| | Models | Description |
| 1. |
A two networks model of connectivity-dependent oscillatory activity (Avella OJ et al. 2014)
|
|
|
Activity in a cortical network may express a single oscillation frequency, alternate between two or more distinct frequencies, or continually express multiple frequencies. In addition, oscillation amplitude may fluctuate over time. Interactions between oscillatory networks may contribute, but their effects are poorly known. Here, we created a two model networks, one generating on its own a relatively slow frequency (slow network) and one generating a fast frequency (fast network). We chose the slow or the fast network as source network projecting feed-forward connections to the other, or target network, and systematically investigated how type and strength of inter-network connections affected target network activity. Our results strongly depended on three factors: the type of the relevant (main) connection, its strength and the amount of source synapses. For high inter-network connection strengths, we found that the source network could completely impose its rhythm on the target network. Interestingly, the slow network was more effective at imposing its rhythm on the fast network than the other way around. The strongest entrainment occurred when excitatory cells of the slow network projected to excitatory or inhibitory cells of the fast network. Just as observed in rat activity at the prefrontal cortex satisfies the behavior described above, such that together, our results suggest that input from other oscillating networks may markedly alter a network’s frequency spectrum and may partly be responsible for the rich repertoire of temporal oscillation patterns observed in the brain. |
| 2. |
H-currents effect on the fluctuation of gamma/beta oscillations (Avella-Gonzalez et al., 2015)
|
|
|
This model was designed to study the impact of H-currents on
the dynamics of cortical oscillations, and in paticular on
the occurrence of high and low amplitude episodes (HAE, LAE) in network oscillations.
The H-current is a slow, hyperpolarization-activated, depolarizing current
that contributes to neuronal resonance and membrane potential.
We characterized amplitude fluctuations in network oscillations by measuring
the average durations of HAEs and LAEs, and explored
how these were modulated by trains of external spikes, both in
the presence and absence of H-channels.
We looked at HAE duration, the frequency
and power of network oscillations, and the effect
of H-channels on the temporal voltage profile in single cells.
We found that H-currents increased the oscillation frequency and, in combination with external spikes, representing input from areas outside the network, strongly decreased the synchrony of firing. As a consequence, the oscillation power and the duration of episodes during which the network exhibited high-amplitude oscillations were greatly reduced in the presence of H-channels. |
| 3. |
Single E-I oscillating network with amplitude modulation (Avella Gonzalez et al. 2012)
|
|
|
"... Intriguingly, the amplitude of ongoing oscillations, such as measured in EEG recordings, fluctuates irregularly, with episodes of high amplitude (HAE) alternating with episodes of low amplitude (LAE).
...
Here, we show that transitions between HAE and LAE in the alpha/beta frequency band occur in a generic neuronal network model consisting of interconnected inhibitory (I) and excitatory (E) cells that are externally driven by sustained depolarizing currents(cholinergic input) and trains of action potentials that activate excitatory synapses.
In the model, action potentials onto inhibitory cells represent input from other brain areas and desynchronize network activity, being crucial for the emergence of amplitude fluctuations.
..."
|
