Passive soma facilitates submillisecond coincidence detection in the owl's auditory system

Structure and dynamics that specialize neurons for high-frequency coincidence detection in the barn owl nucleus laminaris

A principal cue for sound source localization is the difference in arrival times of sounds at an animal's two ears (interaural time difference, ITD). Neurons that process ITDs are specialized to compare the timing of inputs with submillisecond precision. In the barn owl, ITD processing begins in the nucleus laminaris (NL) region of the auditory brain stem. Remarkably, NL neurons are sensitive to ITDs in high-frequency sounds (kilohertz-range). This contrasts with ITD-based sound localization in analogous regions in mammals where ITD sensitivity is typically restricted to lower-frequency sounds. Guided by previous experiments and modeling studies of tone-evoked responses of NL neurons, we propose NL neurons achieve high-frequency ITD sensitivity if they respond selectively to the small-amplitude, high-frequency oscillations in their inputs, and remain relatively non-responsive to mean input level. We use a biophysically based model to study the effects of soma-axon coupling on dynamics and function in NL neurons. First, we show that electrical separation of the soma from the axon region in the neuron enhances high-frequency ITD sensitivity. This soma-axon coupling configuration promotes linear subthreshold dynamics and rapid spike initiation, making the model more responsive to input oscillations, rather than mean input level. Second, we provide new evidence for the essential role of phasic dynamics for high-frequency neural coincidence detection. Transforming our model to the phasic firing mode further tunes the model to respond selectively to the oscillating inputs that carry ITD information. Similar structural and dynamical mechanisms specialize mammalian auditory brain stem neurons for ITD sensitivity, and thus, our work identifies common principles of ITD processing and neural coincidence detection across species and for sounds at widely different frequencies.

A dynamic clamp protocol to artificially modify cell capacitance

Dynamics of excitable cells and networks depend on the membrane time constant, set by membrane resistance and capacitance. Whereas pharmacological and genetic manipulations of ionic conductances of excitable membranes are routine in electrophysiology, experimental control over capacitance remains a challenge. Here, we present capacitance clamp, an approach that allows electrophysiologists to mimic a modified capacitance in biological neurons via an unconventional application of the dynamic clamp technique. We first demonstrate the feasibility to quantitatively modulate capacitance in a mathematical neuron model and then confirm the functionality of capacitance clamp in in vitro experiments in granule cells of rodent dentate gyrus with up to threefold virtual capacitance changes. Clamping of capacitance thus constitutes a novel technique to probe and decipher mechanisms of neuronal signaling in ways that were so far inaccessible to experimental electrophysiology.

Different luminance- and texture-defined contrast sensitivity profiles for school-aged children

Our current understanding of how the visual brain develops is based largely on the study of luminance-defined information processing. This approach, however, is somewhat limiting, since everyday scenes are composed of complex images, consisting of information characterized by physical attributes relating to both luminance and texture. Few studies have explored how contrast sensitivity to texture-defined information develops, particularly throughout the school-aged years. The current study investigated how contrast sensitivity to luminance- (luminance-modulated noise) and texture-defined (contrast-modulated noise) static gratings develops in school-aged children. Contrast sensitivity functions identified distinct profiles for luminance- and texture-defined gratings across spatial frequencies (SFs) and age. Sensitivity to luminance-defined gratings reached maturity in childhood by the ages of 9–10 years for all SFs (0.5, 1, 2, 4 and 8 cycles/degree or cpd). Sensitivity to texture-defined gratings reached maturity at 5–6 years for low SFs and 7–8 years for high SFs (i.e., 4 cpd). These results establish that the processing of luminance- and texture-defined information develop differently as a function of SF and age.

Diversity of Axonal and Dendritic Contributions to Neuronal Output

Our general understanding of neuronal function is that dendrites receive information that is transmitted to the axon, where action potentials (APs) are initiated and propagated to eventually trigger neurotransmitter release at synaptic terminals. Even though this canonical division of labor is true for a number of neuronal types in the mammalian brain (including neocortical and hippocampal pyramidal neurons or cerebellar Purkinje neurons), many neuronal types do not comply with this classical polarity scheme. In fact, dendrites can be the site of AP initiation and propagation, and even neurotransmitter release. In several interneuron types, all functions are carried out by dendrites as these neurons are devoid of a canonical axon. In this article, we present a few examples of "misbehaving" neurons (with a non-canonical polarity scheme) to highlight the diversity of solutions that are used by mammalian neurons to transmit information. Moreover, we discuss how the contribution of dendrites and axons to neuronal excitability may impose constraints on the morphology of these compartments in specific functional contexts.

Spikelets in pyramidal neurons: generating mechanisms, distinguishing properties, and functional implications

Spikelets are small spike-like depolarizations that are found in somatic recordings of many neuron types. Spikelets have been assigned important functions, ranging from neuronal synchronization to the regulation of synaptic plasticity, which are specific to the particular mechanism of spikelet generation. As spikelets reflect spiking activity in neuronal compartments that are electrotonically distinct from the soma, four modes of spikelet generation can be envisaged: (1) dendritic spikes or (2) axonal action potentials occurring in a single cell as well as action potentials transmitted via (3) gap junctions or (4) ephaptic coupling in pairs of neurons. In one of the best studied neuron type, cortical pyramidal neurons, the origins and functions of spikelets are still unresolved; all four potential mechanisms have been proposed, but the experimental evidence remains ambiguous. Here we attempt to reconcile the scattered experimental findings in a coherent theoretical framework. We review in detail the various mechanisms that can give rise to spikelets. For each mechanism, we present the biophysical underpinnings as well as the resulting properties of spikelets and compare these predictions to experimental data from pyramidal neurons. We also discuss the functional implications of each mechanism. On the example of pyramidal neurons, we illustrate that several independent spikelet-generating mechanisms fulfilling vastly different functions might be operating in a single cell.

