On the localization of complex sounds: temporal encoding based on input-slope coincidence detection of envelopes

Axon initial segment plasticity caused by auditory deprivation degrades time difference sensitivity in a model of neural responses to cochlear implants

Synaptic and neural properties can change during periods of auditory deprivation. These changes may disrupt the computations that neurons perform. In the brainstem of chickens, auditory deprivation can lead to changes in the size and biophysics of the axon initial segment (AIS) of neurons in the sound source localization circuit. This is the phenomenon of axon initial segment (AIS) plasticity. Individuals who use cochlear implants (CIs) experience periods of hearing loss, and so we ask whether AIS plasticity in neurons of the medial superior olive (MSO), a key stage of sound location processing, would impact time difference sensitivity in the scenario of hearing with cochlear implants. The biophysical changes that we implement in our model of AIS plasticity include enlargement of the AIS and replacement of low-threshold potassium conductance with the more slowly-activated M-type potassium conductance. AIS plasticity has been observed to have a homeostatic effect with respect to excitability. In our model, AIS plasticity has the additional effect of converting MSO neurons from phasic firing type to tonic firing type. Phasic firing is known to have greater temporal sensitivity to coincident inputs. Consistent with this, we find AIS plasticity degrades time difference sensitivity in the auditory deprived MSO neuron model across a range of stimulus parameters. Our study illustrates a possible mechanism of cellular plasticity in a non-peripheral stage of neural processing that could impose barriers to sound source localization by bilateral cochlear implant users.

The impact of peripheral mechanisms on the precedence effect

When two similar sounds are presented from different locations, with one (the lead) preceding the other (the lag) by a small delay, listeners typically report hearing one sound near the location of the lead sound source-this is called the precedence effect (PE). Several questions about the underlying mechanisms that produce the PE are asked. (1) How might listeners' relative weighting of cues at onset versus ongoing stimulus portions affect perceived lateral position of long-duration lead/lag noise stimuli? (2) What are the factors that influence this weighting? (3) Are the mechanisms invoked to explain the PE for transient stimuli applicable to long-duration stimuli? To answer these questions, lead/lag noise stimuli are presented with a range of durations, onset slopes, and lag-to-lead level ratios over headphones. Monaural, peripheral mechanisms, and binaural cue extraction are modeled to estimate the cues available for determination of perceived laterality. Results showed that all three stimulus manipulations affect the relative weighting of onset and ongoing cues and that mechanisms invoked to explain the PE for transient stimuli are also applicable to the PE, in terms of both onset and ongoing segments of long-duration, lead/lag stimuli.

A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex

Birdsong is a complex vocal communication signal, and like humans, birds need to discriminate between similar sequences of sound with different meanings. The caudal mesopallium (CM) is a cortical-level auditory area implicated in song discrimination. CM neurons respond sparsely to conspecific song and are tolerant of production variability. Intracellular recordings in CM have identified a diversity of intrinsic membrane dynamics, which could contribute to the emergence of these higher-order functional properties. We investigated this hypothesis using a novel linear-dynamical cascade model that incorporated detailed biophysical dynamics to simulate auditory responses to birdsong. Neuron models that included a low-threshold potassium current present in a subset of CM neurons showed increased selectivity and coding efficiency relative to models without this current. These results demonstrate the impact of intrinsic dynamics on sensory coding and the importance of including the biophysical characteristics of neural populations in simulation studies.

Maintaining a stable mental representation of an object is an important task for sensory systems, requiring both recognizing the features required for identification and ignoring incidental changes in its presentation. The prevailing explanation for these processes emphasizes precise sets of connections between neurons that capture only the essential features of an object. However, the intrinsic dynamics of the neurons themselves, which determine how these inputs are transformed into spiking outputs, may also contribute to the neural computations underlying object recognition. To understand how intrinsic dynamics contribute to sensory coding, we constructed a computational model capable of simulating a neural response to an auditory stimulus using a detailed description of different intrinsic dynamics in a higher-order avian auditory area. The results of our simulation showed that intrinsic dynamics can have a profound effect on processes underlying object recognition. These findings challenge the view that patterns of connectivity alone account for the emergence of stable object representations and encourage greater consideration of the functional implications of the diversity of neurons in the brain.

A framework for computational modelling of interaural time difference discrimination of normal and hearing-impaired listeners

Different computational models have been developed to study the interaural time difference (ITD) perception. However, only few have used a physiologically inspired architecture to study ITD discrimination. Furthermore, they do not include aspects of hearing impairment. In this work, a framework was developed to predict ITD thresholds in listeners with normal and impaired hearing. It combines the physiologically inspired model of the auditory periphery proposed by Zilany, Bruce, Nelson, and Carney [(2009). J. Acoust. Soc. Am. 126(5), 2390-2412] as a front end with a coincidence detection stage and a neurometric decision device as a back end. It was validated by comparing its predictions against behavioral data for narrowband stimuli from literature. The framework is able to model ITD discrimination of normal-hearing and hearing-impaired listeners at a group level. Additionally, it was used to explore the effect of different proportions of outer- and inner-hair cell impairment on ITD discrimination.

