Hong-Jian Kang1, Xiao-Hong Li. 1. Kyushu Institute of Technology, Graduate School of Life Science and Systems Engineering, Department of Brain Science and Engineering, Kitakyushu, Fukuoka, Japan. hongjian01@hotmail.com
Abstract
OBJECTIVE: Many studies have reported that animals will display collision avoidance behavior when the size of retinal image of an object reaches a threshold. The present study aimed to investigate the neural correlates underlying the frog collision avoidance behavior. METHODS: Different types of visual stimuli simulating the retinal image of an approaching or a recessing object were generated by a computer and presented to the right eye of frog. A multielectrode array was used to examine the activity of collision-sensitive neurons, and single electrode recordings were employed to quantify visual parameter(s) of the frog collision-sensitive neurons. RESULTS: The multielectrode array revealed that 40 neurons in the optic tectum showed selective responsiveness to objects approaching on a direct collision course. The response profiles of these collision-sensitive neurons were similar to those of lobula giant movement detector (LGMD) in the locust or to those of neurons in the pigeon. However, the receptive field (RF) size of the frog neurons [(18.5+/-3.8) degrees, n=33)] was smaller than those of collision-sensitive neurons of the locust and the pigeon. Multielectrode recordings also showed that the collision-sensitive neurons were activated only when the focus of expansion of a looming retinal image was located within the center of its RF. There was a linear relationship between the parameter l/v (l denotes half-size of the object, v denotes approaching velocity) and time-to-collision (time difference between the peak of the neuronal activity and the predictive collision) in 16 collision-sensitive neurons. Theoretical consideration showed that the peak firing rate always occurred at a fixed delay of (60.1 +/- 39.5) ms (n=16) after the object had reached a constant angular size of (14.8 +/- 3.4) degrees (n=16) on the retina. CONCLUSION: The results may help clarify the mechanisms underlying the collision avoidance behavior in bullfrog.
OBJECTIVE: Many studies have reported that animals will display collision avoidance behavior when the size of retinal image of an object reaches a threshold. The present study aimed to investigate the neural correlates underlying the frog collision avoidance behavior. METHODS: Different types of visual stimuli simulating the retinal image of an approaching or a recessing object were generated by a computer and presented to the right eye of frog. A multielectrode array was used to examine the activity of collision-sensitive neurons, and single electrode recordings were employed to quantify visual parameter(s) of the frog collision-sensitive neurons. RESULTS: The multielectrode array revealed that 40 neurons in the optic tectum showed selective responsiveness to objects approaching on a direct collision course. The response profiles of these collision-sensitive neurons were similar to those of lobula giant movement detector (LGMD) in the locust or to those of neurons in the pigeon. However, the receptive field (RF) size of the frog neurons [(18.5+/-3.8) degrees, n=33)] was smaller than those of collision-sensitive neurons of the locust and the pigeon. Multielectrode recordings also showed that the collision-sensitive neurons were activated only when the focus of expansion of a looming retinal image was located within the center of its RF. There was a linear relationship between the parameter l/v (l denotes half-size of the object, v denotes approaching velocity) and time-to-collision (time difference between the peak of the neuronal activity and the predictive collision) in 16 collision-sensitive neurons. Theoretical consideration showed that the peak firing rate always occurred at a fixed delay of (60.1 +/- 39.5) ms (n=16) after the object had reached a constant angular size of (14.8 +/- 3.4) degrees (n=16) on the retina. CONCLUSION: The results may help clarify the mechanisms underlying the collision avoidance behavior in bullfrog.
Authors: Christopher M Ciarleglio; Arseny S Khakhalin; Angelia F Wang; Alexander C Constantino; Sarah P Yip; Carlos D Aizenman Journal: Elife Date: 2015-11-14 Impact factor: 8.140
Authors: Eric V Jang; Carolina Ramirez-Vizcarrondo; Carlos D Aizenman; Arseny S Khakhalin Journal: Front Neural Circuits Date: 2016-11-24 Impact factor: 3.492