Spike-Timing-Based Computation in Sound Localization (Goodman and Brette 2010)

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Accession:126465
" ... In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. ..."
Reference:
1 . Goodman DF, Brette R (2010) Spike-timing-based computation in sound localization. PLoS Comput Biol 6:e1000993 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Brian; Python;
Model Concept(s): Coincidence Detection; Synchronization;
Implementer(s): Goodman, Dan F. M. ;
from brian import *

def ircam_plot_count(hrtfset, count, index=None, showbest=True, absolute=False,
                     vmin=None, vmax=None, I=None, ms=20, mew=2, indexcol='k', bestcol='w'):
    count = array(count, dtype=float)
    num_indices = hrtfset.num_indices
    count = sum(count, axis=0)
    if I is None: I = arange(num_indices)
    img = zeros((10, 24))
    for i, c in enumerate(count):
        if i in I:
            elev = hrtfset.coordinates['elev'][i]
            azim = hrtfset.coordinates['azim'][i]
            if elev<60:
                w = 1
            elif elev==60:
                w = 2
            elif elev==75:
                w = 4
            elif elev==90:
                w = 24
                azim = -180
            if azim>=180: azim -= 360
            x = int((azim+180)/15)
            y = int((elev+45)/15)
            img[y, x:x+w] = c
    if absolute:
        imshow(img, origin='lower left', interpolation='nearest', extent=(-180-7.5, 180-7.5, -45-7.5, 90+7.5),
               vmin=vmin, vmax=vmax)
        axis('tight')
    else:
        imshow(img, origin='lower left', interpolation='nearest', extent=(-180-7.5, 180-7.5, -45-7.5, 90+7.5))
        axis('tight')
    if index is not None:
        azim = hrtfset.coordinates['azim'][index]
        elev = hrtfset.coordinates['elev'][index]
        if azim>=180: azim -= 360
        plot([azim], [elev], '+', ms=ms, mew=mew, color=indexcol)
    if showbest:
        i = argmax(count)
        azim = hrtfset.coordinates['azim'][i]
        elev = hrtfset.coordinates['elev'][i]
        if azim>=180: azim -= 360
        plot([azim], [elev], 'x', ms=ms, mew=mew, color=bestcol)
    return img