In my master's thesis, I studied the possible unsupervised learning taking place in the early stages of insect olfactory system. To this extend, I applied a synaptic plasticity rule, namely inhibitory spike-timing dependent plasticity in a spiking neural network model based on honeybee antennal lobe. I investigated computationally if inhibitory STDP is an appropriate unsupervised learning mechanism to extract the correlation structure of input data to be reflected as lateral inhibition structure through which the neural representations of stimuli are processed in the insect antennal lobe.