Modeling coincidence detection in nucleus laminaris

The Journal of Neuroscience

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.

1991

A quantitative, neuronal model is proposed for the computation of interaural time difference (ITD) in the auditory system of the barn owl. The model uses a general, probabilistic approach, and is composed of two stages, the characteristics of which are based on anatomical and physiological evidence. Excitatory inputs from both ears, phase-locked to the waveform of tonal stimuli, together with phase-independent inhibitory inputs are summated linearly. The result is transformed into a probability of spike generation by a sigmoid nonlinearity, constituting a stochastic, 'soft' threshold with saturation. The model incorporates inhibition as a control parameter on the nonlinearity, and includes the usual crosscorrelation-type models as a special case. It has a minimum number of parameters, the values of which can be estimated from physiological data in a straightforward manner. This simple, general model accounts for the binaural response properties of physiologically recorded neurons. In particular, it explains the experimentally observed ITD-tuning and the increase of phase-locking from input to output neurons. The model predicts that a decrease in inhibition causes a non-monotonic change in sensitivity to ITD.

Journal of Neurophysiology, 2015

Axons from the nucleus magnocellularis form a presynaptic map of interaural time differences (ITDs) in the nucleus laminaris (NL). These inputs generate a field potential that varies systematically with recording position and can be used to measure the map of ITDs. In the barn owl, the representation of best ITD shifts with mediolateral position in NL, so as to form continuous, smoothly overlapping maps of ITD with iso-ITD contours that are not parallel to the NL border. Frontal space (0°) is, however, represented throughout and thus overrepresented with respect to the periphery. Measurements of presynaptic conduction delay, combined with a model of delay line conduction velocity, reveal that conduction delays can account for the mediolateral shifts in the map of ITD.

Neurocomputing, 1999

We have constructed a detailed biophysical model of coincidence detector neurons in the nucleus laminaris (auditory brainstem) which are purported to detect interaural time di!erences (ITDs). In the model, ITD coding is improved when the inputs from both ears are located on the bipolar dendrites and segregated, over having both inputs on the soma: the model behaves like the in vivo coincidence detectors. The model has enabled us to explore features of the coincidence detector neurons unexplained by a simpler biophysical model (Agmon-Snir et al., Nature 393 (1998) 262}272), including the e!ect of synapse location and multiple dendrites.

Journal of neurophysiology, 2014

Inputs from the two sides of the brain interact to create maps of interaural time difference (ITD) in the nucleus laminaris of birds. How inputs from each side are matched with high temporal precision in ITD-sensitive circuits is unknown, given the differences in input path lengths from each side. To understand this problem in birds, we modeled the geometry of the input axons and their corresponding conduction velocities and latencies. Consistent with existing physiological data, we assumed a common latency up to the border of nucleus laminaris. We analyzed two biological implementations of the model, the single ITD map in chickens and the multiple maps of ITD in barn owls. For binaural inputs, since ipsi- and contralateral initial common latencies were very similar, we could restrict adaptive regulation of conduction velocity to within the nucleus. Other model applications include the simultaneous derivation of multiple conduction velocities from one set of measurements and the dem...

Journal of Physiology-Paris, 2004

In birds and mammals, precisely timed spikes encode the timing of acoustic stimuli, and interaural acoustic disparities propagate to binaural processing centers. The Jeffress model proposes that these projections act as delay lines to innervate an array of coincidence detectors, every element of which has a different relative delay between its ipsilateral and contralateral excitatory inputs. Thus, interaural time difference (ITD) is encoded into the position of the coincidence detector whose delay lines best cancel out the acoustic ITD. Neurons of the avian nucleus laminaris and mammalian MSO phase-lock to both monaural and binaural stimuli but respond maximally when phase-locked spikes from each side arrive simultaneously, i.e. when the difference in the conduction delays compensates for the ITD. McAlpine et al. [Nat. Neurosci. 4 (2001) 396] identified an apparent difference between avian and mammalian ITD coding. In the barn owl, the maximum firing rate appears to encode ITD. This may not be the case for the guinea pig, where the steepest region of the function relating discharge rate to interaural time delay (ITD) is close to midline for all neurons, irrespective of best frequency (BF). These data suggest that low BF ITD sensitivity in the guinea pig is mediated by detection of a change in slope of the ITD function, and not by maximum rate. We review coding of low best frequency ITDs in barn owls and mammals and discuss whether there may be differences in the code used to signal ITD in mammals and birds.

Advances in experimental medicine and biology, 2016

Axons from the nucleus magnocellularis (NM) and their targets in nucleus laminaris (NL) form the circuit responsible for encoding interaural time difference (ITD). In barn owls, NL receives bilateral inputs from NM, such that axons from the ipsilateral NM enter NL dorsally, while contralateral axons enter from the ventral side. These afferents act as delay lines to create maps of ITD in NL. Since delay-line inputs are characterized by a precise latency to auditory stimulation, but the postsynaptic coincidence detectors respond to ongoing phase difference, we asked whether the latencies of a local group of axons were identical, or varied by multiples of the inverse of the frequency they respond to, i.e., to multiples of 2π phase. Intracellular recordings from NM axons were used to measure delay-line latencies in NL. Systematic shifts in conduction delay within NL accounted for the maps of ITD, but recorded latencies of individual inputs at nearby locations could vary by 2π or 4π. The...

Biological Cybernetics, 2008

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, below400 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.

Frontiers in Computational Neuroscience, 2013

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.

Frontiers in Computational Neuroscience, 2013

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).