Collision-Sensitive Neurons in the Optic Tectum of the Bullfrog,Rana catesbeiana

Abstract

In this study, we examined the neuronal correlates of frog collision avoidance behavior. Single unit recordings in the optic tectum showed that 11 neurons gave selective responses to objects approaching on a direct collision course. The collision-sensitive neurons exhibited extremely tight tuning for collision bound trajectories with mean half-width at half height values of 0.8 and 0.9° (n = 4) for horizontal and vertical deviations, respectively. The response of frog collision-sensitive neurons can be fitted by a function that simply multiplies the size dependence of its response, e(-αθ(t)), by the image's instantaneous angular velocity θ'(t). Using fitting analysis, we showed that the peak firing rate always occurred after the approaching object had reached a constant visual angle of 24.2 ± 2.6° (mean ± SD; n = 8), regardless of the approaching velocity. Moreover, a linear relationship was demonstrated between parameters l/v (l: object's half-size, v: approach velocity) and time-to-collision (time difference between peak neuronal activity and the predicted collision) in the 11 collision-sensitive neurons. In addition, linear regression analysis was used to show that peak firing rate always occurred after the object had reached a constant angular size of 21.1° on the retina. The angular thresholds revealed by both theoretical analyses were comparable and showed a good agreement with that revealed by our previous behavioral experiments. This strongly suggests that the collision-sensitive neurons of the frog comprise a threshold detector, which triggers collision avoidance behavior.

Speed-invariant encoding of looming object distance requires power law spike rate adaptation

“…In turn, the torus provides massive input to the optic tectum (46), an analog of the mammalian superior colliculus. "Collision-sensitive" neurons have been discovered in the optic tectum of frogs (47), suggesting that the differential responses of ELL pyramidal cells initiate distinct streams of information, which serve as the basis for tectal neurons to compute and initiate appropriate motor commands in response to looming stimuli.…”

Blowfly flight characteristics are shaped by environmental features and controlled by optic flow information

“…Accordingly, saccade rate is, on average, lower and saccade amplitudes are smaller the longer the estimated time-to-contact to an obstacle. Neurons, signaling time-to-contact either of an approaching object or during the animal's approach towards surfaces, have been described in various animals, including frogs (Nakagawa and Kang, 2010), gerbils (Shankar and Ellard, 2000), pigeons (Frost and Sun, 2004), hawk moths (Wicklein and Strausfeld, 2000), mantids (Yamawaki and Toh, 2009), locusts (Rind and Simmons, 1997;Gabbiani et al, 1999) and Drosophila (de Vries and Clandinin, 2012;Fotowat et al, 2009). In blowflies, such neurons have not yet been characterized.…”

Bilateral flight muscle activity predicts wing kinematics and 3-dimensional body orientation of locusts responding to looming objects

“…Generating appropriate aerodynamic forces while staying aloft requires rapid detection and integration of salient visual cues. Animals have evolved neural circuitry adapted to preferentially detect visual edge expansion of looming stimuli and respond accordingly by generating emergency escape behaviours [for example, frogs (Nakagawa and Hongjian, 2010), cats (Liu et al, 2011), pigeons (Wang and Frost, 1992), crabs (Oliva et al, 2007;Sztarker and Tomsic, 2008) and insects such as flies (Holmqvist and Srinivasan, 1991;Fotowat et al, 2009) and locusts (Robertson and Reye, 1992;Robertson and Johnson, 1993;Gray et al, 2001;Santer et al, 2005;Simmons et al, 2010;Fotowat et al, 2011;Chan and Gabbiani, 2013)]. …”