The basal ganglia(BG) act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors. However,it is still not well understood how the BG maintains wakefulness and suppre...The basal ganglia(BG) act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors. However,it is still not well understood how the BG maintains wakefulness and suppresses sleep to achieve al these fundamental functions until genetical y engineered systems developed these years. Significant research efforts have recently been directed at developing genetic-molecular tools to achieve reversible and cell-type specific in vivo silencing or activation of neurons in behaving animals. Optogenetic tools can be used both to specifically activate or inhibit neurons of interest and identify functional synaptic connectivity between specific neuronal populations,both in vivo and in brain slices. Another recently developed system by Roth and colleagues permits the selective and ″remote″ manipulation(activation and silencing) of neuronal activity via all 3 major GPCR signaling pathways(G_i,G_s and G_q). These so-called ″ designer receptors exclusively activated by designer drugs″(DREADD) involve mutant GPCRs that do not respond to their endogenous ligands but are responsive to otherwise inert biological compounds. Recently,we demonstrated the essential roles and the neural pathways of the neurons expressing adenosine A_(2A) receptors or dopamine D_1 receptors in the BG for sleep-wake regulation using the genetically engineered systems including optogenetics and DREADD. We proposed a plausible model in which the caudate-putamen and the nucleus accumbens integrates behavioral processes with sleep/wakefulness through adenosine and dopamine receptors.展开更多
Sleep-wake rhythm disturbances,which are characterized by abnormal sleep timing or duration,are associated with cognitive dysfunction.Photoacoustic treatments including light and sound stimulation have been found to b...Sleep-wake rhythm disturbances,which are characterized by abnormal sleep timing or duration,are associated with cognitive dysfunction.Photoacoustic treatments including light and sound stimulation have been found to be effective in modulating sleep patterns and improving cognitive behavior in abnormal sleep-wake pattern experiments.In this study,we examined whether light and sound interventions could reduce sleep-wake pattern disturbances and memory deficits in a sleep rhythm disturbance model.We established a model of sleep rhythm disturbance in C57 BL/6 J mice via a sleep deprivation method involving manual cage tapping,cage jostling,and nest disturbance.We used a Mini Mitter radio transmitter device to monitor motor activity in the mice and fear conditioning tests to assess cognitive function.Our results indicated that an intervention in which the mice were exposed to blue light(40-Hz flickering frequency)for 1 hour during their subjective daytime significantly improved the 24-hour-acrophase shift and reduced the degree of memory deficit induced by sleep deprivation.However,interventions in which the mice were exposed to a 40-Hz blue light at offset time or subjective night time points,as well as 2 Hz-blue light at 3 intervention time points(subjective day time,subjective night time,and offset time points),had no positive effects on circadian rhythm shift or memory deficits.Additionally,a 2000-Hz sound intervention during subjective day time attenuated the24-hour-acrophase shift and memory decline,while 440-Hz and 4000-Hz sounds had no effect on circadian rhythms.Overall,these results demonstrate that photoacoustic treatment effectively corrected abnormal sleep-wake patterns and cognitive dysfunction associated with sleep-deprivation-induced disturbances in sleep-wake rhythm.All animal experiments were approved by the Experimental Animal Ethics Committee of Drum Tower Hospital Affiliated to the Medical College of Nanjing University,China(approval No.20171102)on November20,2017.展开更多
The basal ganglia(BG)act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors.However,it is still not well understood how the BG maintains wakefulness and suppress...The basal ganglia(BG)act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors.However,it is still not well understood how the BG maintains wakefulness and suppresses sleep to achieve all these fundamental functions until genetically engineered systems developed these years.We focused on the adenosine A2A and dopamine D1 Receptors(R)in the BG and obtained following 4 findings:①Nucleus accumbens(NAc)dopamine D1R-expressing neurons are essential in controlling wakefulness and are involved in physiological arousal via the lateral hypothalamus and midbrain circuits;②The rostromedial tegmental nucleus(RMTg),also called the GABAergic tail of the ventral tegmental area,projects to the midbrain dopaminergic system and other regions.Our findings reveal an essential role of the RMTg in the promotion of non-rapid eye movement(non-REM,NREM)sleep and homeostatic regulation;③Opposite to the D1R in the NAc,A2AR made a prominent contribution to sleep control associated with motivation.④Striatal adenosine A2AR neurons control active-period sleep via parvalbumin neurons in external globus pallidus.Taken together,we proposed a plausible model in which the caudate-putamen and NAc integrate behavioral processes with sleep/wakefulness through adenosine and dopamine receptors.The impacts of the BG in physiological sleep and insomnia will be discussed.展开更多
