Computation of Interaural Time Difference in the Owl's Coincidence Detector Neurons

Both the mammalian and avian auditory systems localize sound sources by computing the interaural time difference (ITD) with submillisecond accuracy. The neural circuits for this computation in birds consist of axonal delay lines and coincidence detector neurons. Here, we report the first in vivo intracellular recordings from coincidence detectors in the nucleus laminaris of barn owls. Binaural tonal stimuli induced sustained depolarizations (DC) and oscillating potentials whose waveforms reflected the stimulus. The amplitude of this sound analog potential (SAP) varied with ITD, whereas DC potentials did not. The amplitude of the SAP was correlated with firing rate in a linear fashion. Spike shape, synaptic noise, the amplitude of SAP, and responsiveness to current pulses differed between cells at different frequencies, suggesting an optimization strategy for sensing sound signals in neurons tuned to different frequencies

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)

Noise reduction of coincidence detector output by the inferior colliculus of the barn owl

A recurring theme in theoretical work is that integration over populations of similarly tuned neurons can reduce neural noise. However, there are relatively few demonstrations of an explicit noise reduction mechanism in a neural network. Here we demonstrate that the brainstem of the barn owl includes a stage of processing apparently devoted to increasing the signal-to-noise ratio in the encoding of the interaural time difference (ITD), one of two primary binaural cues used to compute the position of a sound source in space. In the barn owl, the ITD is processed in a dedicated neural pathway that terminates at the core of the inferior colliculus (ICcc). The actual locus of the computation of the ITD is before ICcc in the nucleus laminaris (NL), and ICcc receives no inputs carrying information that did not originate in NL. Unlike in NL, the rate-ITD functions of ICcc neurons require as little as a single stimulus presentation per ITD to show coherent ITD tuning. ICcc neurons also displayed a greater dynamic range with a maximal difference in ITD response rates approximately double that seen in NL. These results indicate that ICcc neurons perform a computation functionally analogous to averaging across a population of similarly tuned NL neurons

Medial Superior Olivary Neurons Receive Surprisingly Few Excitatory and Inhibitory Inputs with Balanced Strength and Short-Term Dynamics

Neurons in the medial superior olive (MSO) process microsecond interaural time differences, the major cue for localizing low-frequency sounds, by comparing the relative arrival time of binaural, glutamatergic excitatory inputs. This coincidence detection mechanism is additionally shaped by highly specialized glycinergic inhibition. Traditionally, it is assumed that the binaural inputs are conveyed by many independent fibers, but such an anatomical arrangement may decrease temporal precision. Short-term depression on the other hand might enhance temporal fidelity during ongoing activity. For the first time we show that binaural coincidence detection in MSO neurons may require surprisingly few but strong inputs, challenging long-held assumptions about mammalian coincidence detection. This study exclusively uses adult gerbils for in vitro electrophysiology, single-cell electroporation and immunohistochemistry to characterize the size and short-term plasticity of inputs to the MSO. We find that the excitatory and inhibitory inputs to the MSO are well balanced both in strength and short-term dynamics, redefining this fastest of all mammalian coincidence detector circuits

Tolerance to Sound Intensity of Binaural Coincidence Detection in the Nucleus Laminaris of the Owl

Neurons of the owl's nucleus laminaris serve as coincidence detectors for measurement of interaural time difference. The discharge rate of nucleus laminaris neurons for both monaural and binaural stimulation increased with sound intensity until they reached an asymptote. Intense sounds affected neither the ratio between binaural and monaural responses nor the interaural time difference for which nucleus laminaris neurons were selective. Theoretical analysis showed that high afferent discharge rates cause coincidence detectors with only excitatory input to lose their selectivity for interaural time difference when coincidence of impulses from the same side becomes as likely as that of impulses from the two sides. We hypothesize that inhibitory input whose strength increases with sound intensity protects nucleus laminaris neurons from losing their sensitivity to interaural time difference with intense sounds

Intrinsic and Extrinsic Neuronal Mechanisms in Temporal Coding: A Further Look at Neuronal Oscillations

Many studies in recent years have been devoted to the detection of fast oscillations in the Central Nervous System (CNS), interpreting them as synchronizing devices. We should, however, refrain from associating too closely the two concepts of synchronization and oscillation. Whereas synchronization is a relatively well-defined concept, by contrast oscillation of a population of neurones in the CNS looks loosely defined, in the sense that both its frequency sharpness and the duration of the oscillatory episodes vary widely from case to case. Also, the functions of oscillations in the brain are multiple and are not confined to synchronization. The paradigmatic instantiation of oscillation in physics is given by the harmonic oscillator, a device particularly suited to tell the time, as in clocks. We will thus examine first the case of oscillations or cycling discharges of neurones, which provide a clock or impose a “tempo” for various kinds of information processing. Neuronal oscillators are rarely just clocks clicking at a fixed frequency. Instead, their frequency is often adjustable and controllable, as in the example of the “chattering cells” discovered in the superficial layers of the visual cortex. Moreover, adjustable frequency oscillators are suitable for use in “phase locked loops” (PLL) networks, a device that can convert time coding to frequency coding; such PLL units have been found in the somatosensory cortex of guinea pigs. Finally, are oscillations stricto sensu necessary to induce synchronization in the discharges of downstream neurones? We know that this is not the case, at least not for local populations of neurones. As a contribution to this question, we propose that repeating patterns in neuronal discharges production may be looked at as one such alternative solution in relation to the processing of information. We review here the case of precisely repeating triplets, detected in the discharges of olfactory mitral cells of a freely breathing rat under odor stimulation

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