Soma-axon coupling configurations that enhance neuronal coincidence detection

Coincidence detector neurons transmit timing information by responding preferentially to concurrent synaptic inputs. Principal cells of the medial superior olive (MSO) in the mammalian auditory brainstem are superb coincidence detectors. They encode sound source location with high temporal precision, distinguishing submillisecond timing differences among inputs. We investigate computationally how dynamic coupling between the input region (soma and dendrite) and the spike-generating output region (axon and axon initial segment) can enhance coincidence detection in MSO neurons. To do this, we formulate a two-compartment neuron model and characterize extensively coincidence detection sensitivity throughout a parameter space of coupling configurations. We focus on the interaction between coupling configuration and two currents that provide dynamic, voltage-gated, negative feedback in subthreshold voltage range: sodium current with rapid inactivation and low-threshold potassium current, I_KLT. These currents reduce synaptic summation and can prevent spike generation unless inputs arrive with near simultaneity. We show that strong soma-to-axon coupling promotes the negative feedback effects of sodium inactivation and is, therefore, advantageous for coincidence detection. Furthermore, the feedforward combination of strong soma-to-axon coupling and weak axon-to-soma coupling enables spikes to be generated efficiently (few sodium channels needed) and with rapid recovery that enhances high-frequency coincidence detection. These observations detail the functional benefit of the strongly feedforward configuration that has been observed in physiological studies of MSO neurons. We find that I_KLT further enhances coincidence detection sensitivity, but with effects that depend on coupling configuration. For instance, in models with weak soma-to-axon and weak axon-to-soma coupling, I_KLT in the axon enhances coincidence detection more effectively than I_KLT in the soma. By using a minimal model of soma-to-axon coupling, we connect structure, dynamics, and computation. Although we consider the particular case of MSO coincidence detectors, our method for creating and exploring a parameter space of two-compartment models can be applied to other neurons.

Brain cells (neurons) are spatially extended structures. The locations at which neurons receive inputs and generate outputs are often distinct. We formulate and study a minimal mathematical model that describes the dynamical coupling between the input and output regions of a neuron. We construct our model to reflect known properties of neurons in the auditory brainstem that play an important role in our ability to locate sound sources. These neurons are known as coincidence detectors because they are most likely to respond when they receive simultaneous inputs. We use simulations to explore coincidence detection sensitivity throughout the parameter space of input-output coupling and to identify the coupling configurations that are best for neural coincidence detection. We find that strong forward coupling (from input region to output region), enhances coincidence detection sensitivity in our model and that low-threshold potassium current further improves coincidence detection. Our study is significant in that we detail how cell structure affects neuronal dynamics and, consequently, the ability of neurons to perform as temporally-precise coincidence detectors.

Dynamics of synaptic extracellular field potentials in the nucleus laminaris of the barn owl

Synaptic currents are frequently assumed to make a major contribution to the extracellular field potential (EFP). However, in any neuronal population, the explicit separation of synaptic sources from other contributions such as postsynaptic spikes remains a challenge. Here we take advantage of the simple organization of the barn owl nucleus laminaris (NL) in the auditory brain stem to isolate synaptic currents through the iontophoretic application of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-receptor antagonist 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo[ f]quinoxaline-7-sulfonamide (NBQX). Responses to auditory stimulation show that the temporal dynamics of the evoked synaptic contributions to the EFP are consistent with synaptic short-term depression (STD). The estimated time constants of an STD model fitted to the data are similar to the fast time constants reported from in vitro experiments in the chick. Overall, the putative synaptic EFPs in the barn owl NL are significant but small (<1% change of the variance by NBQX). This result supports the hypothesis that the EFP in NL is generated mainly by axonal spikes, in contrast to most other neuronal systems. NEW & NOTEWORTHY Synaptic currents are assumed to make a major contribution to the extracellular field potential in the brain, but it is hard to directly isolate these synaptic components. Here we take advantage of the simple organization of the barn owl nucleus laminaris in the auditory brain stem to isolate synaptic currents through the iontophoretic application of a synaptic blocker. We show that the responses are consistent with a simple model of short-term synaptic depression.

Physiological models of the lateral superior olive

In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD), which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO) in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi- and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones (‘shot-noise’ models) to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type). These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1) that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2) that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub-neuronal nonlinear processes play important roles, and (3) that, for general purposes, intermediate models might be a reasonable compromise between simplicity and biological plausibility.

