Coding of auditory space

Behavioral, anatomical, and physiological approaches can be integrated in the study of sound localization in barn owls. Space representation in owls provides a useful example for discussion of place and ensemble coding. Selectivity for space is broad and ambiguous in low-order neurons. Parallel pathways for binaural cues and for different frequency bands converge on high-order space-specific neurons, which encode space more precisely. An ensemble of broadly tuned place-coding neurons may converge on a single high-order neuron to create an improved labeled line. Thus, the two coding schemes are not alternate methods. Owls can localize sounds by using either the isomorphic map of auditory space in the midbrain or forebrain neural networks in which space is not mapped

Theoretical foundations of the sound analog membrane potential that underlies coincidence detection in the barn owl

A wide variety of neurons encode temporal information via phase-locked spikes. In the avian auditory brainstem, neurons in the cochlear nucleus magnocellularis (NM) send phase-locked synaptic inputs to coincidence detector neurons in the nucleus laminaris (NL) that mediate sound localization. Previous modeling studies suggested that converging phase-locked synaptic inputs may give rise to a periodic oscillation in the membrane potential of their target neuron. Recent physiological recordings in vivo revealed that owl NL neurons changed their spike rates almost linearly with the amplitude of this oscillatory potential. The oscillatory potential was termed the sound analog potential, because of its resemblance to the waveform of the stimulus tone. The amplitude of the sound analog potential recorded in NL varied systematically with the interaural time difference (ITD), which is one of the most important cues for sound localization. In order to investigate the mechanisms underlying ITD computation in the NM-NL circuit, we provide detailed theoretical descriptions of how phase-locked inputs form oscillating membrane potentials. We derive analytical expressions that relate presynaptic, synaptic, and postsynaptic factors to the signal and noise components of the oscillation in both the synaptic conductance and the membrane potential. Numerical simulations demonstrate the validity of the theoretical formulations for the entire frequency ranges tested (1–8 kHz) and potential effects of higher harmonics on NL neurons with low best frequencies (<2 kHz)

A Comparative Study on the Modulatory Effects of Inhibition in the Mammalian and Avian Sound Localization Circuits

Sound localization is a critically important task for many animals including humans. Due to physical constraints acting on the circuits that process sound localization cues, many neural specializations have evolved. One of the key features and the focus of this dissertation is inhibitory input. To assess the impact of inhibition, I employ in vitro patch clamp techniques to observe cellular and synaptic physiology in brainstem circuits dedicated to sound localization processing. Using a mammalian model, I test the impact that GABAB receptor (GABABR) activation has on the inputs to the medial superior olive (MSO), the first area where sound localization computations take place. Activation of GABABRs modulates both excitatory and inhibitory inputs such that the magnitude of these inputs is decreased and the time course of inhibitory inputs is slowed. The functional significance of this modulation was tested using a bilateral stimulation protocol, which simulates the coincidence of in vivo excitatory inputs. Here, activation of GABABRs increased the sensitivity of MSO neurons to simulated interaural time disparity (ITD), the main cue for low frequency sound localization. To expand on these results, a computational model was used to show that each GABABR dependent modulation had a beneficial impact on ITD sensitivity in the MSO. In an avian system, I described the synaptic activity involving the superior olivary nucleus (SON), which provides the main inhibitory input in the avian sound localization circuit. At the SON itself, synaptic transmission consists of both GABA- and glycinergic components where glycine release is the result of co-release with GABA. I also show that functional glycine receptors localize at brainstem nuclei and that high frequency stimulation results in the release glycine onto nucleus magnocellularis neurons, a feature of the avian brainstem that has not been observed previously. In related experiments, I evaluate possible interactions that may occur when both GABA and glycine receptor systems are activated simultaneously. Here, a pre-activation of GlyRs leads the a decrease in conductance through the GABAAR likely due to changes in Cl- ion concentrations which manipulate the driving force of the ion

Multiplicative Auditory Spatial Receptive Fields Created by a Hierarchy of Population Codes

A multiplicative combination of tuning to interaural time difference (ITD) and interaural level difference (ILD) contributes to the generation of spatially selective auditory neurons in the owl's midbrain. Previous analyses of multiplicative responses in the owl have not taken into consideration the frequency-dependence of ITD and ILD cues that occur under natural listening conditions. Here, we present a model for the responses of ITD- and ILD-sensitive neurons in the barn owl's inferior colliculus which satisfies constraints raised by experimental data on frequency convergence, multiplicative interaction of ITD and ILD, and response properties of afferent neurons. We propose that multiplication between ITD- and ILD-dependent signals occurs only within frequency channels and that frequency integration occurs using a linear-threshold mechanism. The model reproduces the experimentally observed nonlinear responses to ITD and ILD in the inferior colliculus, with greater accuracy than previous models. We show that linear-threshold frequency integration allows the system to represent multiple sound sources with natural sound localization cues, whereas multiplicative frequency integration does not. Nonlinear responses in the owl's inferior colliculus can thus be generated using a combination of cellular and network mechanisms, showing that multiple elements of previous theories can be combined in a single system

