There have been numerous studies on the relationship between sleep and depression, as well as the relationship between sleep and depression, and heart rate variability (HRV), respectively. Even so, few studies have combined 24-h HRV analysis to study sleep quality and depressive symptoms. The purpose of this cross-sectional study was to investigate the relationship between depressed symptoms, sleep quality, and 24-h HRV in medical students. The particiants were all students at a medical university in Guangdong province, China. A total of 74 college students participated. They were asked to complete a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), the Beck Depression Inventory-II (BDI-II), the Positive and Negative Affect Scale (PANAS), and 24-h ECG monitoring. The results showed that 41.7% of the medical students had poor sleep quality, with higher levels of depressive symptoms and more negative emotions, and there was no difference in 24-h HRV indices between the low PSQI group and the high one. Correlation analysis showed that there was a significant relationship between sleep quality and depressive symptoms (r = 0.617), but the relationship between 24-h HRV indices and PSQI global scores, BDI scores were not significant. However, the correlation analysis of PSQI components and 24-h HRV showed that sleep disturbance was significantly negatively correlated with SDNN and LF in waking period (r = −0.285, −0.235), and with SDNN in sleeping period (r = −0.317). In general, the sleep disturbance in PSQI components can sensitively reflect the relationship between sleep quality and 24-h HRV of medical students. Individuals with higher sleep disturance may have lower SDNN during awake period and bedtime period, and lower LF in awake period. Twenty-four hour HRV has certain application value in clinical sleep quality monitoring, and its sensitivity and specificity in clinical application and daily life are still worth further investigation.

The brain areas that mediate the formation of auditory threat memory and perceptual decisions remain uncertain to date. Candidates include the primary (A1) and secondary (A2) auditory cortex, the medial division of the medial geniculate body (MGm), amygdala, and the temporal association cortex. We used chemogenetic and optogenetic manipulations with in vivo and in vitro patch-clamp recordings to assess the roles of these brain regions in threat memory learning in female mice. We found that conditioned sound (CS) frequency-dependent plasticity resulted in the formation of auditory threat memory in the temporal association cortex. This neural correlated auditory threat memory depended on CS frequency information from A1 glutamatergic subthreshold monosynaptic inputs, CS lateral inhibition from A2 glutamatergic disynaptic inputs, and nonfrequency-specific facilitation from MGm glutamatergic monosynaptic inputs. These results indicate that the A2 and MGm work together in an inhibitory-facilitative role.

Objectives Optogenetics is widely applied to study complex brain networks. However, recent studies have found that light alone can produce effects that are unrelated to optogenetics, and it is still unclear whether this can affect the results of optogenetic experiments. MethodsWe explored the characteristics of projection of interneurons to excitatory neurons in the auditory cortex with optogenetics, transgenic mice and patch-clamp recording. ResultsWe discovered that postsynaptic responses can be induced when we stimulated a blank area adjacent to the edge of brain slice. Similar results can be observed after blocking the polysynaptic responses by drugs. Together with the results of control experiments, we found that the false response is caused by activating the synaptic terminals beyond the range of the blue light (470 nm). Also, there was a linear relationship between the response and the stimulus distance for all data, which suggested that these false responses may be related to other factors, such as light scattering. ConclusionsThe LED-light-evoked response cannot reflect microcircuit of the recorded neuron and the activated neurons within the illumination range accurately. Together, these results confirm that light alone can affect neural activity, but this can be unrelated to the genuine 'optogenetic effect'.