Computational models help our understanding of complex biological systems, by identifying their key elements and revealing their operational principles. Close comparisons between model predictions and empirical observations ensure our confidence in a model as a building block for further applications. Most current neuronal models, however, are constructed to replicate only a small specific set of experimental data. Thus, it is usually unclear how these models can be generalized to different datasets and how they compare with each other. In this paper, seven neuronal models are examined that are designed to reproduce known physiological characteristics of auditory neurons involved in the detection of sound source location. Despite their different levels of complexity, the models generate largely similar results when their parameters are tuned with common criteria. Comparisons show that simple models are computationally more efficient and theoretically transparent, and therefore suitable for rigorous mathematical analyses and engineering applications including real-time simulations. In contrast, complex models are necessary for investigating the relationship between underlying biophysical processes and sub- and suprathreshold spiking properties, although they have a large number of unconstrained, unverified parameters. Having identified their advantages and drawbacks, these auditory neuron models may readily be used for future studies and applications.

Contribution of action potentials to the extracellular field potential in the nucleus laminaris of barn owl

Extracellular field potentials (EFP) are widely used to evaluate in vivo neural activity, but identification of multiple sources and their relative contributions is often ambiguous, making the interpretation of the EFP difficult. We have therefore analyzed a model EFP from a simple brainstem circuit with separable pre- and postsynaptic components to determine whether we could isolate its sources. Our previous papers had shown that the barn owl neurophonic largely originates with spikes from input axons and synapses that terminate on the neurons in the nucleus laminaris (NL) (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010; Kuokkanen PT, Ashida G, Carr CE, Wagner H, Kempter R. J Neurophysiol 110: 117-130, 2013; McColgan T, Liu J, Kuokkanen PT, Carr CE, Wagner H, Kempter R. eLife 6: e26106, 2017). To determine how much the postsynaptic NL neurons contributed to the neurophonic, we recorded EFP responses in NL in vivo. Power spectral analyses showed that a small spectral component of the evoked response, between 200 and 700 Hz, could be attributed to the NL neurons' spikes, while nucleus magnocellularis (NM) spikes dominate the EFP at frequencies ≳1 kHz. Thus, spikes of NL neurons and NM axons contribute to the EFP in NL in distinct frequency bands. We conclude that if the spectral components of source types are different and if their activities can be selectively modulated, the identification of EFP sources is possible. NEW & NOTEWORTHY Extracellular field potentials (EFPs) generate clinically important signals, but their sources are incompletely understood. As a model, we have analyzed the auditory neurophonic in the barn owl's nucleus laminaris. There the EFP originates predominantly from spiking in the afferent axons, with spectral power ≳1 kHz, while postsynaptic laminaris neurons contribute little. In conclusion, the identification of EFP sources is possible if they have different spectral components and if their activities can be modulated selectively.

Low Somatic Sodium Conductance Enhances Action Potential Precision in Time-Coding Auditory Neurons

Auditory nerve fibers encode sounds in the precise timing of action potentials (APs), which is used for such computations as sound localization. Timing information is relayed through several cell types in the auditory brainstem that share an unusual property: their APs are not overshooting, suggesting that the cells have very low somatic sodium conductance (g_Na). However, it is not clear how g_Na influences temporal precision. We addressed this by comparing bushy cells (BCs) in the mouse cochlear nucleus with T-stellate cells (SCs), which do have normal overshooting APs. BCs play a central role in both relaying and refining precise timing information from the auditory nerve, whereas SCs discard precise timing information and encode the envelope of sound amplitude. Nucleated-patch recording at near-physiological temperature indicated that the Na current density was 62% lower in BCs, and the voltage dependence of g_Na inactivation was 13 mV hyperpolarized compared with SCs. We endowed BCs with SC-like g_Na using two-electrode dynamic clamp and found that synaptic activity at physiologically relevant rates elicited APs with significantly lower probability, through increased activation of delayed rectifier channels. In addition, for two near-simultaneous synaptic inputs, the window of coincidence detection widened significantly with increasing g_Na, indicating that refinement of temporal information by BCs is degraded by g_Na Thus, reduced somatic g_Na appears to be an adaption for enhancing fidelity and precision in time-coding neurons.

SIGNIFICANCE STATEMENT

Proper hearing depends on analyzing temporal aspects of sounds with high precision. Auditory neurons that specialize in precise temporal information have a suite of unusual intrinsic properties, including nonovershooting action potentials and few sodium channels in the soma. However, it was not clear how low sodium channel availability in the soma influenced the temporal precision of action potentials initiated in the axon initial segment. We studied this using dynamic clamp to mimic sodium channels in the soma, which yielded normal, overshooting action potentials. Increasing somatic sodium conductance had major negative consequences: synaptic activity evoked action potentials with lower fidelity, and the precision of coincidence detection was degraded. Thus, low somatic sodium channel availability appears to enhance fidelity and temporal precision.

Spikelets in Pyramidal Neurons: Action Potentials Initiated in the Axon Initial Segment That Do Not Activate the Soma

Spikelets are small spike-like depolarizations that can be measured in somatic intracellular recordings. Their origin in pyramidal neurons remains controversial. To explain spikelet generation, we propose a novel single-cell mechanism: somato-dendritic input generates action potentials at the axon initial segment that may fail to activate the soma and manifest as somatic spikelets. Using mathematical analysis and numerical simulations of compartmental neuron models, we identified four key factors controlling spikelet generation: (1) difference in firing threshold, (2) impedance mismatch, and (3) electrotonic separation between the soma and the axon initial segment, as well as (4) input amplitude. Because spikelets involve forward propagation of action potentials along the axon while they avoid full depolarization of the somato-dendritic compartments, we conjecture that this mode of operation saves energy and regulates dendritic plasticity while still allowing for a read-out of results of neuronal computations.

