Patterns of Synchrony in Neural Networks with Spike Adaptation
C. van Vreeswijk and D. Hansel
Neural Computation (in press).
We study the emergence of synchronized burst activity in networks of
neurons with spike adaptation. We show that networks of tonically firing adapting
excitatory neurons can evolve to a state where the neurons {\em burst} in a synchronized
manner. The mechanism leading to this burst activity is analyzed in a network of
integrate-and-fire neurons with spike adaptation. The dependence of this state on the
different network parameters is investigated, and it is shown that this mechanism is
robust against inhomogeneities, sparseness of the connectivity, and noise. In networks of
two populations, one excitatory and one inhibitory, we show that decreasing the inhibitory
feedback can cause the network to switch from a tonically active, asynchronous state to
the synchronized bursting state. Finally, we show that the same mechanism also causes
synchronized burst activity in networks of more realistic conductance based model neurons.
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