The increased prevalence of post-traumatic stress disorder (PTSD) that is observed in women may involve sex differences in learned fear inhibition and medial prefrontal cortex (mPFC) function. PTSD is characterized by fear overgeneralization involving impaired fear regulation by safety signals. We recently found that males show fear discrimination and females show fear generalization involving reduced safety signalling after extended fear discrimination training. Here we determined if these sex differences involve altered mPFC function. Male and female rats underwent three days of auditory fear discrimination training, where one tone (CS+) was paired with footshock and another tone (CS−) was presented alone. Local field potentials were recorded from prelimbic (PL) and infralimbic (IL) mPFC during retrieval. We found that males discriminated and females generalized based on cue-induced freezing at retrieval. This was accompanied by sex differences in basal theta and gamma oscillations in PL and IL. Importantly, males also showed PL/IL theta activation during safety signalling by the CS− and IL gamma activation in response to the threat-related CS+, both of which were absent in females. These results add to growing evidence indicating that sex differences in learned fear inhibition are associated with altered mPFC function.

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Techniques for non-stationary signal analysis are important in understanding dynamical behaviour of complex systems. Time-frequency coherence is widely used to study timevarying properties of non-stationary signals. In this study, we present a wavelet-based method, using Airy wavelet, for coherence analysis. The approach incorporates a novel technique for removal of low frequency components due to envelope modulation in non-stationary signals. The technique is demonstrated on synthetic and real neurophysiological data. Results not only provide a clear description of desired features in non-stationary signals, but also suppress low frequency components due to envelope modulation. Our novel technique shows an effectiveness in extracting features hidden within the signals. It may lead to improved results in coherence analysis of medical, biological, physical and geophysical data containing low frequency envelope modulation besides non-stationarities.