To proceed from sensation to movement, integration and transformation of information from different senses and reference frames are required. Several brain areas are involved in this transformation process, but previous neuroanatomical and neurophysiological studies have implicated the caudal area 7b as one particular component of this transformation system. In this study, we present the first quantitative report on the spatial coding properties of caudal area 7b. The results showed that neurons in this area had intermediate component characteristics in the transformation system; the area contained bimodal neurons, and neurons in this area encode spatial information using a hybrid reference frame. These results provide evidence that caudal area 7b may belong to the reference frame transformation system, thus contributing to our general understanding of the transformation system.
Hui-Hui JIANGYing-Zhou HUJian-Hong WANGYuan-Ye MAXin-Tian HU
To proceed from sensation to movement,integration and transformation of information from different senses and reference frames are required.Several brain areas are involved in this transformation process,but previous neuroanatomical and neurophysiological studies have implicated the caudal area 7b as one particular component of this transformation system.In this study,we present the first quantitative report on the spatial coding properties of caudal area 7b.The results showed that neurons in this area had intermediate component characteristics in the transformation system;the area contained bimodal neurons,and neurons in this area encode spatial information using a hybrid reference frame.These results provide evidence that caudal area 7b may belong to the reference frame transformation system,thus contributing to our general understanding of the transformation system.
Hui-Hui JIANGYing-Zhou HUJian-Hong WANGYuan-Ye MAXin-Tian HU
A novel method based on machine learning is developed to estimate event-related potentials from single trial electroencephalography. This paper builds a basic framework using classification and an optimization model based on this framework for estimating event-related potentials. Then the SingleTrialEM algorithm is derived by introducing a logistic regression model, which could be obtained by training before SingleTrialEM is used, to instantiate the optimization model. The simulation tests demonstrate that the proposed method is correct and solid. The advantage of this method is verified by the comparison between this method and the Woody filter in simulation tests. Also, the cognitive test results are consistent with the conclusions of cognitive science.
