Soltanzadeh Mohammad Javad, Daliri Mohammad Reza
Neuroscience Research Laboratory, Biomedical Engineering Department, Faculty of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
Neuroscience Research Laboratory, Biomedical Engineering Department, Faculty of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran ; Cognitive Neuroscience Laboratory, German Primate Center (DPZ), Goettingen, Germany.
Basic Clin Neurosci. 2014 Summer;5(3):205-11.
Direction and latency of electrical connectivity between different sites of brain explains brain neural functionality. We compared efficiency of cross correlation and phase locking methods in time lag estimation which are based on local field potential (LFP) and LFP-spike signals, respectively.
Signals recorded from MT area of a macaque's brain was used in a simulation approach. The first signal was real brain activity and the second was identical to the first one, but with two kinds of delayed and not delayed forms. Time lag between two signals was estimated by cross correlation and phase locking methods.
Both methods estimated the time lags with no errors. Phase locking was not as time efficient as correlation. In addition, phase locking suffered from temporal self bias.
Correlation was a more efficient method. Phase locking was not considered as a proper method to estimate the time lags between brain sites due to time inefficiency and self bias, the problems which are reported for the first time about this method.
大脑不同部位之间电连接的方向和潜伏期解释了大脑的神经功能。我们比较了分别基于局部场电位(LFP)和LFP-尖峰信号的互相关和锁相方法在时间滞后估计中的效率。
在模拟方法中使用从猕猴大脑MT区域记录的信号。第一个信号是真实的大脑活动,第二个信号与第一个信号相同,但有两种延迟和未延迟的形式。通过互相关和锁相方法估计两个信号之间的时间滞后。
两种方法都能准确估计时间滞后。锁相比互相关在时间效率上更低。此外,锁相存在时间自偏倚。
互相关是一种更有效的方法。由于时间效率低和自偏倚,锁相不被认为是估计脑区之间时间滞后的合适方法,这些问题首次针对该方法被报道。