Abstract
AbstractElectrophysiological connectivity patterns in cortex often show a few strong connections in a sea of weak connections. In some brain areas a large fraction of strong connections are bidirectional, in others they are mainly unidirectional. In order to explain these connectivity patterns, we use a model of Spike-Timing-Dependent Plasticity where synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential. The model describes several nonlinear effects in STDP experiments, as well as the voltage dependence of plasticity under voltage clamp and classical paradigms of LTP/LTD induction. We show that in a simulated recurrent network of spiking neurons our plasticity rule leads not only to receptive field development, but also to connectivity patterns that reflect the neural code: for temporal coding paradigms strong connections are predominantly unidirectional, whereas they are bidirectional under rate coding. Thus variable connectivity patterns in the brain could reflect different coding principles across brain areas.
Highlights
Experience-dependent changes in receptive fields [1, 2, 3] or in learned behavior [4] may occur through changes in synaptic strength
Spike-Timing-Dependent Plasticity (STDP) has attracted particular interest in recent years, since temporal coding schemes where information is contained in the exact timing of spikes rather than mean frequency could be learned by a neural system using STDP [17, 18, 19, 20, 21]
In order to study how connectivity patterns in cortex can emerge from an interplay of plasticity rules and coding, we need a plasticity rule that is consistent with a large body of experiments, not just a single paradigm such as STDP
Summary
Experience-dependent changes in receptive fields [1, 2, 3] or in learned behavior [4] may occur through changes in synaptic strength. The question, whether STDP is more fundamental than frequency dependent plasticity or voltage dependent plasticity rules has not been resolved, despite an intense debate [22] It is unclear how the interplay of coding and plasticity yield the functional connectivity patterns seen in experiments. In contrast of earlier attempts towards a unified description of synaptic plasticity rule that focused on detailed biophysical descriptions [24, 25], our model is a mechanistic one (phenomenological model) It does not give an explicit interpretation in terms of biophysical quantities such a Calcium concentration [24], CaMKII [25], glutamate binding, NMDA receptors etc. The mathematical simplicity of the model enables us to identify conditions under which it becomes equivalent to the well-known Bienenstock-Cooper-Munro model [30] used in classical rate-based descriptions of developmental learning; and equivalent to some earlier models of STDP [32] — and why our model is fundamentally different from classical STDP models [17, 26, 21], widely used for temporal coding
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
