This study investigates the neural mechanism underlying theta phase precession and procession in hippocampal place cells, showing that firing rate adaptation in a continuous attractor neural network (CANN) enables oscillatory tracking of the external input, which naturally accounts for theta sweeps. The model demonstrates that forward and backward sweeps of the neural activity bump correspond to phase precession and procession, respectively. By tuning adaptation strength, the model explains the difference between bimodal cells (showing interleaved phase precession and procession) and unimodal cells (predominantly phase precession). The model also explains the constant cycling of theta sweeps in a T-maze environment, speed modulation of place cell firing, and continued phase shift after transient hippocampal silencing. The study highlights the role of firing rate adaptation in generating the rich dynamics of hippocampal neurons and supports the idea that theta phase coding is robust to perturbations. The model provides a framework for understanding how hippocampal place cells encode spatial information through oscillatory tracking, with implications for spatial navigation and episodic memory.This study investigates the neural mechanism underlying theta phase precession and procession in hippocampal place cells, showing that firing rate adaptation in a continuous attractor neural network (CANN) enables oscillatory tracking of the external input, which naturally accounts for theta sweeps. The model demonstrates that forward and backward sweeps of the neural activity bump correspond to phase precession and procession, respectively. By tuning adaptation strength, the model explains the difference between bimodal cells (showing interleaved phase precession and procession) and unimodal cells (predominantly phase precession). The model also explains the constant cycling of theta sweeps in a T-maze environment, speed modulation of place cell firing, and continued phase shift after transient hippocampal silencing. The study highlights the role of firing rate adaptation in generating the rich dynamics of hippocampal neurons and supports the idea that theta phase coding is robust to perturbations. The model provides a framework for understanding how hippocampal place cells encode spatial information through oscillatory tracking, with implications for spatial navigation and episodic memory.