Table 2.
Characterization of the wave front propagation traveling from the source to the sink.
| Cluster | t1 | t2 | t3 | t4 | t5 | |
|---|---|---|---|---|---|---|
| SA | Source | 2.6 ± 0.5 | 6.8 ± 0.8 | 10.0 ± 1.3 | 15.7 ± 2.7 | – |
| SA | Sink | – | 14.9 ± 3.4 | 9.6 ± 2.4 | 3.1 ± 0.7 | 2.2 ± 0.4 |
| SB | Source | 2.3 ± 0.5 | 6.6 ± 1.0 | 9.7 ± 1.1 | 14.4 ± 1.9 | – |
| SB | Sink | – | 13.9 ± 2.0 | 8.2 ± 0.9 | 3.9 ± 1.2 | 2.1 ± 0.4 |
The table shows the evolution of the mean radius of the IO wave fronts in two representative cases to illustrate the activity source-sink phenomena. In a simulation where a cluster of neurons has a higher rate of spiking activity than the average population (CA) and another cluster has only subthreshold oscillating neurons (CB), the evolution of the mean radius of the arcs with center in these clusters shows that the wave fronts generated in CA travel to CB. The table characterizes the wave front propagation corresponding to the two simulations (SA and SB) illustrated in Figure 10. The number of connections among the nearest neighbors is 12 with gc = 0.01 mS/cm2. Both clusters consist of 6 × 6 neighbor neurons. In the cluster with highly excitable neurons (source) Iinj = 0.5 μ A/cm2, while in the cluster with low excitable neurons (sink) σ = 2 and Iinj = 0 μ A/cm2. To calculate the mean radius, the interval from the wave front birth to the wave front death was divided in five subintervals (ti) with the same duration. Dashes indicate that no arcs were detected for that interval. Units are dimensionless as the radii were calculated in terms of the number of adjacent neurons covered by a spatio-temporal pattern from a given center detected with the wave front characterization algorithm described in section 2.5.