Neuronal population model of globular bushy cells covering unit-to-unit variability

Review of Binaural Processing With Asymmetrical Hearing Outcomes in Patients With Bilateral Cochlear Implants

Bilateral cochlear implants (BiCIs) result in several benefits, including improvements in speech understanding in noise and sound source localization. However, the benefit bilateral implants provide among recipients varies considerably across individuals. Here we consider one of the reasons for this variability: difference in hearing function between the two ears, that is, interaural asymmetry. Thus far, investigations of interaural asymmetry have been highly specialized within various research areas. The goal of this review is to integrate these studies in one place, motivating future research in the area of interaural asymmetry. We first consider bottom-up processing, where binaural cues are represented using excitation-inhibition of signals from the left ear and right ear, varying with the location of the sound in space, and represented by the lateral superior olive in the auditory brainstem. We then consider top-down processing via predictive coding, which assumes that perception stems from expectations based on context and prior sensory experience, represented by cascading series of cortical circuits. An internal, perceptual model is maintained and updated in light of incoming sensory input. Together, we hope that this amalgamation of physiological, behavioral, and modeling studies will help bridge gaps in the field of binaural hearing and promote a clearer understanding of the implications of interaural asymmetry for future research on optimal patient interventions.

High-resolution volumetric imaging constrains compartmental models to explore synaptic integration and temporal processing by cochlear nucleus globular bushy cells

Globular bushy cells (GBCs) of the cochlear nucleus play central roles in the temporal processing of sound. Despite investigation over many decades, fundamental questions remain about their dendrite structure, afferent innervation, and integration of synaptic inputs. Here, we use volume electron microscopy (EM) of the mouse cochlear nucleus to construct synaptic maps that precisely specify convergence ratios and synaptic weights for auditory nerve innervation and accurate surface areas of all postsynaptic compartments. Detailed biophysically based compartmental models can help develop hypotheses regarding how GBCs integrate inputs to yield their recorded responses to sound. We established a pipeline to export a precise reconstruction of auditory nerve axons and their endbulb terminals together with high-resolution dendrite, soma, and axon reconstructions into biophysically detailed compartmental models that could be activated by a standard cochlear transduction model. With these constraints, the models predict auditory nerve input profiles whereby all endbulbs onto a GBC are subthreshold (coincidence detection mode), or one or two inputs are suprathreshold (mixed mode). The models also predict the relative importance of dendrite geometry, soma size, and axon initial segment length in setting action potential threshold and generating heterogeneity in sound-evoked responses, and thereby propose mechanisms by which GBCs may homeostatically adjust their excitability. Volume EM also reveals new dendritic structures and dendrites that lack innervation. This framework defines a pathway from subcellular morphology to synaptic connectivity, and facilitates investigation into the roles of specific cellular features in sound encoding. We also clarify the need for new experimental measurements to provide missing cellular parameters, and predict responses to sound for further in vivo studies, thereby serving as a template for investigation of other neuron classes.

Graded optogenetic activation of the auditory pathway for hearing restoration

Optogenetic control of neural activity enables innovative approaches to improve functional restoration of diseased sensory and motor systems. For clinical translation to succeed, optogenetic stimulation needs to closely match the coding properties of the targeted neuronal population and employ optimally operating emitters. This requires the customization of channelrhodopsins, emitters and coding strategies. Here, we provide a framework to parametrize optogenetic neural control and apply it to the auditory pathway that requires high temporal fidelity of stimulation. We used a viral gene transfer of ultrafast targeting-optimized Chronos into spiral ganglion neurons (SGNs) of the cochlea of mice. We characterized the light-evoked response by in vivo recordings from individual SGNs and neurons of the anteroventral cochlear nucleus (AVCN) that detect coincident SGN inputs. Our recordings from single SGNs demonstrated that their spike probability can be graded by adjusting the duration of light pulses at constant intensity, which optimally serves efficient laser diode operation. We identified an effective pulse width of 1.6 ms to maximize encoding in SGNs at the maximal light intensity employed here (∼35 mW). Alternatively, SGNs were activated at lower energy thresholds using short light pulses (<1 ms). An upper boundary of optical stimulation rates was identified at 316 Hz, inducing a robust spike rate adaptation that required a few tens of milliseconds to recover. We developed a semi-stochastic stimulation paradigm to rapidly (within minutes) estimate the input/output function from light to SGN firing and approximate the time constant of neuronal integration in the AVCN. By that, our data pave the way to design the sound coding strategies of future optical cochlear implants.

