We designed a simple structure maze to test participants’ ability of navigation.
We could thus focus on the influence of different typical landmarks on navigation which was relatively independent from the geometric structures. We discussed several factors which may affect the behavioral performance in spatial navigation. We also reported results regarding how different types of landmarks influence spatial navigation.
Further, we investigated the brain dynamics associated with spatial navigation.
We adopted the independent component analysis (ICA) and event related spectral perturbations analysis (ERSP) to compare the EEG results corresponding to different types of landmarks. The theta power increased in the frontal midline component during spatial navigation. Females had better performance in the global condition than in the local condition in path ratio. The results of brain dynamics experiment consisted with the results of behavioral experiment. No matter subjects were familiar with the virtual environment or not, subjects spent more time on walking along paths that were not directly leading to the target. Performance differed between different of landmarks. We observed the significant difference in theta power between the global and the local condition by permutation tests.
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APPENDIX
SSE is the square of error sum. SSC is the average sum of squares. The ANOVA estimates the variance within the populations and the variance of inter-populations by sampling data. The freedom of each population is used to apply the F distribution test.The one-way analysis of variance (one-way ANOVA) is a technique used to compare means of two or more samples. The one-way ANOVA is used to test the average of groups and one-way ANOVA is used to test whether these differences are significant. It appears to test the average, but it analyzes the variance in fact. The one-way ANOVA is a robust procedure relative to violations of the normality assumptions. (a) Variables must be normally distributed. (b)The sample is a simple random sample (SRS). (c)Samples are independent. (d)Variances of populations are equal. The ratio of variance is a comparison of the variance amongst the different populations.
One-way ANOVA: αi is the effect of the ith populations
1. Variance of the inter-groups
H0：α1 = α2 =…= αk = 0， (17)
The one-way ANOVA measures significant effects of one factor only and the two-way ANOVA measures the effects of two factors simultaneously. The methods of ANOVA tests are divided into non-repeat experiment and repeated experiment. For non-repeat experiment of two-way ANOVA, the data are classified with two factors and the factors are tested individually to see whether there are significant impacts on the average for two factors. Classification variables are used to test the relationship between the independent variables and the dependent variables. We can see if there is any interaction between them. For repeated experiment, one-way ANOVA is used to test the different values of the same group in the different situations. For repeated experiment of two-way ANOVA, the above test is processed in addition and then we can observe the impact of the interaction between two independent variables and the dependent variable.
Column variance= (24)
(35) (36)
MSE Fc = MSC
(3)The rejected region
(1) CR1 = { Fr > Fα ( r - 1 , (r -1)(c-1) ) } (37) (2) CR2 = { Fc > Fα ( r - 1 , (r -1)(c-1) ) } (38)
(4)The values of tests statistic is used to calculate in H0 state.
(39) MSE MSR
0 = Fr
(40) MSE
MSC
0 = Fc