Psychophysical and modeling approaches towards determining the cochlear phase response based on interaural time differences

The cochlear phase response is often estimated by measuring masking of a tonal target by harmonic complexes with various phase curvatures. Maskers yielding most modulated internal envelope representations after passing the cochlear filter are thought to produce minimum masking, with fast-acting cochlear compression as the main contributor to that effect. Thus, in hearing-impaired (HI) listeners, reduced cochlear compression hampers estimation of the phase response using the masking method. This study proposes an alternative approach, based on the effect of the envelope modulation strength on the sensitivity to interaural time differences (ITDs). To evaluate the general approach, ITD thresholds were measured in seven normal-hearing listeners using 300-ms Schroeder-phase harmonic complexes with nine different phase curvatures. ITD thresholds tended to be lowest for phase curvatures roughly similar to those previously shown to produce minimum masking. However, an unexpected ITD threshold peak was consistently observed for a particular negative phase curvature. An auditory-nerve based ITD model predicted the general pattern of ITD thresholds except for the threshold peak, as well as published envelope ITD data. Model predictions simulating outer hair cell loss support the feasibility of the ITD-based approach to estimate the phase response in HI listeners.

Noise-enhanced coding in phasic neuron spike trains

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Exploring binaural hearing in gerbils (Meriones unguiculatus) using virtual headphones

The Mongolian gerbil (Meriones unguiculatus) has become a key species in investigations of the neural processing of sound localization cues in mammals. While its sound localization has been tested extensively under free-field stimulation, many neurophysiological studies use headphones to present signals with binaural localization cues. The gerbil's behavioral sensitivity to binaural cues, however, is unknown for the lack of appropriate stimulation paradigms in awake behaving gerbils. We close this gap in knowledge by mimicking a headphone stimulation; we use free-field loudspeakers and apply cross-talk cancellation techniques to present pure tones with binaural cues via “virtual headphones” to gerbils trained in a sound localization task. All gerbils were able to lateralize sounds depending on the interaural time or level difference (ITD and ILD, respectively). For ITD stimuli, reliable responses were seen for frequencies ≤2.9 kHz, the highest frequency tested with ITD stimuli. ITD sensitivity was frequency-dependent with the highest sensitivity observed at 1 kHz. For stimuli with ITD outside the gerbil's physiological range, responses were cyclic indicating the use of phase information when lateralizing narrow-band sounds. For ILD stimuli, reliable responses were obtained for frequencies ≥2 kHz. The comparison of ITD and ILD thresholds with ITD and ILD thresholds derived from gerbils’ free-field performance suggests that ongoing ITD information is the main cue for sound localization at frequencies <2 kHz. At 2 kHz, ITD and ILD cues are likely used in a complementary way. Verification of the use of the virtual headphones suggests that they can serve as a suitable substitute for conventional headphones particularly at frequencies ≤2 kHz.

Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds

Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

Detecting coincident arrivals of synaptic inputs is a shared fundamental property of many sensory neurons. Such 'coincidence detection' usually refers to the detection of synchronized excitatory inputs only. Experimental evidence, however, indicated that some auditory neurons are also sensitive to the relative timing of excitatory and inhibitory synaptic inputs. This type of sensitivity is suggested to be important for coding temporal information of amplitude-modulated sounds, such as speech and other naturalistic sounds. In this study, we used a minimal model of coincidence detection to identify the key elements for temporal information processing. Our series of simulations demonstrated that (1) the threshold and time window for coincidence detection were the major factors for determining the response properties to excitatory inputs, and that (2) timed interactions between excitatory and inhibitory synaptic inputs are responsible for determining the temporal tuning properties of the neuron. These results suggest that coincidence detection is an essential function of neurons that detect the 'anti-coincidence' of excitatory and inhibitory inputs to encode temporal information of sounds.

Sensitivity to Interaural Time Differences Conveyed in the Stimulus Envelope: Estimating Inputs of Binaural Neurons Through the Temporal Analysis of Spike Trains

Sound-source localization in the horizontal plane relies on detecting small differences in the timing and level of the sound at the two ears, including differences in the timing of the modulated envelopes of high-frequency sounds (envelope interaural time differences (ITDs)). We investigated responses of single neurons in the inferior colliculus (IC) to a wide range of envelope ITDs and stimulus envelope shapes. By a novel means of visualizing neural activity relative to different portions of the periodic stimulus envelope at each ear, we demonstrate the role of neuron-specific excitatory and inhibitory inputs in creating ITD sensitivity (or the lack of it) depending on the specific shape of the stimulus envelope. The underlying binaural brain circuitry and synaptic parameters were modeled individually for each neuron to account for neuron-specific activity patterns. The model explains the effects of envelope shapes on sensitivity to envelope ITDs observed in both normal-hearing listeners and in neural data, and has consequences for understanding how ITD information in stimulus envelopes might be maximized in users of bilateral cochlear implants-for whom ITDs conveyed in the stimulus envelope are the only ITD cues available.