Research On The Role Of Attention Load And Temporal Structure In Predicting Motion Estimatio

Prediction-motion(PM)is to determine when the moving object reaches the target position.Accurately judging the reappearance time and location of occluded objects helps individuals successfully interact with them.In the PM task,the individual needs to estimate the time-tocontact or time-to-collision(TTC)of the moving object,which is the time interval between when the moving object is occluded and when the occlusion ends.Previous studies have found that attention load,estimation strategies(speed strategy and timing strategy),and the temporal structure of the motion path(the ratio of the visible path to the occluded path)all have an impact on the estimated TTC,however,the joint effect of the three on estimating TTC is not yet clear.In recent years,studies have shown that the brain may have a common rate control(CRC)mechanism,which can perform dynamic mental simulations of changes in position and number.However,the performance of individual estimation of TTC in different feature spaces such as positions and numbers is similar,so what is the impact of attention load and temporal structure of motion paths on TTC estimation in different feature spaces? Attention plays an important role in daily life and work,and it has important theoretical significance and practical value to explore the influence of attention load on estimating TTC.In this study,three experiments were conducted to systematically explore the influence mechanism of attention load and time structure on PM estimation.In experiment 1,participants’ attentional load was manipulated by digital memory task to explore the effect of attentional load on TTC estimation.It was found that the accuracy of TTC estimation under high-load condition was higher than that under low-load condition,which was consistent with previous results.The reason for this may be that under high-load,individuals reduce the attention resources invested in TTC estimation,reduce the interference of top-down cognitive factors,promote their perception of global movement information,and thus improve the accuracy of TTC estimation.Experiment 2a and Experiment 2b explored the effect of attentional load on TTC estimation with different temporal structures under different estimation strategies.Experiment 2a explored the effect of attentional load in estimating TTC under the speed strategy.This experiment used an occlusion paradigm,where moving objects were initially visible and subsequently occluded.Experiment 2b explored the effect of attentional load in estimating TTC under the timing strategy.This experiment used a flickering paradigm,that was,moving objects were visible at the origin and occlusion points,and invisible the rest of the time.The results of experiment 2a found that the interaction between attentional load and time structure was significant.When the time structure was consistent,the effect of attentional load on the estimated TTC was not significantly different,and when the time structure was inconsistent,the subject’s TTC was estimated better under high load;experiment 2b found that Temporal structure has a significant effect on TTC estimation.When the time structure was consistent,TTC estimation was more accurate than when the time structure was inconsistent,while attention load had no significant effect on it.Experiment 3 explored the effects of attentional load and temporal structure on digit PM estimation using the digital PM task.The results showed that the interaction between attentional load and temporal structure was significant.Under the condition of consistent temporal structure,the effect of attentional load on the estimation of digital PM task was not significant;however,under the condition of inconsistent temporal structure,digital PM estimation with high attentional load was more accurate.In addition,we compared the results of experiment 2a and experiment 3,and found that for the estimation of TTC,the effect of attention load on time structure was mainly through affecting the estimation sensitivity of subjects.For digital PM estimation,attention load affects the accuracy of the estimation by affecting the estimation bias of the subjects.This may be because the existence of the prior experience of the internal integer ratio changes the sensitivity of time estimation less.There were differences in the impact mechanism of attentional load on time estimation under different dimensions.Through the above three experiments,we revealed the impact mechanism of attention load and time structure on PM estimation,which differed with individual estimation strategy and feature space.Individuals can adjust dynamically in PM estimation based on information such as the objective environment and the availability of cues.In real life,the background of PM estimation is variable,so researchers can better understand how individuals estimate TTC,which can provide guarantee for individuals to effectively respond to events in the environment.In the future,it is necessary to further explore the influence of attention in other sensory channels and other dimensions on PM task,and explore how to realize the adjustment of neural network for PM task processing at the level of neural functional connection of attention.