We propose a model for synaptic plasticity according to the Spike Timing Dependent Plasticity (STDP) theory using Linear Hybrid Automata (LHA). We first present a compositional LHA model in which each component corresponds to some process in STDP. We then abstract this model into a monolithic LHA model in order to enable formal analysis using hybrid model checking. We discuss how the availabili...

Rate based (Bienenstock-Cooper-Munroe, BCM) and spike timing dependent plasticity (STDP) are the two principal learning behaviors found at cortical synapses. Some BCM induction protocols have been shown to be compatible with STDP rules, thus combining both forms of plasticity. However, we demonstrate that the majority of actual experimental BCM protocols cannot be reproduced by STDP. This sensi...

Experimental evidence has shown that in some neuron types, such as hippocampal CA1 neurons, distally generated excitatory postsynaptic potentials (EPSPs) are scaled up in amplitude compared to more proximally generated EPSPs such that EPSP magnitudes at the soma are approximately equal regardless of the dendritic location of origin. Using an equivalent cable model neuron, we show that a particu...

Abstract Spike timing-dependent plasticity (STDP) is an attractive candidate to mediate the synaptic changes that support circuit plasticity in sensory cortices during development. STDP is prevalent at excitatory synapses, but it is not known whether the underlying mechanisms are universal, or whether distinct mechanisms underpin STDP at different synapses. Here, we set out to compare and contr...

The ability for cortical neurons to adapt their input/output characteristics and information processing capabilities ultimately relies on the interplay between synaptic plasticity, synapse location, and the nonlinear properties of the dendrite. Collectively, they shape both the strengths and spatial arrangements of convergent afferent inputs to neuronal dendrites. Recent experimental and theore...

Spike time dependent plasticity (STDP) has been observed in both developing and adult animals. Theoretical studies suggest that it implicitly leads to both competition and homeostasis in addition to correlation-based plasticity, making it a good candidate to explain developmental refinement and plasticity in a number of systems. However, it has only been observed to play a clear role in develop...

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repea...

A novel integrative learning architecture based on a reinforcement learning schemata model (RLSM) with a spike timing-dependent plasticity (STDP) network is described. This architecture models operant conditioning with discriminative stimuli in an autonomous agent engaged in multiple reinforcement learning tasks. The architecture consists of two constitutional learning architectures: RLSM and S...

Many cortical synapses exhibit spike timing-dependent plasticity (STDP) in which the precise timing of presynaptic and postsynaptic spikes induces synaptic strengthening [long-term potentiation (LTP)] or weakening [long-term depression (LTD)]. Standard models posit a single, postsynaptic, NMDA receptor-based coincidence detector for LTP and LTD components of STDP. We show instead that STDP at l...