The study of fearful emotions has important implications for animal emotional control and development. Current effects of fearful emotions on the behavior and brain activity of animals (especially birds) are mostly biased towards behavioral and physiological phenomena, and there is a lack of studies involving dynamic analysis of the patterns of neural electrical activity within specific relevant nuclei. In order to understand the rule of change of neural signals in pigeons under the fear emotion, taking pigeons as a model animal and its stratum griseum periventriculare (SGP) nuclei as the target brain area, adopting the experimental method of gradual approach of danger to study the pattern of change of neural activities under different fear proximity, the rhythmic differences of frequency domain, time-frequency energy, and functional connectivity based on the signal of Local field potential (LFP) were analyzed in-depth. The LFP signals of 2 pigeons in the resting state and the fear looming experiment were firstly collected and the four characteristic rhythmic components, Delta, Theta, Beta and Gamma, were extracted. The autoregressive modeling method was used to calculate the difference in the percentage of power spectral density between the quiet and fearful states at each rhythm. Next, the idiosyncratic change in time-frequency energy in the fear state with change in looming distance was analyzed. A coherence-based functional brain network was also constructed, and the local network connectivity characteristics of pigeons in both quiet and fearful states were statistically analyzed using a two-factor analysis of variance (ANOVA) method. Finally, a linear fitting analysis was performed to analyze the relationship between the network topological characteristics and the looming distance. The results show that the power spectral occupancy of the Theta band and the strength of brain functional network connections are significantly increased in the fear looming state of pigeons. With the shortening of the looming distance, the time-frequency energy variations within the Theta and Beta bands show a gradual upward trend, and there is a significant negative correlation between the strength of the local network connections and the looming distance. It suggests that the Theta frequency band may be related to the representation of fearful emotions, and that the difference in neuroelectric signal characteristics between the Theta and Beta frequency bands can characterize changes in fear looming distance. It can be seen that these results can provide valuable references for further exploring the study of the neural coding mechanism of fear emotion and its neural regulation in birds.