Multimodal Imaging Study On The Effect Of Sleep Deprivation And Dexmedetomidine On Brain Function

Sleep alternates with wakefulness,accompanied by a loss of consciousness,and are involved in higher-order cognitive processes such as learning,memory and synaptic plasticity.Therefore,it is of great significance to study the differences in brain function between different arousal level and different levels of consciousness in order to understand the neural mechanism of sleep.This study investigated the effect of sleep deprivation on brain based on the resting-state functional connectivity,task-state activation patterns and prediction of behavior via structural data,and explored the changes of functional connectivity in brainstem and thalamus during dexmedetomidine-induced unconsciousness.Further,this present study estimated the validation of sleep spindle detection based on non-experts.The main findings in present study are as follows: Firstly,this study used a masked independent component analysis to partition the hippocampus into ten small regions and investigated the changes in the functional connectivity with the whole brain after 24 hours of sleep deprivation in 40 normal young subjects.Increased functional connectivity was found between the right anterior hippocampus and left inferior frontal gyrus,bilateral postcentral gyrus(PoCG),bilateral precuneus and vision-related regions after sleep deprivation.Similar results were also identified between the left posterior hippocampus and the pars opercularis of left rolandic area,bilateral insula,left PoCG,left superior temporal gyrus,bilateral lingual gyrus and fusiform gyrus.These results reflect differential effects of sleep deprivation on the functional connectivity in specific hippocampal regions and provide new insights into the impact of sleep deprivation on the resting-state functional organization in the human brain.Secondly,this study used fMRI to examine the effects of 24 h of sleep deprivation on cerebral activation during a stop-signal task in 20 normal young subjects.Behaviorally,subjects showed significantly delayed stop-signal reaction time(SSRT)following sleep deprivation.In addition,reduced cerebral activation was found in the stopping network(including the inferior frontal gyrus [IFG],supplementary motor area,subthalamic nucleus [STN] and insula)and vision-related regions(occipital cortex,lingual gyrus and fusiform gyrus)after sleep deprivation.These findings support the hypothesis that task-related activation in prefrontal cortex is particularly vulnerable to sleep deprivation.Furthermore,we observed significant interaction effects of state(sleep deprivation or rested wakefulness)with activation in bilateral IFG,left STN and left lingual gyrus on SSRT.In conclusion,sleep deprivation is associated with the deficits in inhibition-related neural activation and the altered correlation between SSRT and cerebral activation,especially in the bilateral IFG,left STN and left lingual gyrus.Sleep deprivation for one night can impair the preformance of inhibition control.Poor response inhibition may profoundly interfere with the requirements of everyday life.Therefore,a decrease in response inhibition ability after sleep deprivation could have deleterious outcomes,and being able to predict the effect of sleep deprivation on inhibitory control could help avoid danger in the future.In this study,structural MRI data were used to predict the change in response inhibition performance(?SSRT)measured by a stop-signal task after 24 hours of sleep deprivation in 52 normal young subjects.For each subject,T1-weighted MRI data were acquired and the gray matter(GM)volumes were calculated using voxel-based morphometry analysis.First,the regions in which GM volumes correlated with ?SSRT were explored.Then,features were extracted from these regions and the prediction process was performed using a linear regression model with four-fold cross-validation.We found that the GM volumes of the left middle frontal gyrus,pars opercularis of right inferior frontal gyrus,pars triangularis of left inferior frontal gyrus,pars opercularis of right rolandic area,left supplementary motor area,left hippocampus,right lingual gyrus,right postcentral gyrus and left middle temporal gyrus could predict the ?SSRT with a low mean square error and a high Pearson's correlation coefficient between the predicted and actual values.In conclusion,our results demonstrated that a linear combination of structural MRI data could accurately predict the change in response inhibition performance after SD.Forthly,this study explored the effect of dexmedetomidine on the functional connectivity in brainstem and thalamus subregions based on the simultaneous EEG/fMRI data.All subjects underwent the simultaneous EEG/fMRI scaning and dexmedetomidine infusion.In order to evaluate the arousal level,the auditory stimuli consisted of the subject's name were presented every 1 min throughout the second visit and subjects were instructed to press the left button with their right index finger.Behaviorally,all subjects have response to the auditory stimuli during baseline.Significant individual difference of the unconscious latency have been observed.In addition,this study partitioned brainstem into nine small regions using mICA and compared the brainstem subregions-to-whole-brain functional connectivity between wakefulness and dexmedetomidine-induced unconsciousness states.One subregion of brainstem which included the major arousal centers: periaquaductal gray(PAG)and laterodorsal tegmental area(LDT)exhibited significantly reduced functional connectivity with default mode network,frontoparietal network,supplementary motor area,postcentral gyrus and temporal cortex during dexmedetomidine-induced unconsciousness state.The increased functional connectivity between the brainstem noradrenergic centers and default mode network,frontoparietal network,hippocampus,thalamus,temporal cortex and cerebellum during dexmedetomidine-induced unconsciousness state.Furthermore,similar analyses were performed on thalamus.The reduced functional connectivity between the right mediodorsal thalamic nucleus and motor network,between right medial pulvinar and visual related regions and between left medioventral nucleus and right calcarine sulcus and right lingual gyrus during unconsciousness state.One subregion of thalamus which included the left central median nucleus and left mediodorsal nucleus also exhibited reduced functional connectivity with left middle cingulate cortex and left supplementary motor area during unconsciousness state.The left pulvinar showed reduced functional connectivity with various brain regions.However,the increased functional connectivity was observed between the right lateral pulvinar and right precuneus during unconsciousness state.The above study investigated the changes of brain functional connectivity on fMRI data during dexmedetomidine-induced unconsciousness.For EEG,previous study have found that dexmedetomidine produces sleep spindles and sleep spindles were similar during dexmedetomidine sedation and normal sleep.Sleep spindles may be considered both as a physiological index of intellectual abilities and a marker of the capacity for learning.They may also have important supplementary diagnostic value.Therefore,it is imperative to accurately detect spindles.The present study described a method of using non-experts for manual detection of sleep spindles.We recruited five experts and 168 non-experts to manually identify spindles in N2 and N3 sleep data using a MATLAB interface.Scorers classified each spindle into definite and indefinite spindle(with weights of 1 and 0.5,respectively).First,a method of optimizing the thresholds of the expert/non-expert group consensus according to the results of experts and non-experts themselves is described.Using this method,we established expert and non-expert group standards from expert and non-expert scorers,respectively,and evaluated the performance of the non-expert group standards by compared with the expert group standard(termed EGS).The results indicated that the highest performance was the nonexpert group standard when definite spindles were only considered(termed nEGS-1).Second,four automatic spindle detection methods were compared with the EGS.We found that the performance of nEGS-1 versus EGS was higher than that of the four automated methods.Further,we found that six and nine non-experts were needed to manually identify spindles in stages N2 and N3,respectively,while maintaining acceptable performance of nEGS-1 versus EGS.In conclusion,this study establishes a detailed process for detection of sleep spindles by non-experts in a crowdsourcing scheme.In summary,the functional connectivity pattern have significant chagnes in different arousla levels and different conscious staes.Sleep deprivation altered the functional connectivity in hippocampal subreigons,and caused significant declines in inhibition control ability and deficits in inhibition-related neural activation.The gray matter volumes of stopping network,somatosensory cortex and hippcampus could accurately predict the change in response inhibition performance after sleep deprivation.During the other arousal level dexmedetomidine-induced unconsciousness,the functional connectivity in brainstem and thalamus subregions have significant changes.Finally,this study established a detailed process for detection of sleep spindles by non-experts in crowdsourcing scheme.