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Corrigendum for Bazhenov et al., J Neurophysiol 100 (3) 1562-1575.
J Neurophysiol 100: 3460, 2008; doi:10.1152/jn.z9k-9187-corr.2008
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CORRIGENDA

Corrigendum

Volume 100, September, 2008

Bazhenov M, Rulkov NF, Timofeev I. Effect of Synaptic Connectivity on Long-Range Synchronization of Fast Cortical Oscillations. J Neurophysiol 100: 1562–1575, 2008. First published July 16, 2008; doi:10.1152/jn.90613.2008; http://jn.physiology.org/cgi/content/full/100/3/1562.

During production, an older version of Fig. 7 was not replaced with a revised version. Figure 7 as it should appear is shown below.


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FIG. 7. Effect of network dimensionality on gamma range synchronization. A: oscillations in the 16 x 512 PYs (8 x 256 INs) network model. Snapshots of IN activity at 3 different times (left) and cross-correlation of field potentials along x axis (right). B: oscillations in the 8 x 512 PYs (4 x 256 INs) network model. C: normalized probability density distribution of time lags to the main peak of the cross-correlation function between local field potentials at different spatial locations as a function of the network size along the y dimension. Logarithmic scale. Results are averaged across 15 independent trials with randomly selected initial conditions. Note disappearance of the isolated peak for the network of size <1 footprint (8 PY neurons). D: spectrogram of the local field potential [averaged across all neurons within (150,350) x (1, N) area, where N is number of PY neurons along y axis] as a function of the network's size along the y-dimension. Logarithmic scale (dB). E, left: cross-correlation of field potentials along x axis in 2D model with radius of the synaptic footprint 4 for PY-PY and PY-IN synapses (total 47 and 48 neurons, respectively) and 2 for IN-PY synapses (total 13 neurons). Right: cross-correlation of field potentials along the chain of neurons in 1D model with radius of the synaptic footprint 24 for PY-PY and PY-IN synapses (total 47 and 48 neurons, respectively) and 6 for IN-PY synapses (total 13 neurons). Not only is delay to the peak of cross-correlation function larger in 1D model but also the amplitude of the correlation function is significantly reduced in 1D model.

 





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