Objective: To observe the influence of heterogeneity on sleep-wake architecture in single-prolonged stress(SPS) animal model. Methods: SPS rats were subdivided into low responders(LR) and high responders(HR) based on ...Objective: To observe the influence of heterogeneity on sleep-wake architecture in single-prolonged stress(SPS) animal model. Methods: SPS rats were subdivided into low responders(LR) and high responders(HR) based on their freezing responses to a novel environment. Sleeping time(ST), awakening numbers(AN), brief awakening numbers(b AN) and frequency distribution of sleep bouts were used as observing indicators, single factor variance analysis combined with Dunnett t test were used to compare the differences between control, exposure, LR and HR groups. Results: We found sleeping time was increased only in HR group. Moreover, awakening numbers and brief awakening number increased in exposure group and HR group during the light phase, but not in LR group. The number of sleep bouts for the ranges of 40-80 s increased obviously in HR group, but not in exposure and LR group. In addition, there were significant correlation between sleep-related parameters and freezing in HR group, but not in LR group. Conclusion: Heterogeneity existed in SPS model in view of different sleep-wake architectures of SPS rats. Rats in HR group exactly mimicked the freezing response and sleep disorders of PTSD. So HR rats were more appropriate to be used as PTSD-like models, especially when studying sleep disorder in PTSD.展开更多
Background:To observe the development of neonatal sleep among healthy infants of different conceptional age(CA)by analyzing the amplitude-integrated electroencephalography(aEEG)of their sleep-wake cycles(SWC).Methods:...Background:To observe the development of neonatal sleep among healthy infants of different conceptional age(CA)by analyzing the amplitude-integrated electroencephalography(aEEG)of their sleep-wake cycles(SWC).Methods:Bedside aEEG monitoring was carried out for healthy newborns from 32 to 46 weeks CA between September 1,2011 and August 30,2012.For each aEEG tracing,mean duration of every complete SWC,number of SWC repetition within 12 hours,mean duration of each narrow and broadband of SWC,mean voltage of the upper edge and lower edge of SWC,mean bandwidth of SWC were counted and calculated.Analysis of the correlations between voltages or bandwidth of SWC and CA was performed to assess the developmental changes of central nervous system of newborns with different CA.Results:The SWC of different CA on aEEG showed clearly identifiable trend after 32 weeks of CA.The occurrence of SWC gradually increases from preterm to post-term infants;term infants had longer SWC duration.The voltage of upper edge of the broadband decreased at 39 weeks,while the lower edge voltage increases and the bandwidth of broadband declined along with the growing CA.The upper edge of the narrowband dropped while the lower edge rised gradually,especially in preterm stage.The width of the narrowband narrowed down while CA increased.Conclusions:The SWC on aEEG of 32-46 weeks infants showed a continuous,dynamic and developmental progress.The appearance of SWC and the narrowing bandwidth of narrowband is the main indicator to identify the CA-dependent SWC from the preterm to the late preterm period.The lower edge of the broadband identifi es the term to post-term period.展开更多
Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system.EEG based neonatal sleep staging provides valuable information about an infant’s growth and h...Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system.EEG based neonatal sleep staging provides valuable information about an infant’s growth and health,but is challenging due to the unique characteristics of EEG and lack of standardized protocols.This study aims to develop and compare 18 machine learning models using Automated Machine Learning(autoML)technique for accurate and reliable multi-channel EEG-based neonatal sleep-wake classification.The study investigates autoML feasibility without extensive manual selection of features or hyperparameter tuning.The data is obtained from neonates at post-menstrual age 37±05 weeks.352530-s EEG segments from 19 infants are used to train and test the proposed models.There are twelve time and frequency domain features extracted from each channel.Each model receives the common features of nine channels as an input vector of size 108.Each model’s performance was evaluated based on a variety of evaluation metrics.The maximum mean accuracy of 84.78%and kappa of 69.63%has been obtained by the AutoML-based Random Forest estimator.This is the highest accuracy for EEG-based sleep-wake classification,until now.While,for the AutoML-based Adaboost Random Forest model,accuracy and kappa were 84.59%and 69.24%,respectively.High performance achieved in the proposed autoML-based approach can facilitate early identification and treatment of sleep-related issues in neonates.展开更多
