Biophysical basis of the sound analog membrane potential that underlies coincidence detection in the barn owl

Interaural time difference (ITD), or the difference in timing of a sound wave arriving at the two ears, is a fundamental cue for sound localization. A wide variety of animals have specialized neural circuits dedicated to the computation of ITDs. In the avian auditory brainstem, ITDs are encoded as the spike rates in the coincidence detector neurons of the nucleus laminaris (NL). NL neurons compare the binaural phase-locked inputs from the axons of ipsi- and contralateral nucleus magnocellularis (NM) neurons. Intracellular recordings from the barn owl's NL in vivo showed that tonal stimuli induce oscillations in the membrane potential. Since this oscillatory potential resembled the stimulus sound waveform, it was named the sound analog potential (Funabiki et al., 2011). Previous modeling studies suggested that a convergence of phase-locked spikes from NM leads to an oscillatory membrane potential in NL, but how presynaptic, synaptic, and postsynaptic factors affect the formation of the sound analog potential remains to be investigated. In the accompanying paper, we derive analytical relations between these parameters and the signal and noise components of the oscillation. In this paper, we focus on the effects of the number of presynaptic NM fibers, the mean firing rate of these fibers, their average degree of phase-locking, and the synaptic time scale. Theoretical analyses and numerical simulations show that, provided the total synaptic input is kept constant, changes in the number and spike rate of NM fibers alter the ITD-independent noise whereas the degree of phase-locking is linearly converted to the ITD-dependent signal component of the sound analog potential. The synaptic time constant affects the signal more prominently than the noise, making faster synaptic input more suitable for effective ITD computation

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)

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

Release from masking: Behavioral and physiological masking level differences

Binaural hearing offers several advantages over monaural hearing and is believed to be one factor that is involved in the ability to understand speech in background noise. Binaural hearing involves analysis of interaural timing and intensity differences in signals arriving at the two ears which provides listeners with sound localization cues as well as signal in noise detection. When sounds arrive at each ear at slightly different times, there may be a release from the effects of background noise, allowing listeners to detect softer sounds in noise. Masking Level Differences (MLDs) have been widely used to evaluate behavioral binaural processing. However, the literature inconsistently reports a release from masking in physiological responses. The purposes of this study were 1) to establish the feasibility of measuring physiological masking level differences using the frequency-following response (FFR), and 2) to characterize the relationship between behavioral and physiological measures of masking level differences (MLDs). Fourteen young adults (ages 21-26) with clinically normal hearing sensitivity participated in this study. Stimuli for behavioral and physiological conditions were 500 Hz tonebursts presented in one-third octave narrowband noise. Three phase conditions were tested: SoNo, SoNπ, and SπNo. Behavioral MLDs were assessed using an adaptive 2AFC procedure. Physiological MLDs were assessed using the frequency-following response, an auditory evoked potential reliant on phase-locked neural activity. FFR analysis focused on amplitude measures. Speech-in-noise understanding was also tested using the Words-in-Noise test (WIN). Behavioral MLDs were 8.29 dB (std. dev = 4.09) for SoNπ and 10.03 dB (std. dev = 4.96) for the SπNo condition. Physiological MLDs did not indicate a robust release from masking, especially for the SπNo condition. Correlations between behavioral and physiological MLDs were not significant. However, FFR amplitude differences between having the signal, or 500 Hz tone, in phase between the ears (e.g., SoNo) and 180° out of phase (i.e., SπNo) predicted behavioral SπNo MLDs. These findings may help to clarify which scalp-recorded auditory evoked potentials reflect binaural processing in humans and report the first brainstem auditory evoked potentials in humans that can predict behavioral masking level differences

Anatomical and Physiological Characterization of the Turtle Brain Stem Auditory Circuit

The goal of this dissertation is to add to understanding of the evolution of hearing by studying the testudine taxon. This dissertation focuses on central auditory processing in the context of evolution. The experiments described are designed to give insight into how binaural hearing evolved. Follow the findings of Christensen-Dalsgaard and colleagues (2012) that an amphibious turtle had lower hearing thresholds under water than in air and that this difference is conferred by resonance of the middle ear cavity, I examined middle ear cavities across families of Testudines. I found that middle ear cavity structure and function is shared by all testudines (Willis, et al., 2013). Modern neuroanatomical tract tracing techniques were used to understand the connections among the auditory nuclei in the brain stem of the turtle. Turtles have brain stem nuclei that are connected in the same pattern as the other reptiles, including birds. These nuclei are nucleus angularis, nucleus magnocellularis, nucleus laminaris, superior olive, and torus semicircularis. Details of neuron structure were also examined and quantified. Finally, I developed an isolated head preparation that enables in vivo-like physiological recording. As proof of principle, neurons were characterized by best frequency response, threshold, phase locking. Additionally, binaurally responsive neurons were found, which have a range of interaural time difference sensitivity responses. Although the evolutionary position of testudines is not yet resolved, it is most likely that testudines share their most recent common ancestor with the archosaurs. I hypothesize that testudines likely reflect the ancestral condition of auditory processing for the archosaur clade. All experiments described in this dissertation were performed according to the guidelines approved by the Marine Biological Laboratory (Woods Hole, MA, USA), the University of Maryland Institutional Animal Care and Use Committees (IACUC) and the Danish National Animal Experimentation Board (Dyreforsøgstilsynet)