Action potentials (APs) are digital, all-or-none signals by which neurons communicate with each other. Therefore, APs are the basis of neural function, yet some of their fundamental features are still not well understood. Here we focus on pyramidal cells, which are the principal neurons in neocortex and hippocampus. According to textbook knowledge, an AP in pyramidal neurons is initiated at the axon initial segment and propagates along the axon to the next cell. Concurrently, the AP also propagates back to the soma and into the dendrites where it might trigger synaptic plasticity, which is the basis of learning and memory. However, besides APs, pyramidal cells sometimes also show somatic spikelets—small depolarizations with an AP-like shape—whose origin remains unclear. Here, we propose that spikelets occur when an AP initiated at the axon initial segment only propagates down the axon, but fails to activate sodium currents in the soma and dendrites. As a result, spikelet firing saves energy, and moreover, might be a means to control synaptic plasticity and thereby control learning and memory.

Dipolar extracellular potentials generated by axonal projections

Extracellular field potentials (EFPs) are an important source of information in neuroscience, but their physiological basis is in many cases still a matter of debate. Axonal sources are typically discounted in modeling and data analysis because their contributions are assumed to be negligible. Here, we established experimentally and theoretically that contributions of axons to EFPs can be significant. Modeling action potentials propagating along axons, we showed that EFPs were prominent in the presence of terminal zones where axons branch and terminate in close succession, as found in many brain regions. Our models predicted a dipolar far field and a polarity reversal at the center of the terminal zone. We confirmed these predictions using EFPs from the barn owl auditory brainstem where we recorded in nucleus laminaris using a multielectrode array. These results demonstrate that axonal terminal zones can produce EFPs with considerable amplitude and spatial reach.

High-Frequency Resonance in the Gerbil Medial Superior Olive

A high-frequency, subthreshold resonance in the guinea pig medial superior olive (MSO) was recently linked to the efficient extraction of spatial cues from the fine structure of acoustic stimuli. We report here that MSO neurons in gerbil also have resonant properties and, based on our whole-cell recordings and computational modeling, that a low-voltage-gated potassium current, I_KLT, underlies the resonance. We show that resonance was lost following dynamic clamp replacement of I_KLT with a leak conductance and in the model when voltage-gating of I_KLT was suppressed. Resonance was characterized using small amplitude sinusoidal stimuli to generate impedance curves as typically done for linear systems analysis. Extending our study into the nonlinear, voltage-dependent regime, we increased stimulus amplitude and found, experimentally and in simulations, that the subthreshold resonant frequency (242Hz for weak stimuli) increased continuously to the resonant frequency for spiking (285Hz). The spike resonance of these phasic-firing (type III excitable) MSO neurons and of the model is of particular interest also because previous studies of resonance typically involved neurons/models (type II excitable, such as the standard Hodgkin-Huxley model) that can fire tonically for steady inputs. To probe more directly how these resonances relate to MSO neurons as slope-detectors, we presented periodic trains of brief, fast-rising excitatory post-synaptic potentials (EPSCs) to the model. While weak subthreshold EPSC trains were essentially low-pass filtered, resonance emerged as EPSC amplitude increased. Interestingly, for spike-evoking EPSC trains, the threshold amplitude at spike resonant frequency (317Hz) was lower than the single ESPC threshold. Our finding of a frequency-dependent threshold for repetitive brief EPSC stimuli and preferred frequency for spiking calls for further consideration of both subthreshold and suprathreshold resonance to fast and precise temporal processing in the MSO.

Principal neurons of the medial superior olive (MSO) are fast and precise coincidence detectors involved in the neuronal computation of sound localization. We show that they exhibit resonance properties in vitro, responding to small oscillatory inputs, maximally at preferred frequencies. Their resonant frequencies are high, nearly a hundred-fold that found in cortical or hippocampal neurons. We used electrophysiological recordings (gerbil MSO) and computational modelling to identify the key biophysical factors for this fast resonance: a low-threshold potassium current, I_KLT, whose activation time constant is slightly slower than the membrane time constant (τ_m < 1ms). An MSO neuron’s resonant frequency increases with stimulus amplitude and approaches the preferred frequency at which spiking is elicited with the lowest stimulus amplitude. This relationship between subthreshold and suprathreshold resonances also holds for trains of brief synaptic-like inputs in our neuron model, even though responses for weak subthreshold synaptic inputs are low-pass filtered. Our results demonstrate the important effects of stimulus amplitude and waveform, and I_KLT, on measurements of impedance and therefore resonance. In addition, our data highlight the possibility that even brief synaptic input may be selectively filtered by the intrinsic biophysical properties of MSO neurons.

Detection of transient synchrony across oscillating receptors by the central electrosensory system of mormyrid fish

Recently, we reported evidence for a novel mechanism of peripheral sensory coding based on oscillatory synchrony. Spontaneously oscillating electroreceptors in weakly electric fish (Mormyridae) respond to electrosensory stimuli with a phase reset that results in transient synchrony across the receptor population (Baker et al., 2015). Here, we asked whether the central electrosensory system actually detects the occurrence of synchronous oscillations among receptors. We found that electrosensory stimulation elicited evoked potentials in the midbrain exterolateral nucleus at a short latency following receptor synchronization. Frequency tuning in the midbrain resembled peripheral frequency tuning, which matches the intrinsic oscillation frequencies of the receptors. These frequencies are lower than those in individual conspecific signals, and instead match those found in collective signals produced by groups of conspecifics. Our results provide further support for a novel mechanism for sensory coding based on the detection of oscillatory synchrony among peripheral receptors.