文摘The basal ganglia(BG) act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors. However,it is still not well understood how the BG maintains wakefulness and suppresses sleep to achieve al these fundamental functions until genetical y engineered systems developed these years. Significant research efforts have recently been directed at developing genetic-molecular tools to achieve reversible and cell-type specific in vivo silencing or activation of neurons in behaving animals. Optogenetic tools can be used both to specifically activate or inhibit neurons of interest and identify functional synaptic connectivity between specific neuronal populations,both in vivo and in brain slices. Another recently developed system by Roth and colleagues permits the selective and ″remote″ manipulation(activation and silencing) of neuronal activity via all 3 major GPCR signaling pathways(G_i,G_s and G_q). These so-called ″ designer receptors exclusively activated by designer drugs″(DREADD) involve mutant GPCRs that do not respond to their endogenous ligands but are responsive to otherwise inert biological compounds. Recently,we demonstrated the essential roles and the neural pathways of the neurons expressing adenosine A_(2A) receptors or dopamine D_1 receptors in the BG for sleep-wake regulation using the genetically engineered systems including optogenetics and DREADD. We proposed a plausible model in which the caudate-putamen and the nucleus accumbens integrates behavioral processes with sleep/wakefulness through adenosine and dopamine receptors.
基金supported by the National Natural Science Foundation of China,No.81730033(to XPG),No.81701371(to TJX),No.81801380(to XZ)the Natural Science Foundation of Jiangsu Province of China,No.BK20170654(to TJX),No.BK20170129(to XZ)the Key Talent’s 13th Five-Year Plan for Strengthening Health of Jiangsu Province of China,No.ZDRCA2016069(to XPG)
文摘Sleep-wake rhythm disturbances,which are characterized by abnormal sleep timing or duration,are associated with cognitive dysfunction.Photoacoustic treatments including light and sound stimulation have been found to be effective in modulating sleep patterns and improving cognitive behavior in abnormal sleep-wake pattern experiments.In this study,we examined whether light and sound interventions could reduce sleep-wake pattern disturbances and memory deficits in a sleep rhythm disturbance model.We established a model of sleep rhythm disturbance in C57 BL/6 J mice via a sleep deprivation method involving manual cage tapping,cage jostling,and nest disturbance.We used a Mini Mitter radio transmitter device to monitor motor activity in the mice and fear conditioning tests to assess cognitive function.Our results indicated that an intervention in which the mice were exposed to blue light(40-Hz flickering frequency)for 1 hour during their subjective daytime significantly improved the 24-hour-acrophase shift and reduced the degree of memory deficit induced by sleep deprivation.However,interventions in which the mice were exposed to a 40-Hz blue light at offset time or subjective night time points,as well as 2 Hz-blue light at 3 intervention time points(subjective day time,subjective night time,and offset time points),had no positive effects on circadian rhythm shift or memory deficits.Additionally,a 2000-Hz sound intervention during subjective day time attenuated the24-hour-acrophase shift and memory decline,while 440-Hz and 4000-Hz sounds had no effect on circadian rhythms.Overall,these results demonstrate that photoacoustic treatment effectively corrected abnormal sleep-wake patterns and cognitive dysfunction associated with sleep-deprivation-induced disturbances in sleep-wake rhythm.All animal experiments were approved by the Experimental Animal Ethics Committee of Drum Tower Hospital Affiliated to the Medical College of Nanjing University,China(approval No.20171102)on November20,2017.
文摘The basal ganglia(BG)act as a cohesive functional unit that regulates motor function,habit formation,and reward/addictive behaviors.However,it is still not well understood how the BG maintains wakefulness and suppresses sleep to achieve all these fundamental functions until genetically engineered systems developed these years.We focused on the adenosine A2A and dopamine D1 Receptors(R)in the BG and obtained following 4 findings:①Nucleus accumbens(NAc)dopamine D1R-expressing neurons are essential in controlling wakefulness and are involved in physiological arousal via the lateral hypothalamus and midbrain circuits;②The rostromedial tegmental nucleus(RMTg),also called the GABAergic tail of the ventral tegmental area,projects to the midbrain dopaminergic system and other regions.Our findings reveal an essential role of the RMTg in the promotion of non-rapid eye movement(non-REM,NREM)sleep and homeostatic regulation;③Opposite to the D1R in the NAc,A2AR made a prominent contribution to sleep control associated with motivation.④Striatal adenosine A2AR neurons control active-period sleep via parvalbumin neurons in external globus pallidus.Taken together,we proposed a plausible model in which the caudate-putamen and NAc integrate behavioral processes with sleep/wakefulness through adenosine and dopamine receptors.The impacts of the BG in physiological sleep and insomnia will be discussed.
