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The Journal of Neuroscience, October 28, 2009, 29(43):13484-13493; doi:10.1523/JNEUROSCI.2207-09.2009

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Behavioral/Systems/Cognitive
Oscillations, Phase-of-Firing Coding, and Spike Timing-Dependent Plasticity: An Efficient Learning Scheme

Timothée Masquelier,¹ Etienne Hugues,¹ Gustavo Deco,¹ and Simon J. Thorpe²

¹Theoretical and Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona 08018, Spain, ²Centre de Recherche Cerveau et Cognition, Université Toulouse 3, Centre National de la Recherche Scientifique, Faculté de Médecine de Rangueil, Toulouse 31062, France

Correspondence should be addressed to Timothée Masquelier, Theoretical and Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, C/Roc Boronat, 138, 08018 Barcelona, Spain. Email: timothee.masquelier{at}alum.mit.edu

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as "phase-of-firing coding" (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

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Received May 11, 2009; revised Aug. 19, 2009; accepted Sept. 3, 2009.

Correspondence should be addressed to Timothée Masquelier, Theoretical and Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, C/Roc Boronat, 138, 08018 Barcelona, Spain. Email: timothee.masquelier{at}alum.mit.edu

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