外侧丘系腹核(ventral nucleus of the lateral lemniscus,VNLL)是中枢听觉通路中连接耳蜗核等低位脑干和中脑下丘(inferior colliculus,IC)的重要核团,其神经元能够对声信号的不同参数进行检测与加工,进而形成多样的声反应特性。VNLL...外侧丘系腹核(ventral nucleus of the lateral lemniscus,VNLL)是中枢听觉通路中连接耳蜗核等低位脑干和中脑下丘(inferior colliculus,IC)的重要核团,其神经元能够对声信号的不同参数进行检测与加工,进而形成多样的声反应特性。VNLL神经元对频率反应的调谐曲线有多种类型,但其锐化程度一般较低,对频率的分析亦不够精确;有关强度调谐的放电率函数分为两种类型:单调型与非单调型,它们对强度的加工和编码往往受到发放模式的影响;不同发放模式的VNLL神经元对时程的编码能力不同,其中起始型具有精确的时间特性,适合编码声刺激的起始时间信息,对蝙蝠的回声定位非常重要。VNLL接受来自低位核团的输入,并发出上行的抑制性投射至IC,在IC神经元的声信息检测过程中发挥重要作用。近来研究认为VNLL快速的抑制性投射延迟IC神经元的首次发放潜伏期,VNLL延迟的抑制性投射介导IC神经元的发放模式,但VNLL抑制性输入如何在IC进行整合,并增强IC神经元检测声信号能力的机制并不清楚,且缺乏VNLL对IC进行实时调控作用的直接证据。这些问题的研究有助于进一步认识上行输入在声信号加工过程中的作用,同时也是本实验室今后的研究重点。本文结合本实验室相关研究,围绕VNLL对听觉信号的加工和上行传导进行综述。展开更多
In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and th...In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n+2.67)M^3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness.展开更多
基金supported by grants from the National Natural Science Foundation of China(No.31000493)Independent Scientific Research Project Fund for Youth Doctors from Central China Normal University(No.11A01025)+1 种基金Foundation of Hubei Key Laboratory of Genetic Regulation and Integrative BiologyChina
文摘外侧丘系腹核(ventral nucleus of the lateral lemniscus,VNLL)是中枢听觉通路中连接耳蜗核等低位脑干和中脑下丘(inferior colliculus,IC)的重要核团,其神经元能够对声信号的不同参数进行检测与加工,进而形成多样的声反应特性。VNLL神经元对频率反应的调谐曲线有多种类型,但其锐化程度一般较低,对频率的分析亦不够精确;有关强度调谐的放电率函数分为两种类型:单调型与非单调型,它们对强度的加工和编码往往受到发放模式的影响;不同发放模式的VNLL神经元对时程的编码能力不同,其中起始型具有精确的时间特性,适合编码声刺激的起始时间信息,对蝙蝠的回声定位非常重要。VNLL接受来自低位核团的输入,并发出上行的抑制性投射至IC,在IC神经元的声信息检测过程中发挥重要作用。近来研究认为VNLL快速的抑制性投射延迟IC神经元的首次发放潜伏期,VNLL延迟的抑制性投射介导IC神经元的发放模式,但VNLL抑制性输入如何在IC进行整合,并增强IC神经元检测声信号能力的机制并不清楚,且缺乏VNLL对IC进行实时调控作用的直接证据。这些问题的研究有助于进一步认识上行输入在声信号加工过程中的作用,同时也是本实验室今后的研究重点。本文结合本实验室相关研究,围绕VNLL对听觉信号的加工和上行传导进行综述。
基金Supported by the National Natural Science Foundation of China (No.60102005).
文摘In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n+2.67)M^3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness.
