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

Dual Coding of Frequency Modulation in the Ventral Cochlear Nucleus.

Frequency modulation (FM) is a common acoustic feature of natural sounds and is known to play a role in robust sound source recognition. Auditory neurons show precise stimulus-synchronized discharge patterns that may be used for the representation of low-rate FM. However, it remains unclear whether this representation is based on synchronization to slow temporal envelope (ENV) cues resulting from cochlear filtering or phase locking to faster temporal fine structure (TFS) cues. To investigate the plausibility of those encoding schemes, single units of the ventral cochlear nucleus of guinea pigs of either sex were recorded in response to sine FM tones centered at the unit's best frequency (BF). The results show that, in contrast to high-BF units, for modulation depths within the receptive field, low-BF units (<4 kHz) demonstrate good phase locking to TFS. For modulation depths extending beyond the receptive field, the discharge patterns follow the ENV and fluctuate at the modulation rate. The receptive field proved to be a good predictor of the ENV responses for most primary-like and chopper units. The current in vivo data also reveal a high level of diversity in responses across unit types. TFS cues are mainly conveyed by low-frequency and primary-like units and ENV cues by chopper and onset units. The diversity of responses exhibited by cochlear nucleus neurons provides a neural basis for a dual-coding scheme of FM in the brainstem based on both ENV and TFS cues.SIGNIFICANCE STATEMENT Natural sounds, including speech, convey informative temporal modulations in frequency. Understanding how the auditory system represents those frequency modulations (FM) has important implications as robust sound source recognition depends crucially on the reception of low-rate FM cues. Here, we recorded 115 single-unit responses from the ventral cochlear nucleus in response to FM and provide the first physiological evidence of a dual-coding mechanism of FM via synchronization to temporal envelope cues and phase locking to temporal fine structure cues. We also demonstrate a diversity of neural responses with different coding specializations. These results support the dual-coding scheme proposed by psychophysicists to account for FM sensitivity in humans and provide new insights on how this might be implemented in the early stages of the auditory pathway

Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficient coding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform - Independent Component Analysis (ICA) trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment.Comment: 22 pages, 9 figure

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)

Sparse Codes for Speech Predict Spectrotemporal Receptive Fields in the Inferior Colliculus

We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogram representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus and cortex, and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds.Comment: For Supporting Information, see PLoS website: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100259

Role of Inhibition in Binaural Processing

The medial and lateral superior olives (MSO, LSO) are the lowest order cell groups in the mammalian auditory circuit to receive massive binaural input. The MSO functions in part to encode interaural time differences (ITD), the predominant cue for localization of low frequency sounds. Binaural inputs to the MSO consist of excitatory projections from the cochlear nuclei (CN) and inhibitory projections from both the medial nucleus of the trapezoid body (MNTB) and lateral nucleus of the trapezoid body (LNTB). The interaction of excitatory and inhibitory currents within an MSO cell\u27s soma and dendrites over the backdrop of its intrinsic ionic conductances imbues ITD sensitivity to these neurons. Lloyd Jeffress proposed a coincidence detection circuit in which arrays of neurons receive sub-threshold excitatory inputs via delay lines that represent sound location as a place code of activity patterns within the cell group (Jeffress, 1948). The Jeffress place code model later found a neural instantiation in the MSO. Recent in vivo (McAlpine et al., 2001; Brand et al., 2002) studies have shown that peak discharge rates do not fall within the ecological range as the Jeffress model predicts but instead ITD is coded by changes in discharge rate. The timing of inhibition relative to excitation modulates the discharge rates of MSO cells (Brand et al., 2002; Chirila et al., 2007); however, the details of this circuit, such as the onset time of inhibition, are not well known. Although the MNTB and LNTB have been investigated in vivo and in vitro , they have not been well characterized with respect to their function in ITD processing in larger mammals. Additionally, inhibition is modulated by anesthesia and confounds in vivo experiments that examine the careful interplay of excitatory and inhibitory effects in the MSO. For this reason, these physiological experiments were performed on decerebrate unanaesthetized animals. Further investigation of the anatomical organization of inhibitory inputs was carried out as the basis for a comprehensive model of the MSO that incorporates the effects of binaural inhibiting projections to MSO neurons.;Unbiased stereological counts of the MNTB, MSO and subdivisions of the LNTB showed that the MSO and MNTB contain approximately the same number of cells. The main (m)LNTB, posteroventral (pv)LNTB and the hilus (h)LNTB are estimated to contain 3800, 1400, and 200 neurons respectively. Tonotopic organization of the MNTB and MSO show that in the low frequency area, MSO cells outnumber MNTB cells 2 to 1, suggesting a divergent innervation of the MSO from the MNTB. Injection of the retrograde tracer, biotinylated dextrane amine, in the MSO, labeled cells in the MNTB, pvLNTB and mLNTB and defines the important role that these sub-nuclei, and in particular the pvLNTB, have in ITD coding. Computational modeling of a single MSO cell suggests that when two sources of inhibition temporally frame excitation the coincidence detection window is refined and less sensitive to temporal fluctuations that otherwise might degrade ITD sensitivity. Finally, physiological properties of MNTB cells reveal a heterogeneous population of responses and less precise temporal coding than are found in their inputs, globular bushy cells

