Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation...Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy,and provide insightful biological implications.展开更多
Sleep deprivation causes disturbances of the neural activity, leading to the impairment of brain functions. However, the exact mechanism of sleep deprivation and how it affects the dynamics of brain activity during th...Sleep deprivation causes disturbances of the neural activity, leading to the impairment of brain functions. However, the exact mechanism of sleep deprivation and how it affects the dynamics of brain activity during the recovery sleep remains unclear. In the current study, we performed sleep deprivation experiments on ten adult rats, and recorded the local field potentials from default mode network(DMN) regions during sleep before and after sleep deprivation. The DMN dynamics was assessed with the configurations of coactive micropatterns(CAMPs) using our previously proposed CAMP method. Our analysis revealed that the effects of sleep deprivation on DMN dynamics in the slow-wave sleep(SWS) state and the rapid eye-movement sleep(REM)state were disparate. Dynamic configurations of DMN activity in the SWS state were significantly impaired after sleep deprivation, with increased occurrence of low-activity CAMP and reorganized transition structure across three CAMPs. Moreover,enhanced functional connectivity and improved efficiencies in all CAMP networks were observed during the SWS state in the recovery sleep. However, there were no significant alterations in either DMN dynamics or CAMP network structures in the REM sleep state after sleep deprivation. Our results described the alterations of DMN dynamics in different sleep states after sleep deprivation, and illustrated the differential effects of sleep deprivation on two sleep states. These findings demonstrated the underlying neural mechanisms of the effects of sleep deprivation on DMN activity during sleep and increased our understanding of the physiological roles of the DMN in maintain sleep homeostasis after sleep deprivation.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.81571770,61527815,81371636 and 81330032)
文摘Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy,and provide insightful biological implications.
基金supported by the MOST 2030 Brain Project (Grant No.2022ZD0208500)the National Natural Science Foundation of China(Grant Nos. 31771149, 81861128001, and 61933003)partly supported by the CAMS Innovation Fund for Medical Sciences (CIFMS)(Grant No.2019-I2M-5-039)。
文摘Sleep deprivation causes disturbances of the neural activity, leading to the impairment of brain functions. However, the exact mechanism of sleep deprivation and how it affects the dynamics of brain activity during the recovery sleep remains unclear. In the current study, we performed sleep deprivation experiments on ten adult rats, and recorded the local field potentials from default mode network(DMN) regions during sleep before and after sleep deprivation. The DMN dynamics was assessed with the configurations of coactive micropatterns(CAMPs) using our previously proposed CAMP method. Our analysis revealed that the effects of sleep deprivation on DMN dynamics in the slow-wave sleep(SWS) state and the rapid eye-movement sleep(REM)state were disparate. Dynamic configurations of DMN activity in the SWS state were significantly impaired after sleep deprivation, with increased occurrence of low-activity CAMP and reorganized transition structure across three CAMPs. Moreover,enhanced functional connectivity and improved efficiencies in all CAMP networks were observed during the SWS state in the recovery sleep. However, there were no significant alterations in either DMN dynamics or CAMP network structures in the REM sleep state after sleep deprivation. Our results described the alterations of DMN dynamics in different sleep states after sleep deprivation, and illustrated the differential effects of sleep deprivation on two sleep states. These findings demonstrated the underlying neural mechanisms of the effects of sleep deprivation on DMN activity during sleep and increased our understanding of the physiological roles of the DMN in maintain sleep homeostasis after sleep deprivation.
