The explanation of higher neural processes requires an understanding of the dynamics of complex, spiking neural networks. So far, modeling studies have focused on networks with linear or sublinear dendritic input summation. However, recent single-neuron experiments have demonstrated strongly supralinear dendritic enhancement of synchronous inputs. What are the implications of this amplification for networks of neurons? Here, I show numerically and analytically that such networks can generate intermittent, strong increases of activity with high-frequency oscillations; the models developed predict the shape of these events and the oscillation frequency. As an example, for the hippocampal region CA1, events with 200-Hz oscillations are predicted. I argue that these dynamics provide a plausible explanation for experimentally observed sharp-wave/ripple events. High-frequency oscillations can involve the replay of spike patterns. The models suggest that these patterns may reflect underlying network structures.network dynamics | nonlinear dendrites | hippocampus | ripples D uring the last few years, experiments have shown that several inputs that arrive simultaneously (or with a temporal difference of at most few milliseconds) at a dendrite can cooperatively trigger a dendritic spike mediated by voltage-gated sodium channels (1-5). This spike generates a rapid depolarization in the soma, which has a rise time constant in the submillisecond range and typically is larger than the sum of the depolarizations the individual inputs would generate. If a somatic spike is generated by such a depolarization, this generation happens with high temporal precision; variations in the somatic spike response times are in the submillisecond range, as are the differences between response times of different neurons (1,3,5).Theoretical studies on active dendrites mainly considered single neurons. Simulations of neuron models incorporating details of channel spatial distribution and dendritic morphology showed dendritic spike generation in agreement with experiments (1, 2, 4, 6). For neurons with comparatively slow NMDA receptor-dependent dendritic spikes (7), which are largely insensitive to temporal coincidence of inputs and generate somatic depolarizations with rise times of tens of milliseconds, firing rate models have been developed (6). Based on these models, the computational abilities of simple circuits have been studied (7-9). In ref. 10, networks of bursting neurons were examined, where the bursts can be explained by slow dendritic spikes. Active dendrites generating fast dendritic sodium spikes were studied in a two-neuron circuit and in a simple feed-forward structure (11), and model neurons incorporating such dendritic spikes were used as an output layer in simulations of hippocampal network models (12).This article considers the implications of supralinear dendritic interactions as mediated by fast dendritic spikes in larger recurrent neural networks. How does a mechanism leading to strong enhancement of synchronous input and ...