DOI:http://dx.doi.org/10.7554/eLife.16851.001

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.

Minimal conductance-based model of auditory coincidence detector neurons

Sound localization is a fundamental sensory function of a wide variety of animals. The interaural time difference (ITD), an important cue for sound localization, is computed in the auditory brainstem. In our previous modeling study, we introduced a two-compartment Hodgkin-Huxley type model to investigate how cellular and synaptic specializations may contribute to precise ITD computation of the barn owl's auditory coincidence detector neuron. Although our model successfully reproduced fundamental physiological properties observed in vivo, it was unsuitable for mathematical analyses and large scale simulations because of a number of nonlinear variables. In the present study, we reduce our former model into three types of conductance-based integrate-and-fire (IF) models. We test their electrophysiological properties using data from published in vivo and in vitro studies. Their robustness to parameter changes and computational efficiencies are also examined. Our numerical results suggest that the single-compartment active IF model is superior to other reduced models in terms of physiological reproducibility and computational performance. This model will allow future theoretical studies that use more rigorous mathematical analysis and network simulations.

Subthreshold membrane currents confer distinct tuning properties that enable neurons to encode the integral or derivative of their input

Neurons rely on action potentials, or spikes, to encode information. But spikes can encode different stimulus features in different neurons. We show here through simulations and experiments how neurons encode the integral or derivative of their input based on the distinct tuning properties conferred upon them by subthreshold currents. Slow-activating subthreshold inward (depolarizing) current mediates positive feedback control of subthreshold voltage, sustaining depolarization and allowing the neuron to spike on the basis of its integrated stimulus waveform. Slow-activating subthreshold outward (hyperpolarizing) current mediates negative feedback control of subthreshold voltage, truncating depolarization and forcing the neuron to spike on the basis of its differentiated stimulus waveform. Depending on its direction, slow-activating subthreshold current cooperates or competes with fast-activating inward current during spike initiation. This explanation predicts that sensitivity to the rate of change of stimulus intensity differs qualitatively between integrators and differentiators. This was confirmed experimentally in spinal sensory neurons that naturally behave as specialized integrators or differentiators. Predicted sensitivity to different stimulus features was confirmed by covariance analysis. Integration and differentiation, which are themselves inverse operations, are thus shown to be implemented by the slow feedback mediated by oppositely directed subthreshold currents expressed in different neurons.

Action potential generation in an anatomically constrained model of medial superior olive axons

Neurons in the medial superior olive (MSO) encode interaural time differences (ITDs) with sustained firing rates of >100 Hz. They are able to generate such high firing rates for several hundred milliseconds despite their extremely low-input resistances of only few megaohms and high synaptic conductances in vivo. The biophysical mechanisms by which these leaky neurons maintain their excitability are not understood. Since action potentials (APs) are usually assumed to be generated in the axon initial segment (AIS), we analyzed anatomical data of proximal MSO axons in Mongolian gerbils and found that the axon diameter is <1 μm and the internode length is ∼100 μm. Using a morphologically constrained computational model of the MSO axon, we show that these thin axons facilitate the excitability of the AIS. However, for ongoing high rates of synaptic inputs the model generates a substantial fraction of APs in its nodes of Ranvier. These distally initiated APs are mediated by a spatial gradient of sodium channel inactivation and a strong somatic current sink. The model also predicts that distal AP initiation increases the dynamic range of the rate code for ITDs.

Neuronal specializations for the processing of interaural difference cues in the chick

Sound information is encoded as a series of spikes of the auditory nerve fibers (ANFs), and then transmitted to the brainstem auditory nuclei. Features such as timing and level are extracted from ANFs activity and further processed as the interaural time difference (ITD) and the interaural level difference (ILD), respectively. These two interaural difference cues are used for sound source localization by behaving animals. Both cues depend on the head size of animals and are extremely small, requiring specialized neural properties in order to process these cues with precision. Moreover, the sound level and timing cues are not processed independently from one another. Neurons in the nucleus angularis (NA) are specialized for coding sound level information in birds and the ILD is processed in the posterior part of the dorsal lateral lemniscus nucleus (LLDp). Processing of ILD is affected by the phase difference of binaural sound. Temporal features of sound are encoded in the pathway starting in nucleus magnocellularis (NM), and ITD is processed in the nucleus laminaris (NL). In this pathway a variety of specializations are found in synapse morphology, neuronal excitability, distribution of ion channels and receptors along the tonotopic axis, which reduces spike timing fluctuation in the ANFs-NM synapse, and imparts precise and stable ITD processing to the NL. Moreover, the contrast of ITD processing in NL is enhanced over a wide range of sound level through the activity of GABAergic inhibitory systems from both the superior olivary nucleus (SON) and local inhibitory neurons that follow monosynaptic to NM activity.

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).

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.