A novel concept for dynamic adjustment of auditory space

Traditionally, the auditory system is thought to serve reliable sound localization. Stimulus-history driven feedback circuits in the early binaural pathway, however, contradict this canonical concept and raise questions about their functional significance. Here we show that stimulus-history dependent changes in absolute space perception are poorly captured by the traditional labeled-line and hemispheric-difference models of auditory space coding. We therefore developed a new decoding model incorporating recent electrophysiological findings in which sound location is initially computed in both brain hemispheres independently and combined to yield a hemispherically balanced code. This model closely captures the observed absolute localization errors caused by stimulus history, and furthermore predicts a selective dilation and compression of perceptional space. These model predictions are confirmed by improvement and degradation of spatial resolution in human listeners. Thus, dynamic perception of auditory space facilitates focal sound source segregation at the expense of absolute sound localization, questioning existing concepts of spatial hearing

Developmental alterations and electrophysiological properties

The medial superior olive (MSO) is an auditory brainstem nucleus within the superior olivary complex. Its functional role for sound source localization has been thoroughly investigated (for review see Grothe et al., 2010). However, few quantita tive data about the morphology of these neuronal coincidence detectors are available and computational models incorporating detailed reconstructions do not exist. This leaves open questions about metric characteristics of the morphology of MSO neurons as well as about electrophysiological properties that can be discovered using detailed multicompartmental models: what are the passive parameters of the membrane? What is the axial resistivity? How do dendrites integrate synaptic events? Is the medial dendrite symmetric to the lateral dendrite with respect to integration of synaptic events? This thesis has two main aspects: on the one hand, I examined the shape of a MSO neuron by developing and applying various morphological quantifications. On the other hand, I looked at the impact of morphology on basic electrophysiological properties and on characteristics of coincidence detection. As animal model I used Mongolian gerbils (Meriones unguiculatus) during the late phase of development between postnatal day 9 (P9) and 37 (P37). This period of time is of special interest, as it spans from just before hearing onset at P12 – P13 (Finck et al., 1972; Ryan et al., 1982; Smith and Kraus, 1987) to adulthood. I used single cell electroporation, microscopic reconstruction, and compartmentalization to extract anatomical parameters of MSO neurons, to quantitatively describe their morphology and development, and to establish multi-compartmental models. I found that maturation of the morphology is completed around P27, when the MSO neurons are morphologically compact and cylinder-like. Dendritic arbors become less complex between P9 and P21 as the number of branch points, the total cell length, and the amount of cell membrane decrease. Dendritic radius increases until P27 and is likely to be the main source of the increase in cell volume. In addition, I showed that in more than 85% of all MSO neurons, the axonal origin is located at the soma. I estimated the axial resistivity (80 Ω·cm) and the development of the resting conductance (total conductance during the state of resting potential) which reaches 3 mS/cm2 in adult gerbils. Applying these parameters, multi-compartmental models showed that medial versus lateral dendritic trees do not equally integrate comparable synaptic inputs. On average, latencies to peak and rise times of lateral stimulation are longer (12 μs and 5 μs, respectively) compared to medial stimulation. This is reflected in the fact that volume, surface area, and total cell length of the lateral dendritic trees are significantly more larger in comparison to the medial ones. Simplified models of MSO neurons showed that dendrites improve coincidence detection (Agmon-Snir et al., 1998; Grau-Serrat et al., 2003; Dasika et al., 2007). Here, I confirmed these findings also for multi-compartmental models with biological realistic morphologies. However, the improvement of coincidence detection by dendrites decreases during early postnatal development

Cortical transformation of spatial processing for solving the cocktail party problem: a computational model(1,2,3).

In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural time differences (ITDs) are well understood in precortical areas, how such information is reused and transformed in higher cortical regions to represent segregated sound sources is not clear. We present a computational model describing a hypothesized neural network that spans spatial cue detection areas and the cortex. This network is based on recent physiological findings that cortical neurons selectively encode target stimuli in the presence of competing maskers based on source locations (Maddox et al., 2012). We demonstrate that key features of cortical responses can be generated by the model network, which exploits spatial interactions between inputs via lateral inhibition, enabling the spatial separation of target and interfering sources while allowing monitoring of a broader acoustic space when there is no competition. We present the model network along with testable experimental paradigms as a starting point for understanding the transformation and organization of spatial information from midbrain to cortex. This network is then extended to suggest engineering solutions that may be useful for hearing-assistive devices in solving the cocktail party problem.R01 DC000100 - NIDCD NIH HHSPublished versio