by measuring sound localization performance of 11 NH listeners, listening to free-field stimuli processed by a real-time CI vocoder. The use of a real-time vocoder is a new approach, which enables testing in a free-field environment. For the NH listening condition, all listeners accurately and precisely localized sounds according to a linear stimulus–response relationship with an optimal gain and a minimal bias both in the azimuth and in the elevation directions. In contrast, when listening with bilateral real-time vocoders, listeners tended to orient either to the left or to the right in azimuth and were unable to determine sound source elevation. When listening with an NH ear and a unilateral vocoder, localization was impoverished on the vocoder side but improved toward the NH side. Localization performance was also reflected by systematic variations in reaction times across listening conditions. We conclude that perturbation of interaural temporal cues, reduction of interaural level cues, and removal of spectral pinna cues by the vocoder impairs sound localization. Listeners seem to ignore cues that were made unreliable by the vocoder, leading to acute reweighting of available localization cues. We discuss how current CI processors prevent CI users from localizing sounds in everyday environments.

The midbrain superior colliculus (SC) is a crucial sensorimotor interface in the generation of rapid saccadic gaze shifts. For every saccade it recruits a large population of cells in its vectorial motor map. Supra-threshold electrical microstimulation in the SC reveals that the stimulated site produces the saccade vector specified by the motor map. Electrically evoked saccades (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-saccades), with little influence of the stimulation parameters. Moreover, synchronous stimulation at two sites yields eye movements that resemble a weighted vector average of the individual stimulation effects. Single-unit recordings have indicated that the SC population acts as a vectorial pulse generator by specifying the instantaneous gaze-kinematics through dynamic summation of the movement effects of all SC spike trains. But how to reconcile the a-specific stimulation pulses with these intricate saccade properties? We recently developed a spiking neural network model of the SC, in which microstimulation initially activates a relatively small set of (~50) neurons around the electrode tip, which subsequently sets up a large population response (~5,000 neurons) through lateral synaptic interactions. Single-site microstimulation in this network thus produces the saccade properties and firing rate profiles as seen in single-unit recording experiments. We here show that this mechanism also accounts for many results of simultaneous double stimulation at different SC sites. The resulting E-saccade trajectories resemble a weighted average of the single-site effects, in which stimulus current strength of the electrode pulses serve as weighting factors. We discuss under which conditions the network produces effects that deviate from experimental results.

BackgroundSpeech understanding may rely not only on auditory, but also on visual information. Non-invasive functional neuroimaging techniques can expose the neural processes underlying the integration of multisensory processes required for speech understanding in humans. Nevertheless, noise (from fMRI) limits the usefulness in auditory experiments, and electromagnetic artefacts caused by electronic implants worn by subjects can severely distort the scans (EEG, fMRI). Therefore, we assessed audio-visual activation of temporal cortex with a silent, optical neuroimaging technique: functional near-infrared spectroscopy (fNIRS).MethodsWe studied temporal cortical activation as represented by concentration changes of oxy- and deoxy-hemoglobin in four, easy-to-apply fNIRS optical channels of 33 normal-hearing adult subjects and 5 post-lingually deaf cochlear implant (CI) users in response to supra-threshold unisensory auditory and visual, as well as to congruent auditory-visual speech stimuli. ResultsActivation effects were not visible from single fNIRS channels. However, by discounting physiological noise through reference channel subtraction, auditory, visual and audiovisual speech stimuli evoked concentration changes for all sensory modalities in both cohorts (p

Direction-specific interactions of sound waves with the head, torso and pinna provide unique spectral-shape cues that are used for the localization of sounds in the vertical plane, whereas horizontal sound localization is based primarily on the processing of binaural acoustic differences in arrival time (interaural time differences, or ITDs) and sound level (interaural level differences, or ILDs). Because the binaural sound-localization cues are absent in listeners with total single-sided deafness (SSD), their ability to localize sound is heavily impaired. However, some studies have reported that SSD listeners are able, to some extent, to localize sound sources in azimuth, although the underlying mechanisms used for localization are unclear. To investigate whether SSD listeners rely on monaural pinna-induced spectral-shape cues of their hearing ear for directional hearing, we investigated localization performance for low-pass filtered (LP, 3 kHz) and broadband (BB, 0.5 – 20 kHz) noises in the two-dimensional frontal hemifield. We tested whether localization performance of SSD listeners further deteriorated when the pinna cavities of their hearing ear were filled with a mold that disrupted their spectral-shape cues. To remove the potential use of perceived sound level as an invalid azimuth cue, we randomly varied stimulus presentation levels over a broad range (45-65 dB SPL). Several listeners with SSD could localize HP and BB sound sources in the horizontal plane, but inter-subject variability was considerable. Localization performance of these listeners strongly reduced after diminishing of their spectral pinna-cues. We further show that inter-subject variability of SSD can be explained to a large extent by the severity of high-frequency hearing loss in their hearing ear.

Human sound localization in the mid-saggital plane (elevation) relies on an analysis of the idiosyncratic spectral shape cues provided by the head and pinnae. However, because the actual free-field stimulus spectrum is a-priori unknown to the auditory system, the problem of extracting the elevation angle from the sensory spectrum is ill-posed. Here we test different spectral localization models by eliciting head movements toward broad-band noise stimuli with randomly shaped, rippled amplitude spectra emanating from a speaker at a fixed location, while varying the ripple bandwidth between 1.5 and 5.0 cycles/octave. Six listeners participated in the experiments. From the distributions of localization responses toward the individual stimuli, we estimated the listeners' spectral-shape cues underlying their elevation percepts, by applying maximum-likelihood estimation. The reconstructed spectral cues resulted to be invariant to the considerable variation in ripple bandwidth, and for each listener they had a remarkable resemblance to the idiosyncratic head-related transfer functions (HRTFs). These results are not in line with models that rely on the detection of a single peak or notch in the amplitude spectrum, nor with a local analysis of first- and second-order spectral derivatives. Instead, our data support a model in which the auditory system performs a cross-correlation between the sensory input at the eardrum-auditory nerve, and stored representations of HRTF spectral shapes, to extract the perceived elevation angle.