Brain cognitive functions are due to interaction between huge numbers of neurons distributed in different regions of the brain. The study of neural communications and interactions between these regions is a challenging field in neuroscience. Many neuron ensembles are simultaneously active, and the synchronized oscillation between these ensembles cause an effective neural communication throughout the brain. Recent researches show that synchronized neural activities in different frequency bands such as ? and ? are related to cognitive functions. Perception, cognition, data analysis, and working memory are some examples of cognitive functions. Studies have shown that some mental disorders are resulted from abnormal neural activities. Discrimination of normal brain synchrony from abnormal brain synchrony can be used in diagnosis of mental diseases. Studies on the Parkinson treatment show that applying a controlled synchrony by electrodes to those parts of the brain without normal synchronization, may cure the disease. This research uses functional connectivity methods to study relationship between signals of different regions of the brain. For this purpose, these signals are analyzed in the time-frequency domain, and statistical measures are applied to examine synchrony between different signals of the brain regions. Gabor filters are applied to calculate the instantaneous phase of neural activities in different frequency bands. The computed phase is used in phase locking value (PLV) algorithm to estimate the level of synchronization. In addition to PLV, another algorithm is proposed to estimate the synchronization between two signals using the instantaneous phase computed by Gabor filters and the cross-correlation function. When the phase lag of two signals is calculated, the histogram of their phase lag is used to estimate the level of synchronization. Synthetic data is used for evaluation of the algorithms. The level of synchronization between synthetic signals is controlled by some parameters. The synthetic data is used to evaluate the proposed algorithm, PLV measure and Global Coherency. In this thesis besides the synthetic data, local field potential data (LFP) is also used to evaluate the synchrony between different regions of the brain. The real LFP data is recorded from the human brain in the rest state. Finally, the PLV method and proposed algorithm are used to estimate the synchronization level of the LFP signals Keywords: synchronization, functional connectivity, phase locking, PLV , Gabor filters, LFP