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

Abstract

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 interactionsonly 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 (ϳ10%) 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.

Category-selective phase coding in the superior temporal sulcus

“…Here we tested for phase coding in an object-selective region of the brain as a possible mechanism for rapid object categorization (14). We found rapid response latencies, with the majority of onset latencies <100 ms (median, ∼80 ms) and some as fast as 42 ms.…”

“…Here the <20-Hz activity was partially accounted for by phase alignment with respect to the evoked LFP response. Given the period of lower frequencies, this could translate to the spike placement in only one or two cycles, which nevertheless is at the level necessary for rapid categorization and shown to be sufficient in models using phase coding for object categorization (14).…”

“…Phase codes can be complementary to rate codes (9,10) and have the theoretical benefits of a greater potential information content, greater speed and efficiency of information transfer (e.g., communication through coherence) (11), and greater potential for plasticity through precise spike timing (11)(12)(13). Indeed, one model of object recognition explicitly uses phase-of-firing to accomplish rapid object processing (14). Nonetheless, direct empirical support for such a model is scarce.…”

STDP Pattern Onset Learning Depends on Background Activity

“…If presynaptic activity precedes postsynaptic activity, the conjoining synapse is strengthened-usually according to some STDP function-and if the reverse is observed, the synapse is depressed. Moreover, STDP can increase the mutual information between inputs and outputs of simple networks ( [14] used information theory to quantify learning performance), provides a function for Hebbian learning and development and captures the causality of determining the direction of synaptic change that is implied by Hebb's original postulate. STDP has accordingly been studied extensively and is commonly used as a substrate of forms of learning [9,10,20].…”

Adaptation-induced synchronization in laminar cortical circuits

“…Indeed, although gamma synchronization has been found to be involved in a variety of conditions (9-11, 14, 18-20), whether a fundamental feature of individual neurons, such as the capacity to exhibit adaptive changes or plasticity, is influenced by synchrony in the gamma frequency band remains unclear. Recently, several studies have addressed the relationship between neuronal synchronization and adaptationinduced cortical changes during learning and memory (33)(34)(35). However, these studies have focused on longer forms of plasticity while ignoring plastic changes occurring at more rapid time scales.…”