A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive bra...A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive brain-computer interface(BCI)applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles.In this study,a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal.The proposed decoder is constructed based on Gaussian Process model(GPM)which is a nonparametric Bayesian approach that has the advantages of being able to operate on small datasets and providing measurements of uncertainty on predictions.To evaluate the effectiveness of the proposed method,the GPM is compared against other competitive techniques which include k-Nearest Neighbors,linear discriminant analysis,support vector machine,ensemble learning and neural network.Results demonstrate that a significant improvement can be achieved via the GPM approach with average accuracy reaching over 96%and mean absolute error of no greater than 0.8 cm/s.In addition,the analysis reveals that while the performances of other existing methods deteriorate with a certain type of stimulus due to signal drifts resulting from the voluntary eyeblinks,the proposed GPM exhibits consistent performance across all stimuli considered,thereby manifesting its generalization capability and making it a more suitable option for dynamic commands with a single-channel EEG-controlled actuator.展开更多
While the hippocampus has been implicated in supporting the association among time-separated events,the underlying cellular mechanisms have not been fully clarified.Here,we combined in vivo multi-channel recording and...While the hippocampus has been implicated in supporting the association among time-separated events,the underlying cellular mechanisms have not been fully clarified.Here,we combined in vivo multi-channel recording and optogenetics to investigate the activity of hippocampal interneurons in freely-moving mice performing a trace eyeblink conditioning(tEBC)task.We found that the hippocampal interneurons exhibited conditioned stimulus(CS)-evoked sustained activity,which predicted the performance of conditioned eyeblink responses(CRs)in the early acquisition of the tEBC.Consistent with this,greater proportions of hippocampal pyramidal cells showed CS-evoked decreased activity in the early acquisition of the tEBC.Moreover,optogenetic suppression of the sustained activity in hippocampal interneurons severely impaired acquisition of the tEBC.In contrast,suppression of the sustained activity of hippocampal interneurons had no effect on the performance of well-learned CRs.Our findings highlight the role of hippocampal interneurons in the tEBC,and point to a potential cellular mechanism subserving associative learning.展开更多
目的研究消退过程中豚鼠眨眼条件反应特征参数的变化规律。方法 27只雄性12~16周龄豚鼠（体质量450~600 g）,按随机抽签法分为：1延迟性眨眼条件反射组（n=13）;2痕迹性眨眼条件反射组（n=14）。使用2 k Hz的正弦波纯音和医用氧气流分...目的研究消退过程中豚鼠眨眼条件反应特征参数的变化规律。方法 27只雄性12~16周龄豚鼠（体质量450~600 g）,按随机抽签法分为：1延迟性眨眼条件反射组（n=13）;2痕迹性眨眼条件反射组（n=14）。使用2 k Hz的正弦波纯音和医用氧气流分别作为条件刺激和非条件刺激,配对训练豚鼠建立延迟性和痕迹性眨眼条件反射。而后单独给予纯音条件刺激,使豚鼠已经建立的眨眼条件反射消退。高精度张力换能器记录豚鼠左侧的眼轮匝肌活动,Matlab程序分析眨眼运动行为数据。结果与痕迹组比较,延迟组动物条件眨眼反应习得率和条件眨眼反应峰幅度均显著增高（P〈0.05）,但两组条件眨眼反应的消退速率没有显著区别（P〉0.05）。此外,延迟组豚鼠反射消退较痕迹组自发恢复更明显（P〈0.05）。结论延迟性和痕迹性眨眼条件反应的消退具有不同的行为学特征。展开更多
基金This work was supported by the Ministry of Higher Education Malaysia for Fundamental Research Grant Scheme with Project Code:FRGS/1/2021/TK0/USM/02/18.
文摘A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive brain-computer interface(BCI)applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles.In this study,a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal.The proposed decoder is constructed based on Gaussian Process model(GPM)which is a nonparametric Bayesian approach that has the advantages of being able to operate on small datasets and providing measurements of uncertainty on predictions.To evaluate the effectiveness of the proposed method,the GPM is compared against other competitive techniques which include k-Nearest Neighbors,linear discriminant analysis,support vector machine,ensemble learning and neural network.Results demonstrate that a significant improvement can be achieved via the GPM approach with average accuracy reaching over 96%and mean absolute error of no greater than 0.8 cm/s.In addition,the analysis reveals that while the performances of other existing methods deteriorate with a certain type of stimulus due to signal drifts resulting from the voluntary eyeblinks,the proposed GPM exhibits consistent performance across all stimuli considered,thereby manifesting its generalization capability and making it a more suitable option for dynamic commands with a single-channel EEG-controlled actuator.
基金the National Natural Science Foundation of China(32071014)the Open Project Program of Brain and Intelligence Research Key Laboratory of Chongqing Education Commission(BIR2019001)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(31921003).
文摘While the hippocampus has been implicated in supporting the association among time-separated events,the underlying cellular mechanisms have not been fully clarified.Here,we combined in vivo multi-channel recording and optogenetics to investigate the activity of hippocampal interneurons in freely-moving mice performing a trace eyeblink conditioning(tEBC)task.We found that the hippocampal interneurons exhibited conditioned stimulus(CS)-evoked sustained activity,which predicted the performance of conditioned eyeblink responses(CRs)in the early acquisition of the tEBC.Consistent with this,greater proportions of hippocampal pyramidal cells showed CS-evoked decreased activity in the early acquisition of the tEBC.Moreover,optogenetic suppression of the sustained activity in hippocampal interneurons severely impaired acquisition of the tEBC.In contrast,suppression of the sustained activity of hippocampal interneurons had no effect on the performance of well-learned CRs.Our findings highlight the role of hippocampal interneurons in the tEBC,and point to a potential cellular mechanism subserving associative learning.
文摘目的研究消退过程中豚鼠眨眼条件反应特征参数的变化规律。方法 27只雄性12~16周龄豚鼠（体质量450~600 g）,按随机抽签法分为：1延迟性眨眼条件反射组（n=13）;2痕迹性眨眼条件反射组（n=14）。使用2 k Hz的正弦波纯音和医用氧气流分别作为条件刺激和非条件刺激,配对训练豚鼠建立延迟性和痕迹性眨眼条件反射。而后单独给予纯音条件刺激,使豚鼠已经建立的眨眼条件反射消退。高精度张力换能器记录豚鼠左侧的眼轮匝肌活动,Matlab程序分析眨眼运动行为数据。结果与痕迹组比较,延迟组动物条件眨眼反应习得率和条件眨眼反应峰幅度均显著增高（P〈0.05）,但两组条件眨眼反应的消退速率没有显著区别（P〉0.05）。此外,延迟组豚鼠反射消退较痕迹组自发恢复更明显（P〈0.05）。结论延迟性和痕迹性眨眼条件反应的消退具有不同的行为学特征。
