Analysis Of Neural Information Flow In Pigeon's Goal-directed Behavior

Neural information coding mechanism of goal-directed behavior in animal is a hot topic in neuroscience research.Pigeons have strong spatial navigation capabilities and have been widely used in recent years,namely,pigeons is an ideal animal model for goal-directed behavior research.Studies have shown that NCL brain region of pigeons plays an important role in goal-directed behavior,but its neural coding mechanism remains to be clarified.Therefore,in this thesis,pigeons as a model animal,from the point of view of the neural flow analysis,study the spatial and temporal information coding pattern of the local field potential signals of the pigeon's NCL brain region.This thesis designed an experimental paradigm for pigeons' goal-directed behavior and detected neural signals in the NCL brain region when three typical goal-directed behaviors(left turn,right turn,and straight line)occur.Firstly,the environmental and behavioral interference noise was removed,and then the related characteristic frequency bands were determined.Secondly,on the basis of the first part,selected the channel with high correlation and containing the main information to build a local causal network.Finally,the directed transfer function was used to analyze the information flow of the local network,and the information flow direction and intensity difference of the local causal network under the three typical behaviors are compared.The completed studies are as follows:(1)Y maze target-oriented experimental paradigm based on light indication and food induction was designed,and behavioral experiments were performed to record neural signals simultaneously.Considering the signal quality requirements of the information flow analysis,independent component analysis and common average reference filtering were used to remove the 50 Hz power frequency interference and the common reference generated by the pigeon movement in the local field potential signal.(2)The feature bands were determined and the selection of effective channelswas completed.The time-frequency analysis of the local field potential signals of three typical steering behaviors was performed,and the behavior-relevant gamma characteristic bands were determined and the band extraction was completed by a zero-phase digital filter.For the problem of multicollinearity between neural signals in each channel,combined with Pearson correlation and partial least-squares regression,the channels that are truly correlated and have a large proportion of information weight in the characteristic frequency band are determined.(3)Based on the directed transfer function,the change of information flow in goal-directed behavior is analyzed.Firstly,the effectiveness of the algorithm is verified by using the directed transfer function of the information flow analysis on the simulation data set.Then,from the aspects of information flow direction and intensity,the information flow analysis of pigeon goal-directed experimental records was performed.The results show that there are significant differences in the information flow between the three typical behaviors.