Temporal Map Formation in the Barn Owl’s Brain

Abstract

Barn owls provide an experimentally well-specified example of a temporal map, a neuronal representation of the outside world in the brain by means of time. Their laminar nucleus exhibits a place code of interaural time differences, a cue which is used to determine the azimuthal location of a sound stimulus, e.g., prey. We analyze a model of synaptic plasticity that explains the formation of such a representation in the young bird and show how in a large parameter regime a combination of local and nonlocal synaptic plasticity yields the temporal map as found experimentally. Our analysis includes the effect of nonlinearities as well as the influence of neuronal noise. DOI: 10.1103/PhysRevLett.87.248101 PACS numbers: 87.18. -h, 43.64. +r, 87.19.La Many animals have in their brain neuronal representations of the outside world, which we call maps. These representations are due to sensory organs. Vision, for instance, provides a direct map through the lens of the eye onto the retina and, accordingly, is dominantly spatial. Audition, on the other hand, has far fewer cues but time is one of them, a very important one. Here we face the question of how a temporal map can arise and provide an answer by considering a specific example, the barn owl's sound localization.Barn owls are nocturnal predators that are able to catch mice in complete darkness. In so doing they reach an amazing azimuthal resolution of 2 ± . Interaural (inter-ear) time differences have been shown [1] to be their only cue. The spatial resolution implies a temporal precision at least as good as 40 ms [2,3].We focus on the laminar nucleus as the first station in the brain receiving input from both ears. Interaural time differences (ITDs) are represented there by means of a place code. That is to say, the azimuthal position is mapped one-to-one onto corresponding neuronal sites in the laminar nucleus, each neuron signaling its preferred azimuthal location through a maximal firing rate. As the stimulus location is varied, so is the maximal ITD response in the laminar nucleus [2]; cf. Fig. 1. Henceforth the resulting map is a neuronal representation of azimuthal stimulus locations. We can now ask two questions. How does it function, in particular, why is the precision that good (40 ms), and how does it arise? As we will see, the answers to both questions are interrelated in that the map as it evolves leads to firing precision.Here we analyze how a novel mechanism of synaptic plasticity [5] gives rise to a temporal map. As was indicated by a numerical study [5], local so-called Hebbian learning depending on spike timing of the pre-and postsynaptic neuron [6,7], which precede and follow the synapse under consideration (hence Hebbian), and small, axonally propagated, synaptic modifications [8] together induce a temporal map. One may call the underlying mechanism "axon-mediated spike-based learning" (AMSL). We now present an analytic solution to the proposed synaptic dynamics and explain the model's performance in dependence upon the learning procedure, biol...

Effect of instantaneous frequency glides on interaural time difference processing by auditory coincidence detectors

“…Such an STDP mechanism has been demonstrated in many preparations (25,26), in particular in the auditory system (27). It has been shown that STDP can account for the development of ITD-sensitive neurons (28)(29)(30). However, these studies addressed only the learning of temporal delays.…”

Development of NMDA R1 expression in chicken auditory brainstem

“…Synaptophysin and syntaxin immunoreactivity also increase in NM and NL between E12 and E16 (Alladi et al., 2002). Modeling studies in the barn owl have proposed that formation of a computational map for interaural time differences in NL is mediated by the action of homosynaptic spike-based Hebbian learning Leibold et al, 2001). NR2A and NR2B subunits are of central importance in models of Hebbian learning and memory (Lisman et al, 2002;Liu et al, 2004;Massey et al, 2004), and we propose that early expression of NR2B contributes to synapse formation in the circuit for detection of interaural time differences.…”

Neural Development of Binaural Tuning through Hebbian Learning Predicts Frequency-Dependent Best Delays

“…Since this adaptation is frequency-specific, it must occur at an early stage in the auditory pathway: it has indeed been identified in the lateral shell and external nucleus of the inferior colliculus Knudsen, 1999, 2000). Previous modeling studies have also shown that STDP is a viable mechanism for the development of ITD selectivity (Gerstner et al, 1996;Kempter et al, 2001;Leibold et al, 2001;Leibold and van Hemmen, 2005). Thus, these two assumptions are plausible and are sufficient to account for the frequency dependence of BDs.…”

“…This mechanism has been demonstrated in vitro in many preparations (Markram et al, 1997;Poo, 1998, 2001;Caporale and Dan, 2008), in particular in the auditory system (Tzounopoulos et al, 2004), and has been the subject of many modeling studies (Kempter et al, 1999;Song et al, 2000;van Rossum et al, 2000), including in the context of ITD selectivity (Gerstner et al, 1996;Kempter et al, 2001;Leibold et al, 2001;Leibold and van Hemmen, 2005). Specifically, we consider a plasticity rule where synaptic modification is determined by the difference in timing of postsynaptic and presynaptic spikes, at each synapse (Fig.…”

“…Initially, the neuron receives synaptic inputs from monaural neurons on both sides, with monaural delays varying between 0 and 667 s [several times larger than the maximal ITD experienced by a barn owl (Moiseff, 1989); as in Gerstner et al, 1996;Kempter et al, 2001;Leibold et al, 2001;Leibold and van Hemmen, 2005; using a larger range (0 -1250 s) did not affect the results], and the synaptic weights evolve according to STDP. We first tested the development of ITD selectivity when the binaural neuron is stimulated by a binaurally delayed white noise, band-passed filtered around its CF (Fig.…”