Linear summation in the barn owl's brainstem underlies responses to interaural time differences

The neurophonic potential is a synchronized frequency-following extracellular field potential that can be recorded in the nucleus laminaris (NL) in the brainstem of the barn owl. Putative generators of the neurophonic are the afferent axons from the nucleus magnocellularis, synapses onto NL neurons, and spikes of NL neurons. The outputs of NL, i.e., action potentials of NL neurons, are only weakly represented in the neurophonic. Instead, the inputs to NL, i.e., afferent axons and their synaptic potentials, are the predominant origin of the neurophonic (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010). Thus in NL the monaural inputs from the two brain sides converge and create a binaural neurophonic. If these monaural inputs contribute independently to the extracellular field, the response to binaural stimulation can be predicted from the sum of the responses to ipsi- and contralateral stimulation. We found that a linear summation model explains the dependence of the responses on interaural time difference as measured experimentally with binaural stimulation. The fit between model predictions and data was excellent, even without taking into account the nonlinear responses of NL coincidence detector neurons, although their firing rate and synchrony strongly depend on the interaural time difference. These results are consistent with the view that the afferent axons and their synaptic potentials in NL are the primary origin of the neurophonic.

Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245-15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

Auditory neuroscience: how to encode microsecond differences

Minute differences between the time of arrival of a sound at the two ears are used by humans and animals to locate the source. New in vivo recordings have shed light on how auditory neurons solve the problem of resolving microsecond time differences.

Control of neuronal excitability by NMDA-type glutamate receptors in early developing binaural auditory neurons

Precise control of neuronal excitability in the auditory brainstem is fundamental for processing timing cues used for sound localization and signal discrimination in complex acoustic environments. In mature nucleus laminaris (NL), the first nucleus responsible for binaural processing in chickens, neuronal excitability is governed primarily by voltage-activated potassium conductances (K(VA)). High levels of K(VA) expression in NL neurons result in one or two initial action potentials (APs) in response to high-frequency synaptic activity or sustained depolarization. Here we show that during a period of synaptogenesis and circuit refinement, before hearing onset, K(VA) conductances are relatively small, in particular low-voltage-activated K(+) conductances (K(LVA)). In spite of this, neuronal output is filtered and repetitive synaptic activity generates only one or two initial APs during a train of stimuli. During this early developmental time period, synaptic NMDA-type glutamate receptors (NMDA-Rs) contain primarily the GluN2B subunit. We show that the slow decay kinetics of GluN2B-containing NMDA-Rs allows synaptic responses to summate, filtering the output of NL neurons before intrinsic properties are fully developed. Weaker Mg(2+) blockade of NMDA-Rs and ambient glutamate early in development generate a tonic NMDA-R-mediated current that sets the membrane potential at more depolarized values. Small KLVA conductances, localized in dendrites, prevent excessive depolarization caused by tonic activation of NMDA-Rs. Thus, before intrinsic properties are fully developed, NMDA-Rs control the output of NL neurons during evoked synaptic transmission.

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.

Kv1 channels control spike threshold dynamics and spike timing in cortical pyramidal neurones

Previous studies showed that cortical pyramidal neurones (PNs) have a dynamic spike threshold that functions as a high-pass filter, enhancing spike timing in response to high-frequency input. While it is commonly assumed that Na(+) channel inactivation is the primary mechanism of threshold accommodation, the possible role of K(+) channel activation in fast threshold changes has not been well characterized. The present study tested the hypothesis that low-voltage activated Kv1 channels affect threshold dynamics in layer 2-3 PNs, using α-dendrotoxin (DTX) or 4-aminopyridine (4-AP) to block these conductances. We found that Kv1 blockade reduced the dynamic changes of spike threshold in response to a variety of stimuli, including stimulus-evoked synaptic input, current steps and ramps of varied duration, and noise. Analysis of the responses to noise showed that Kv1 channels increased the coherence of spike output with high-frequency components of the stimulus. A simple model demonstrates that a dynamic spike threshold can account for this effect. Our results show that the Kv1 conductance is a major mechanism that contributes to the dynamic spike threshold and precise spike timing of cortical PNs.

Sound localization: Jeffress and beyond

Many animals use the interaural time differences (ITDs) to locate the source of low frequency sounds. The place coding theory proposed by Jeffress has long been a dominant model to account for the neural mechanisms of ITD detection. Recent research, however, suggests a wider range of strategies for ITD coding in the binaural auditory brainstem. We discuss how ITD is coded in avian, mammalian, and reptilian nervous systems, and review underlying synaptic and cellular properties that enable precise temporal computation. The latest advances in recording and analysis techniques provide powerful tools for both overcoming and utilizing the large field potentials in these nuclei.

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.

On the origin of the extracellular field potential in the nucleus laminaris of the barn owl (Tyto alba)

The neurophonic is a sound-evoked, frequency-following potential that can be recorded extracellularly in nucleus laminaris of the barn owl. The origin of the neurophonic, and thus the mechanisms that give rise to its exceptional temporal precision, has not yet been identified. Putative generators of the neurophonic are the activity of afferent axons, synaptic activation of laminaris neurons, or action potentials in laminaris neurons. To identify the generators, we analyzed the neurophonic in the high-frequency (>2.5 kHz) region of nucleus laminaris in response to monaural pure-tone stimulation. The amplitude of the neurophonic is typically in the millivolt range. The signal-to-noise ratio reaches values beyond 30 dB. To assess which generators could give rise to these large, synchronous extracellular potentials, we developed a computational model. Spike trains were produced by an inhomogeneous Poisson process and convolved with a spike waveform. The model explained the dependence of the simulated neurophonic on parameters such as the mean rate, the vector strength of phase locking, the number of statistically independent sources, and why the signal-to-noise ratio is independent of the spike waveform and subsequent filtering of the signal. We found that several hundred sources are needed to reach the observed signal-to-noise ratio. The summed coherent signal from the densely packed afferent axons and activation of their synapses on laminaris neurons are alone sufficient to explain the measured properties of the neurophonic.