Theoretical Relationship Between Two Measures of Spike Synchrony: Correlation Index and Vector Strength

Information processing in the nervous system critically relies on temporally precise spiking activity. In the auditory system, various degrees of phase-locking can be observed from the auditory nerve to cortical neurons. The classical metric for quantifying phase-locking is the vector strength (VS), which captures the periodicity in neuronal spiking. More recently, another metric, called the correlation index (CI), was proposed to quantify the temporally reproducible response characteristics of a neuron. The CI is defined as the peak value of a normalized shuffled autocorrelogram (SAC). Both VS and CI have been used to investigate how temporal information is processed and propagated along the auditory pathways. While previous analyses of physiological data in cats suggested covariation of these two metrics, general characterization of their connection has never been performed. In the present study, we derive a rigorous relationship between VS and CI. To model phase-locking, we assume Poissonian spike trains with a temporally changing intensity function following a von Mises distribution. We demonstrate that VS and CI are mutually related via the so-called concentration parameter that determines the degree of phase-locking. We confirm that these theoretical results are largely consistent with physiological data recorded in the auditory brainstem of various animals. In addition, we generate artificial phase-locked spike sequences, for which recording and analysis parameters can be systematically manipulated. Our analysis results suggest that mismatches between empirical data and the theoretical prediction can often be explained with deviations from the von Mises distribution, including skewed or multimodal period histograms. Furthermore, temporal relations of spike trains across trials can contribute to higher CI values than predicted mathematically based on the VS. We find that, for most applications, a SAC bin width of 50 ms seems to be a favorable choice, leading to an estimated error below 2.5% for physiologically plausible conditions. Overall, our results provide general relations between the two measures of phase-locking and will aid future analyses of different physiological datasets that are characterized with these metrics.

Auditory Brainstem Models: Adapting Cochlear Nuclei Improve Spatial Encoding by the Medial Superior Olive in Reverberation

Listeners typically perceive a sound as originating from the direction of its source, even as direct sound is followed milliseconds later by reflected sound from multiple different directions. Early-arriving sound is emphasised in the ascending auditory pathway, including the medial superior olive (MSO) where binaural neurons encode the interaural-time-difference (ITD) cue for spatial location. Perceptually, weighting of ITD conveyed during rising sound energy is stronger at 600 Hz than at 200 Hz, consistent with the minimum stimulus rate for binaural adaptation, and with the longer reverberation times at 600 Hz, compared with 200 Hz, in many natural outdoor environments. Here, we computationally explore the combined efficacy of adaptation prior to the binaural encoding of ITD cues, and excitatory binaural coincidence detection within MSO neurons, in emphasising ITDs conveyed in early-arriving sound. With excitatory inputs from adapting, nonlinear model spherical bushy cells (SBCs) of the bilateral cochlear nuclei, a nonlinear model MSO neuron with low-threshold potassium channels reproduces the rate-dependent emphasis of rising vs. peak sound energy in ITD encoding; adaptation is equally effective in the model MSO. Maintaining adaptation in model SBCs, and adjusting membrane speed in model MSO neurons, 'left' and 'right' populations of computationally efficient, linear model SBCs and MSO neurons reproduce this stronger weighting of ITD conveyed during rising sound energy at 600 Hz compared to 200 Hz. This hemispheric population model demonstrates a link between strong weighting of spatial information during rising sound energy, and correct unambiguous lateralisation of a speech source in reverberation.