Table 3.
Network connectivity and excitabilitya
Spikes | Seizures | |
---|---|---|
Connectivity | ||
Uniform, 2σ2 = 10 | Yes | No |
Uniform, 2σ2 = 15 | Yes | No |
Uniform, 2σ2 = 20 | Yes | No |
Uniform, 2σ2 = 25 | Yes | No |
Uniform, 2σ2 = 30 | Yes | No |
Small-world, p = 10 | Yes | No |
Small-world, p = 20 | Yes | Yes |
Small-world, p = 30 | Yes | No |
Small-world, p = 40 | Yes | No |
Small-world, p = 50 | Yes | No |
Scale-free, λ = 2.0 | Yes | No |
Scale-free, λ = 2.5 | Yes | No |
Scale-free, λ = 3.0 | Yes | No |
Scale-free, λ = 3.5 | Yes | No |
Scale-free, λ = 4.0 | Yes | |
Spontaneous release probability | ||
1 × 10−5 | Yes | Yes |
5 × 10−5 | Yes | Yes |
1 × 10−4 | Yes | Yes |
5 × 10−4 | Yes | Yes |
1 × 10−3 | Yes | No |
aFor the connectivity table, spontaneous release probability per second = 0.05. For the spontaneous release probability table, connectivity = small-world, with 25% of connections long-distance. The term long-distance refers to connections to neurons that are >5 neurons away from the index neuron. Uniform connectivity, σ = SD of the Gaussian connectivity probability distribution, connectivity probability being the probability of connecting to a neuron at increasing distance from index neuron. Small-world connectivity, p = percentage of long-distance connections. Scale-free connectivity, λ = exponential in power law for scale-free networks. In scale-free networks, the probability P(k) that a node in the network has k connections to other nodes in the network follows a power law: P(k) ∼ k−λ. Five independent simulations were run for each of the listed configurations.