This study investigates the dynamic behavior of resting-state brain connectivity using time-frequency coherence analysis based on wavelet transforms. The research focuses on the posterior cingulate cortex (PCC), a key node of the default-mode network (DMN), and its relationship with the "anticorrelated" network, which is associated with task-positive or executive-control functions. The study reveals that coherence and phase between the PCC and the anticorrelated network vary over time and frequency, with significant scale-dependent temporal variability. A sliding-window correlation procedure identified other brain regions with variable connectivity to the PCC, including areas involved in attention and salience processing. Although the observed coherence and phase variability may be attributed to residual noise or cognitive state modulation, the results suggest that resting-state functional connectivity is not static. Therefore, measures of variability, in addition to average quantities, should be considered when characterizing resting-state networks. The study used wavelet transform coherence (WTC) to examine temporal variability in the relationship between nodes of the DMN and its anticorrelated network. WTC is well-suited for analyzing nonstationary changes in coupling between fMRI time series. The results show that the anticorrelated ROIs exhibit considerable modulation of coherence across the time-frequency plane, with significant coherence often focal in time. Positive correlations were more widespread across subjects, while negative correlations were weaker and less consistent. A statistical test based on Monte Carlo simulations revealed significant scale-dependent temporal variability in the wavelet transform coherence between the PCC and anticorrelated ROIs. The results also indicate that the anticorrelated ROIs have a predominantly unimodal distribution of coherence, peaking around a period of 32 seconds. The study also examined the effects of motion, scanner, and breath-holding on connectivity variability. No significant relationships were found between motion and connectivity variability, and the effects of scanner and breath-holding were not significant. The results suggest that the number of subjects in these between-group comparisons is small, and further study with larger subject groups would be necessary to attain the power required for a more conclusive inference concerning these effects. The study highlights the importance of considering temporal variability in resting-state functional connectivity and suggests that further dynamic analysis of the associated seed ROIs relative to the PCC is of interest. The findings indicate that resting-state BOLD connectivity has dynamic properties that may be overlooked by stationary analyses, complementing recent studies of dynamic spontaneous activity in animal models.This study investigates the dynamic behavior of resting-state brain connectivity using time-frequency coherence analysis based on wavelet transforms. The research focuses on the posterior cingulate cortex (PCC), a key node of the default-mode network (DMN), and its relationship with the "anticorrelated" network, which is associated with task-positive or executive-control functions. The study reveals that coherence and phase between the PCC and the anticorrelated network vary over time and frequency, with significant scale-dependent temporal variability. A sliding-window correlation procedure identified other brain regions with variable connectivity to the PCC, including areas involved in attention and salience processing. Although the observed coherence and phase variability may be attributed to residual noise or cognitive state modulation, the results suggest that resting-state functional connectivity is not static. Therefore, measures of variability, in addition to average quantities, should be considered when characterizing resting-state networks. The study used wavelet transform coherence (WTC) to examine temporal variability in the relationship between nodes of the DMN and its anticorrelated network. WTC is well-suited for analyzing nonstationary changes in coupling between fMRI time series. The results show that the anticorrelated ROIs exhibit considerable modulation of coherence across the time-frequency plane, with significant coherence often focal in time. Positive correlations were more widespread across subjects, while negative correlations were weaker and less consistent. A statistical test based on Monte Carlo simulations revealed significant scale-dependent temporal variability in the wavelet transform coherence between the PCC and anticorrelated ROIs. The results also indicate that the anticorrelated ROIs have a predominantly unimodal distribution of coherence, peaking around a period of 32 seconds. The study also examined the effects of motion, scanner, and breath-holding on connectivity variability. No significant relationships were found between motion and connectivity variability, and the effects of scanner and breath-holding were not significant. The results suggest that the number of subjects in these between-group comparisons is small, and further study with larger subject groups would be necessary to attain the power required for a more conclusive inference concerning these effects. The study highlights the importance of considering temporal variability in resting-state functional connectivity and suggests that further dynamic analysis of the associated seed ROIs relative to the PCC is of interest. The findings indicate that resting-state BOLD connectivity has dynamic properties that may be overlooked by stationary analyses, complementing recent studies of dynamic spontaneous activity in animal models.