Control of submillisecond synaptic timing in binaural coincidence detectors by K(v)1 channels

Neurons in the medial superior olive process sound-localization cues via binaural coincidence detection, in which excitatory synaptic inputs from each ear are segregated onto different branches of a bipolar dendritic structure and summed at the soma and axon with submillisecond time resolution. Although synaptic timing and dynamics critically shape this computation, synaptic interactions with intrinsic ion channels have received less attention. Using paired somatic and dendritic patch-clamp recordings in gerbil brainstem slices together with compartmental modeling, we found that activation of K(v)1 channels by dendritic excitatory postsynaptic potentials (EPSPs) accelerated membrane repolarization in a voltage-dependent manner and actively improved the time resolution of synaptic integration. We found that a somatically biased gradient of K(v)1 channels underlies the degree of compensation for passive cable filtering during propagation of EPSPs in dendrites. Thus, both the spatial distribution and properties of K(v)1 channels are important for preserving binaural synaptic timing.

Tonotopic tuning in a sound localization circuit

Nucleus laminaris (NL) neurons encode interaural time difference (ITD), the cue used to localize low-frequency sounds. A physiologically based model of NL input suggests that ITD information is contained in narrow frequency bands around harmonics of the sound frequency. This suggested a theory, which predicts that, for each tone frequency, there is an optimal time course for synaptic inputs to NL that will elicit the largest modulation of NL firing rate as a function of ITD. The theory also suggested that neurons in different tonotopic regions of NL require specialized tuning to take advantage of the input gradient. Tonotopic tuning in NL was investigated in brain slices by separating the nucleus into three regions based on its anatomical tonotopic map. Patch-clamp recordings in each region were used to measure both the synaptic and the intrinsic electrical properties. The data revealed a tonotopic gradient of synaptic time course that closely matched the theoretical predictions. We also found postsynaptic band-pass filtering. Analysis of the combined synaptic and postsynaptic filters revealed a frequency-dependent gradient of gain for the transformation of tone amplitude to NL firing rate modulation. Models constructed from the experimental data for each tonotopic region demonstrate that the tonotopic tuning measured in NL can improve ITD encoding across sound frequencies.

Reliability and precision of the mouse calyx of Held synapse

Traditionally, the calyx of Held synapse is viewed as a highly reliable relay in the sound localization circuit of the auditory brainstem, with every presynaptic action potential triggering a postsynaptic action potential in vivo. However, this view is at odds with slice recordings that report large short-term depression (STD). To investigate the reliability and precision of this synapse, we compared slice and in vivo recordings from medial nucleus of the trapezoid body neurons of young adult mice. We show that the extracellularly recorded complex waveform can be used to estimate both presynaptic release and postsynaptic excitability. Whereas under standard slice conditions the synapse underwent large STD, both extracellular and whole-cell recordings indicated that in vivo the size of the EPSPs was independent of recent history. The estimated quantal content was typically <20 in vivo, much lower than in the resting synapse under standard slice conditions. However, due to the large quantal size and summation of EPSPs, the safety factor of this synapse was generally still sufficiently large and postsynaptic failures were observed only infrequently in vivo. When present, failures were typically due to stochastic fluctuations in EPSP size or postsynaptic spike depression. In vivo, the calyx of Held synapse thus functions as a tonic synapse. The price it pays for its low release probability is an increase in jitter and synaptic latency and occasional postsynaptic failures.

Detection of interaural time differences in the alligator

The auditory systems of birds and mammals use timing information from each ear to detect interaural time difference (ITD). To determine whether the Jeffress-type algorithms that underlie sensitivity to ITD in birds are an evolutionarily stable strategy, we recorded from the auditory nuclei of crocodilians, who are the sister group to the birds. In alligators, precisely timed spikes in the first-order nucleus magnocellularis (NM) encode the timing of sounds, and NM neurons project to neurons in the nucleus laminaris (NL) that detect interaural time differences. In vivo recordings from NL neurons show that the arrival time of phase-locked spikes differs between the ipsilateral and contralateral inputs. When this disparity is nullified by their best ITD, the neurons respond maximally. Thus NL neurons act as coincidence detectors. A biologically detailed model of NL with alligator parameters discriminated ITDs up to 1 kHz. The range of best ITDs represented in NL was much larger than in birds, however, and extended from 0 to 1000 micros contralateral, with a median ITD of 450 micros. Thus, crocodilians and birds employ similar algorithms for ITD detection, although crocodilians have larger heads.

The modulation by intensity of the processing of interaural timing cues for localizing sounds

Features of sounds such as time and intensity are important binaural cues for localizing their sources. Interaural time differences (ITDs) and interaural level differences are extracted and processed in parallel by separate pathways in the brainstem auditory nuclei. ITD cues are small, particularly in small-headed animals, and processing of these cues is optimized by both morphological and physiological specializations. Moreover, recent observations in mammals and in some birds indicate that interaural time and level cues are not processed independently but cooperatively to improve the detection of interaural differences. This review will specifically summarize what is known about how inhibitory circuits improve the measurements of ITD in a sound-level-dependent manner.

