Original Article

Journal of Computational Neuroscience

, Volume 34, Issue 2, pp 319-336

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks

  • Silvia ScarpettaAffiliated withDepartment of Physics ‘E. R. Caianiello’, University of SalernoINFN Unita’ di Napoli Gruppo coll. di Salerno Email author 
  • , Ferdinando GiaccoAffiliated withDepartment of Environmental Sciences, Second University of Naples


We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stable precise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units.


Learning and memory Phase-of-spikes coding Storage capacity Replay Associative memory Noise robustness STDP