I have made a number of small corrections to the article. I like it; it is short and to the point.
You can see my corrections just by clicking 'article', then 'revisions', then 'compare selected versions'.
I put some explanation on what polychrony is. Also, I included the following paragraph:
Luczak et al. (2007) showed that reproducible precise firing patterns can appear at the beginning of transitions from down- to up-states in vivo in anesthetized and awake rats (see UP and DOWN States). The exact mechanism of generation of such patterns is not known, but it most probably relies on the fact that pyramidal neurons exhibit reproducible latencies (delays up to 500 ms) to the first spike when stimulated with an injected step of dc-current or injected conductance (via dynamic clamp). Different neurons have different latencies resulting in stereotypical patterns of transition from down- to up-states.
this is a nicely written article which provides a broad overview of the topic in a clear and compact manner.
I have only a few minor remarks and suggestions:
Sec.1, 1st par.:
The notion "stable mode of transmission" is maybe unclear at this point. I would rather say something like "the only firing mode that allows a (stable) transmission of information". Asynchronous activity --the ground state-- can be stable, too (Tetzlaff et al., 2002), but it can hardly serve as a signal carrier.
Sec.1, 1st par.:
"This was shown ... in the slice."
"Slice" of what? Rather say "in-vitro in cortical slices."
Sec.3, 2nd par.:
"With the synfire memory capacity described below (Sec.4)"
Sec.4, 2nd par.:
"As pointed out by Maass,..."
Can you provide the full reference?
Sec.4, 4th par.:
The reference (Tetzlaff et al., 2002) is not correct. We discussed the embedding of synfire chains in
Tetzlaff, T. and Morrison, A. and Geisel, T. and Diesmann, M. (2004), Consequences of realistic network size on the stability of embedded synfire chains, Neurocomputing 58-60:117--121 .
Sec.4, 4th par.:
Heterogeneity in synaptic potential sizes is not the optimal solution for this problem, because due to the large number of synapses a plausible variability in synaptic weights would largely average out (in contrast to a heteorgeneity in membrane time constants or thresholds).
Fast oscillatory modes can be dampened by distributions of delays not only for inhibitory but also excitatory connections. Of course, the delays of the connections between two consecutive synfire layers must be approximately identical (this may be justified by some learning rule based on spike timing). Connections between different pairs of layers can, however, have different delays.
Sec.5, 3rd par.:
"Such learning rules ... are dubbed STDP."
"...are dubbed spike-timing dependent plasticity (STDP)."
Figure 2, left:
What exactly is meant by "A statistic based on the most prominent peaks in cross-correlations"? Could you add a label to the x-axis here?
The article is highly readable and balanced. My comments below are only concerned with technical details of the dynamics.
In "Activity in synfire chains"
"It has been argued that the only stable mode of transmission is the synchronous mode (Abeles 1982, 1991). This was shown to be true theoretically (Hertz 1997), through numerical calculations (Diesmann et al. 1999), simulations (Abeles et al. 1993, Gewaltig et al. 2001, Hayon et al. 2004), and in the slice (Reyes 2003)."
I suggest to add sentences like the following here: "A minimal number of neurons in each pool is required for stable propagation of synchronous spiking. Tetzlaff et al. (2002) showed that above a maximal number of neurons the ground state of asynchronous activity becomes unstable and synchronous activity emerges spontaneously."
In "Memory capacity for synfire chains"
"Even when only one synfire chain was embedded in such a balanced network, the network went into a mode of synchronous oscillations (Tetzlaff et al. 2002, Aviel et al. 2002)."
The Tetzlaff 2002 reference is not accurate here. Replace by "Even when only one synfire chain was embedded in such a balanced network stable propagation is challenged by modes of synchronous oscillations (Aviel et al. 2002, Mehring et al. 2003)."
Mehring, C., Hehl, U., Kubo, M., Diesmann, M., & Aertsen, A. (2003). Activity dynamics and propagation of synchronous spiking in locally connected random networks. Biol. Cybern., 88(5), 395�$-1òó408.
"In particular, using dispersed thresholds, synaptic potential sizes, and delays for the inhibitory neurons was very useful for avoiding global synchronization."
it is more accurate to say
"In particular, using a biologically plausible heterogeneity in the number of incoming synapses was found to be more effective than dispersing any other parameter."