Title: Critical neural networks with short and long term plasticity,
Abstract: In recent years self organised critical neuronal models have provided
insights regarding the origin of the experimentally observed avalanching
behaviour of neuronal systems. It has been shown that dynamical synapses, as a
form of short-term plasticity, can cause critical neuronal dynamics. Whereas
long-term plasticity, such as hebbian or activity dependent plasticity, have a
crucial role in shaping the network structure and endowing neural systems with
learning abilities. In this work we provide a model which combines both
plasticity mechanisms, acting on two different time-scales. The measured
avalanche statistics are compatible with experimental results for both the
avalanche size and duration distribution with biologically observed percentages
of inhibitory neurons. The time-series of neuronal activity exhibits temporal
bursts leading to 1/f decay in the power spectrum. The presence of long-term
plasticity gives the system the ability to learn binary rules such as XOR,
providing the foundation of future research on more complicated tasks such as
pattern recognition.