基金supported by the Key Project of Science Research Foundation of Yunnan Provincial Department of Education (The study on the sleepimproving effect of Rhizoma,2015Z151)
文摘Objective: To observe the influence of heterogeneity on sleep-wake architecture in single-prolonged stress(SPS) animal model. Methods: SPS rats were subdivided into low responders(LR) and high responders(HR) based on their freezing responses to a novel environment. Sleeping time(ST), awakening numbers(AN), brief awakening numbers(b AN) and frequency distribution of sleep bouts were used as observing indicators, single factor variance analysis combined with Dunnett t test were used to compare the differences between control, exposure, LR and HR groups. Results: We found sleeping time was increased only in HR group. Moreover, awakening numbers and brief awakening number increased in exposure group and HR group during the light phase, but not in LR group. The number of sleep bouts for the ranges of 40-80 s increased obviously in HR group, but not in exposure and LR group. In addition, there were significant correlation between sleep-related parameters and freezing in HR group, but not in LR group. Conclusion: Heterogeneity existed in SPS model in view of different sleep-wake architectures of SPS rats. Rats in HR group exactly mimicked the freezing response and sleep disorders of PTSD. So HR rats were more appropriate to be used as PTSD-like models, especially when studying sleep disorder in PTSD.
基金This work was supported by the Guangzhou Science Technology and Innovation Commission 1563000668(Lian Zhang).
文摘Background:To observe the development of neonatal sleep among healthy infants of different conceptional age(CA)by analyzing the amplitude-integrated electroencephalography(aEEG)of their sleep-wake cycles(SWC).Methods:Bedside aEEG monitoring was carried out for healthy newborns from 32 to 46 weeks CA between September 1,2011 and August 30,2012.For each aEEG tracing,mean duration of every complete SWC,number of SWC repetition within 12 hours,mean duration of each narrow and broadband of SWC,mean voltage of the upper edge and lower edge of SWC,mean bandwidth of SWC were counted and calculated.Analysis of the correlations between voltages or bandwidth of SWC and CA was performed to assess the developmental changes of central nervous system of newborns with different CA.Results:The SWC of different CA on aEEG showed clearly identifiable trend after 32 weeks of CA.The occurrence of SWC gradually increases from preterm to post-term infants;term infants had longer SWC duration.The voltage of upper edge of the broadband decreased at 39 weeks,while the lower edge voltage increases and the bandwidth of broadband declined along with the growing CA.The upper edge of the narrowband dropped while the lower edge rised gradually,especially in preterm stage.The width of the narrowband narrowed down while CA increased.Conclusions:The SWC on aEEG of 32-46 weeks infants showed a continuous,dynamic and developmental progress.The appearance of SWC and the narrowing bandwidth of narrowband is the main indicator to identify the CA-dependent SWC from the preterm to the late preterm period.The lower edge of the broadband identifi es the term to post-term period.
文摘Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system.EEG based neonatal sleep staging provides valuable information about an infant’s growth and health,but is challenging due to the unique characteristics of EEG and lack of standardized protocols.This study aims to develop and compare 18 machine learning models using Automated Machine Learning(autoML)technique for accurate and reliable multi-channel EEG-based neonatal sleep-wake classification.The study investigates autoML feasibility without extensive manual selection of features or hyperparameter tuning.The data is obtained from neonates at post-menstrual age 37±05 weeks.352530-s EEG segments from 19 infants are used to train and test the proposed models.There are twelve time and frequency domain features extracted from each channel.Each model receives the common features of nine channels as an input vector of size 108.Each model’s performance was evaluated based on a variety of evaluation metrics.The maximum mean accuracy of 84.78%and kappa of 69.63%has been obtained by the AutoML-based Random Forest estimator.This is the highest accuracy for EEG-based sleep-wake classification,until now.While,for the AutoML-based Adaboost Random Forest model,accuracy and kappa were 84.59%and 69.24%,respectively.High performance achieved in the proposed autoML-based approach can facilitate early identification and treatment of sleep-related issues in neonates.
