Frontiers in Computational Neuroscience Computational Neuroscience
A biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and spike timing-dependent plasticity (STDP) suggests that STDP may be an important mechanism for creating a clustered plasticity engram, which shapes how different input streams are spatially represented in dendrite.
Abstract
weak or absent elsewhere. Whether such a functionally clustered spatial organization of synaptic efficacy patterning may emerge as a result of synaptic plasticity is a question that is still being actively pursued. Notably, why would clustering be a desirable emergent prop-erty? Firstly, previous studies have illustrated non-linear summa-tion between nearby synchronous (or near-synchronous) synaptic inputs (Koch et al., 1983; Tuckwell, 1986; Polsky et al., 2004), allowing for easier spike generation in regions with clustered inputs. Other studies have shown that altering the spatial configuration of inputs changes firing properties (Mel, 1993; Poirazi et al., 2003; Iannella et al., 2004), while correlated activity can alter the integra-tive properties of neurons (Destexhe and Paré, 1999; Rudolph and Destexhe, 2003). Such clusters may provide part of the scaffolding underlying the emergence of functional dendritic compartments, subregions where activity tends to be correlated and where local signal integration permits some state-dependent non-linear computation to take place, but simultaneously different to what is happening in other compartments (Polsky et al. Importantly, various studies have indicated that plasticity may lead to arrange afferent fiber contacts into spatial clusters. Three-eyed frog experiments have shown that synapses contributed by