Bilateral matching of frequency tuning in neural cross-correlators of the owl

Sound localization requires comparison between the inputs to the left and right ears. One important aspect of this comparison is the differences in arrival time to each side, also called interaural time difference (ITD). A prevalent model of ITD detection, consisting of delay lines and coincidence-detector neurons, was proposed by Jeffress (J Comp Physiol Psychol 41:35-39, 1948). As an extension of the Jeffress model, the process of detecting and encoding ITD has been compared to an effective cross-correlation between the input signals to the two ears. Because the cochlea performs a spectrotemporal decomposition of the input signal, this cross-correlation takes place over narrow frequency bands. Since the cochlear tonotopy is arranged in series, sounds of different frequencies will trigger neural activity with different temporal delays. Thus, the matching of the frequency tuning of the left and right inputs to the cross-correlator units becomes a 'timing' issue. These properties of auditory transduction gave theoretical support to an alternative model of ITD-detection based on a bilateral mismatch in frequency tuning, called the 'stereausis' model. Here we first review the current literature on the owl's nucleus laminaris, the equivalent to the medial superior olive of mammals, which is the site where ITD is detected. Subsequently, we use reverse correlation analysis and stimulation with uncorrelated sounds to extract the effective monaural inputs to the cross-correlator neurons. We show that when the left and right inputs to the cross-correlators are defined in this manner, the computation performed by coincidence-detector neurons satisfies conditions of cross-correlation theory. We also show that the spectra of left and right inputs are matched, which is consistent with predictions made by the classic model put forth by Jeffress.

On hearing with more than one ear: lessons from evolution

Although ears capable of detecting airborne sound have arisen repeatedly and independently in different species, most animals that are capable of hearing have a pair of ears. We review the advantages that arise from having two ears and discuss recent research on the similarities and differences in the binaural processing strategies adopted by birds and mammals. We also ask how these different adaptations for binaural and spatial hearing might inform and inspire the development of techniques for future auditory prosthetic devices.

Maps of interaural time difference in the chicken's brainstem nucleus laminaris

Animals, including humans, use interaural time differences (ITDs) that arise from different sound path lengths to the two ears as a cue of horizontal sound source location. The nature of the neural code for ITD is still controversial. Current models differentiate between two population codes: either a map-like rate-place code of ITD along an array of neurons, consistent with a large body of data in the barn owl, or a population rate code, consistent with data from small mammals. Recently, it was proposed that these different codes reflect optimal coding strategies that depend on head size and sound frequency. The chicken makes an excellent test case of this proposal because its physical prerequisites are similar to small mammals, yet it shares a more recent common ancestry with the owl. We show here that, like in the barn owl, the brainstem nucleus laminaris in mature chickens displayed the major features of a place code of ITD. ITD was topographically represented in the maximal responses of neurons along each isofrequency band, covering approximately the contralateral acoustic hemisphere. Furthermore, the represented ITD range appeared to change with frequency, consistent with a pressure gradient receiver mechanism in the avian middle ear. At very low frequencies, below 400 Hz, maximal neural responses were symmetrically distributed around zero ITD and it remained unclear whether there was a topographic representation. These findings do not agree with the above predictions for optimal coding and thus revive the discussion as to what determines the neural coding strategies for ITDs.

Cellular and molecular mechanisms of avian auditory coincidence detection

Sound localization along the horizontal plane begins with comparing sound arrival times at the two ears in the brainstem coincidence detector neurons. Coincidence detectors are functionally as well as morphologically specialized depending on the frequency of sounds that they handle, and the expression of various channel molecules underlies these specializations. Some voltage-gated K(+) channels determine the acuity of coincidence detection, and are expressed most abundantly in the middle-frequency-coding neurons. Some hyperpolarization-activated channels are dominant in the high-frequency-coding neurons, and enable a delicate modulation of coincidence detection by noradrenalin. Axonal clustering of Na(+) channels is also frequency-dependent, and optimizes the coincidence detection. This article aims to provide an overview of recent findings in the cellular and molecular mechanisms of auditory coincidence detection in birds.

Neural networks a century after Cajal

At the time of Golgi and Cajal's reception of the Nobel Prize in 1906 most scientists had accepted the notion that neurons are independent units. Although neuroscientists today still believe that neurons are independent anatomical units, functionally, it is thought that some sort of population coding occurs. Throughout this essay, we provide evidence that suggests that populations of neurons can code information through the synchronization of their responses. This synchronization occurs at several levels in the brain. Whereas spike synchrony refers to the correlation between spikes of different neurons' spike trains, oscillatory synchrony refers to the synchronization of oscillatory responses, generally among large groups of neurons. In the first section of this essay we describe the dependence of the brain's developmental processes on synchronous firing and how these processes form a brain that supports and is sensitive to synchronous spikes. Data are then presented that suggest that spike and oscillatory synchrony may serve as useful neural codes. Examples from sensory (auditory, olfactory and somatosensory), motor and higher cognitive (attention, memory) systems are then presented to illustrate potential roles for these synchronous codes in normal brain function. Results from these studies collectively suggest that spike synchrony in sensory and motor systems may provide detail information not available from changes in firing rate. Oscillatory synchrony, on the other hand, may be globally involved in the coordination of long-distance neuronal communication during higher cognitive processes. These concepts represent a dramatic shift in direction since the times of Golgi and Cajal.