Computational study of experience-dependent plasticity in adult rat cortical barrel-column

We model experience-dependent plasticity in the adult rat S1 cortical representation of the whiskers (the barrel cortex) which has been produced by trimmmg all whiskers on one side of the snout except two. This manipulation alters the pattern of afferent sensory activity while avoiding any direct nerve damage. Our simplified model circuitry represents multiple cortical layers and inhibitory neurons within each layer of a barrel-column. Utilizing a computational model we show that the evolution of the response bias in the barrel-column towards spared whiskers is consistent with synaptic modifications that follow the rules of the Bienenstock, Cooper and Munro (BCM) theory. The BCM theory postulates that a neuron possesses a dynamic synaptic modification threshold, θM, which dictates whether the neuron's activity at any given instant will lead to strengthening or weakening of the synapses impinging on it. However, the major prediction of our model is the explanation of the delay in response potentiation in the layer-IV neurons through a masking effect produced by the thresholded monotonically increasing inhibition expressed by either the logarithmic function, h(x) = μ log(1 + x), or by the power function, h(x) = μx0.8-0.9, where μ is a constant. Furthermore, simulated removal of the supragranular layers (layers II/III) reduces plasticity of neurons in the remaining layers (IV-VI) and points to the role of noise in synaptic plasticity.