Abstract
Accurate models of synaptic plasticity are essential to understand the adaptive properties of the nervous system and for realistic models of learning and memory. Experiments have shown that synaptic plasticity depends not only on pre- and post-synaptic activity patterns, but also on the strength of the connection itself. Namely, weaker synapses are more easily strengthened than already strong ones. This so called soft-bound plasticity automatically constrains the synaptic strengths. It is known that this has important consequences for the dynamics of plasticity and the synaptic weight distribution, but its impact on information storage is unknown. In this modeling study we introduce an information theoretic framework to analyse memory storage in an online learning setting. We show that soft-bound plasticity increases a variety of performance criteria by about 18% over hard-bound plasticity, and likely maximizes the storage capacity of synapses.
Highlights
Long term synaptic plasticity has been established as one of the most important components for learning and memory
We show that soft-bound plasticity leads to a 18% higher information capacity and find strong evidence that soft-bound plasticity optimizes storage capacity
We have studied plasticity rules that include the experimental observation that plasticity depends on the synaptic weight itself
Summary
Long term synaptic plasticity has been established as one of the most important components for learning and memory. Synaptic depression protocols lead to a percentage decrease in strength independent of strength itself [6] This phenomenon has been observed under both classical and spike timing dependent plasticity protocols [7], and is known as soft-bound or weight-dependent plasticity (see Discussion for possible biophysical correlates). Including weight dependence in plasticity rules is not just a minor fix noticeable only if synapses reach extreme values It has profound consequences for plasticity and its dynamics: First, it leads to unimodal synaptic weight distributions [13,14], consistent with distributions observed both in electro-physiological [15] and in spine size data [16]. Despite the experimental evidence for soft-bound plasticity rules, the effect of weight dependence on information storage is not well understood [22].
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