Inhibiting the inhibition

The precedence effect describes the phenomenon whereby echoes are spatially fused to the location of an initial sound by selectively suppressing the directional information of lagging sounds (echo suppression). Echo suppression is a prerequisite for faithful sound localization in natural environments but can break down depending on the behavioral context. To date, the neural mechanisms that suppress echo directional information without suppressing the perception of echoes themselves are not understood. We performed in vivo recordings in Mongolian gerbils of neurons of the dorsal nucleus of the lateral lemniscus (DNLL), a GABAergic brainstem nucleus that targets the auditory midbrain, and show that these DNLL neurons exhibit inhibition that persists tens of milliseconds beyond the stimulus offset, so-called persistent inhibition (PI). Using in vitro recordings, we demonstrate that PI stems from GABAergic projections from the opposite DNLL. Furthermore, these recordings show that PI is attributable to intrinsic features of this GABAergic innervation. Implementation of these physiological findings into a neuronal model of the auditory brainstem demonstrates that, on a circuit level, PI creates an enhancement of responsiveness to lagging sounds in auditory midbrain cells. Moreover, the model revealed that such response enhancement is a sufficient cue for an ideal observer to identify echoes and to exhibit echo suppression, which agrees closely with the percepts of human subjects

Particle Swarm Optimization Using Multiple Neighborhood Connectivity And Winner Take All Activation Applied To Biophysical Models Of Inferior Colliculus Neurons

Age-related hearing loss is a prevalent neurological disorder, affecting as many as 63% of adults over the age of 70. The inability to hear and understand speech is a cause of much distress in aged individuals and is becoming a major public health concern as age-related hearing loss has also been correlated with other neurological disorders such as Alzheimer\u27s dementia. The Inferior Colliculus (IC) is a major integrative auditory center, receiving excitatory and inhibitory inputs from several brainstem nuclei. This complex balance of excitation and inhibition gives rise to complex neural responses, which are measured in terms of firing rate as a given parameter is varied. A major obstacle in understanding the mechanisms involved in generating normal and aberrant auditory responses is estimating the strength and tuning of excitatory and inhibitory inputs that are integrated to form the output firing of IC neurons. To better understand IC response generation, biophysically accurate, conductance-based computational models were used to recreate IC frequency tuning responses. The problem of fitting response curves in vivo was approached using particle swarm optimization, an optimization paradigm which mimics social networks of flocking birds to solve problems. A new social network modeling winner-take-all activation found in visual neuron coding was developed in which agents are divided into social hierarchies and compete for leadership rights. This social network has shown good performance in benchmark optimization problems and is used to recreate IC frequency tuning responses which can be used to further understand pathological aging in the auditory system