BACKGROUND The neural mechanisms underlying aggressive behavior in schizophrenia(SCZ)remain poorly understood.To date,no studies have reported on the event-related potential(ERP)characteristics of aggression in SCZ us...BACKGROUND The neural mechanisms underlying aggressive behavior in schizophrenia(SCZ)remain poorly understood.To date,no studies have reported on the event-related potential(ERP)characteristics of aggression in SCZ using the competitive reaction time task(CRTT).Further investigation into the ERP correlates of aggression in SCZ would provide valuable insights into the neural processes involved.AIM To explore the neural mechanism of aggressive behavior in SCZ.METHODS Participants of this study included 40 SCZ patients and 42 healthy controls(HCs).The Reactive Proactive Aggression Questionnaire was used to assess trait of aggression.The Barratt Impulsiveness Scale 11 was used to measure impulsiveness.The Positive and Negative Symptom Scale(PANSS)was used to evaluate psychopathological features and disease severity.All participants were measured with ERP while performing the CRTT.Data of behavior,ERP components(P2,N2,and P3),and feedback-related negativity(FRN)were analyzed.RESULTS Analysis of the behavioral data revealed that compared with HCs,SCZ patients exhibited higher punishment choices.Analysis of ERP components showed that compared with HCs,SCZ patients exhibited higher N2 amplitudes and P2 amplitudes during the decision phase of the CRTT;however,SCZ patients exhibited lower FRN amplitudes and lower P3 amplitudes during the outcome phase of the CRTT.The N2 amplitudes evoked by highintensity provocation were positively related to PANSS-P scores.And the P3 amplitudes evoked in the winning trials were negatively correlated with the PANSS-G scores.CONCLUSION SCZ patients exhibit abnormal ERP characteristics evoked by the CRTT,which suggests the neural correlates of aggressive behavior in SCZ.展开更多
In this paper, competitive neural networks with time-varying and distributed delays are investigated. By utilizing Lyapunov functional methods, the global exponential stability of periodic solutions of the neural netw...In this paper, competitive neural networks with time-varying and distributed delays are investigated. By utilizing Lyapunov functional methods, the global exponential stability of periodic solutions of the neural networks is discussed on time scales. In addition, an example is given to illustrate the effectiveness of the theoretical results.展开更多
To improve the efficiency and stability of data transmission in the long-range(LoRa) Internet of things(IoT),a hybrid time slot allocation algorithm is proposed, which implements a priority mechanism with high-priorit...To improve the efficiency and stability of data transmission in the long-range(LoRa) Internet of things(IoT),a hybrid time slot allocation algorithm is proposed, which implements a priority mechanism with high-priority nodes sending data in fixed time slots and low-priority nodes using the carrier sense multiple access(CSMA) algorithm to compete for shared time slots to transmit data. To improve network efficiency, a gateway is used to adjust the time slot allocation policy according to network status and balance the number of fixed and shared time slots. And more, a retransmission time slot is added to the time slot allocation algorithm, which redesigns the time frame structure, and adopts a retransmission mechanism to improve communication reliability. Simulation and measurement results show that the packet loss rate and transmission delay of the proposed hybrid algorithm are smaller than those of the fixed slot allocation algorithm, making the proposed algorithm more suitable for LoRa IoT.展开更多
基金Supported by Wuxi Municipal Health Commission Major Project,No.Z202107Wuxi Taihu Talent Project,No.WXTTP 2021.
文摘BACKGROUND The neural mechanisms underlying aggressive behavior in schizophrenia(SCZ)remain poorly understood.To date,no studies have reported on the event-related potential(ERP)characteristics of aggression in SCZ using the competitive reaction time task(CRTT).Further investigation into the ERP correlates of aggression in SCZ would provide valuable insights into the neural processes involved.AIM To explore the neural mechanism of aggressive behavior in SCZ.METHODS Participants of this study included 40 SCZ patients and 42 healthy controls(HCs).The Reactive Proactive Aggression Questionnaire was used to assess trait of aggression.The Barratt Impulsiveness Scale 11 was used to measure impulsiveness.The Positive and Negative Symptom Scale(PANSS)was used to evaluate psychopathological features and disease severity.All participants were measured with ERP while performing the CRTT.Data of behavior,ERP components(P2,N2,and P3),and feedback-related negativity(FRN)were analyzed.RESULTS Analysis of the behavioral data revealed that compared with HCs,SCZ patients exhibited higher punishment choices.Analysis of ERP components showed that compared with HCs,SCZ patients exhibited higher N2 amplitudes and P2 amplitudes during the decision phase of the CRTT;however,SCZ patients exhibited lower FRN amplitudes and lower P3 amplitudes during the outcome phase of the CRTT.The N2 amplitudes evoked by highintensity provocation were positively related to PANSS-P scores.And the P3 amplitudes evoked in the winning trials were negatively correlated with the PANSS-G scores.CONCLUSION SCZ patients exhibit abnormal ERP characteristics evoked by the CRTT,which suggests the neural correlates of aggressive behavior in SCZ.
基金Supported by the Fundamental Research Funds for the Central Universities(Grant No.JUSRP51317B)the National Natural Science Foundation of China(Grant No.60875036)
文摘In this paper, competitive neural networks with time-varying and distributed delays are investigated. By utilizing Lyapunov functional methods, the global exponential stability of periodic solutions of the neural networks is discussed on time scales. In addition, an example is given to illustrate the effectiveness of the theoretical results.
基金supported by the Shaanxi Science and Technology Department of International Science ( 2018KW025 )he Xi’an Science and Technology Plan Project and Technology Cooperation Program ( 2019218114GXRC017CG018GXYD17. 2 )+1 种基金the Shaanxi Provincial Department of Education Special Scientific Research Plan ( 18JK0700 )the IoT Innovation Team for Talent Promotion Plan of Shaanxi Province Support ( 2019TD-028)。
文摘To improve the efficiency and stability of data transmission in the long-range(LoRa) Internet of things(IoT),a hybrid time slot allocation algorithm is proposed, which implements a priority mechanism with high-priority nodes sending data in fixed time slots and low-priority nodes using the carrier sense multiple access(CSMA) algorithm to compete for shared time slots to transmit data. To improve network efficiency, a gateway is used to adjust the time slot allocation policy according to network status and balance the number of fixed and shared time slots. And more, a retransmission time slot is added to the time slot allocation algorithm, which redesigns the time frame structure, and adopts a retransmission mechanism to improve communication reliability. Simulation and measurement results show that the packet loss rate and transmission delay of the proposed hybrid algorithm are smaller than those of the fixed slot allocation algorithm, making the proposed algorithm more suitable for LoRa IoT.
