The binaural masking level difference(BMLD)is a psychoacoustic method to determine binaural interaction and central auditory processes.The BMLD is the difference in hearing thresholds in homophasic and antiphasic cond...The binaural masking level difference(BMLD)is a psychoacoustic method to determine binaural interaction and central auditory processes.The BMLD is the difference in hearing thresholds in homophasic and antiphasic conditions.The duration,phase and frequency of the stimuli can affect the BMLD.The main aim of the study is to evaluate the BMLD for stimuli of different durations and frequencies which could also be used in future electrophysiological studies.To this end we developed a GUI to present different frequency signals of variable duration and determine the BMLD.Three different durations and five different frequencies are explored.The results of the study confirm that the hearing threshold for the antiphasic condition is lower than the hearing threshold for the homophasic condition and that differences are significant for signals of 18ms and 48ms duration.Future objective binaural processing studies will be based on 18ms and 48ms stimuli with the same frequencies as used in the current study.展开更多
The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatl...The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatly. Robot localization and decisionmaking are the most important cognitive processes during navigation. However, most of these algorithms are not efficient and are challenging tasks while robots navigate through complex environments. In this paper,we propose a biologically inspired method for robot decision-making, based on rat’s brain signals. Rodents accurately and rapidly navigate in complex spaces by localizing themselves in reference to the surrounding environmental landmarks. Firstly, we analyzed the rats’ strategies while navigating in the complex Y-maze, and recorded local field potentials(LFPs), simultaneously.The recorded LFPs were processed and different features were extracted which were used as the input in the artificial neural network(ANN) to predict the rat’s decision-making in each junction. The ANN performance was tested in a real robot and good performance is achieved. The implementation of our method on a real robot, demonstrates its abilities to imitate the rat’s decision-making and integrate the internal states with external sensors, in order to perform reliable navigation in complex maze.展开更多
文摘The binaural masking level difference(BMLD)is a psychoacoustic method to determine binaural interaction and central auditory processes.The BMLD is the difference in hearing thresholds in homophasic and antiphasic conditions.The duration,phase and frequency of the stimuli can affect the BMLD.The main aim of the study is to evaluate the BMLD for stimuli of different durations and frequencies which could also be used in future electrophysiological studies.To this end we developed a GUI to present different frequency signals of variable duration and determine the BMLD.Three different durations and five different frequencies are explored.The results of the study confirm that the hearing threshold for the antiphasic condition is lower than the hearing threshold for the homophasic condition and that differences are significant for signals of 18ms and 48ms duration.Future objective binaural processing studies will be based on 18ms and 48ms stimuli with the same frequencies as used in the current study.
基金supported by the Japanese Government,Grants-in-Aid for Scientific Research 2014 to 2016 under Grant No.26330296
文摘The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatly. Robot localization and decisionmaking are the most important cognitive processes during navigation. However, most of these algorithms are not efficient and are challenging tasks while robots navigate through complex environments. In this paper,we propose a biologically inspired method for robot decision-making, based on rat’s brain signals. Rodents accurately and rapidly navigate in complex spaces by localizing themselves in reference to the surrounding environmental landmarks. Firstly, we analyzed the rats’ strategies while navigating in the complex Y-maze, and recorded local field potentials(LFPs), simultaneously.The recorded LFPs were processed and different features were extracted which were used as the input in the artificial neural network(ANN) to predict the rat’s decision-making in each junction. The ANN performance was tested in a real robot and good performance is achieved. The implementation of our method on a real robot, demonstrates its abilities to imitate the rat’s decision-making and integrate the internal states with external sensors, in order to perform reliable navigation in complex maze.
