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Abstract
An essential component of autonomous and flexible behavior in animals is active exploration of the environment, allowing for perception-guided planning and control of actions. An important sensory system involved is active touch. Here, we introduce a general modeling framework of Central Pattern Generators (CPGs) for movement generation in active tactile exploration behavior. The CPG consists of two network levels: (i) phase-coupled Hopf oscillators for rhythm generation, and (ii) pattern formation networks for capturing the frequency and phase characteristics of individual joint oscillations. The model captured the natural, quasi-rhythmic joint kinematics as observed in coordinated antennal movements of walking stick insects. Moreover, it successfully produced tactile exploration behavior on a three-dimensional skeletal model of the insect antennal system with physically realistic parameters. The effect of proprioceptor ablations could be simulated by changing the amplitude and offset parameters of the joint oscillators, only. As in the animal, the movement of both antennal joints was coupled with a stable phase difference, despite the quasi-rhythmicity of the joint angle time courses. We found that the phase-lead of the distal scape-pedicel (SP) joint relative to the proximal head-scape (HS) joint was essential for producing the natural tactile exploration behavior and, thus, for tactile efficiency. For realistic movement patterns, the phase-lead could vary within a limited range of 10–30° only. Tests with artificial movement patterns strongly suggest that this phase sensitivity is not a matter of the frequency composition of the natural movement pattern. Based on our modeling results, we propose that a constant phase difference is coded into the CPG of the antennal motor system and that proprioceptors are acting locally to regulate the joint movement amplitude.
Highlights
A basic element of autonomous intelligent behaviors is the ability to actively explore the surrounding environment with different sensing systems (Beer, 2000; Nelson and MacIver, 2006; Prescott et al, 2011)
We investigate the constraints of a stable phase difference in the presence of a variable, a quasi-rhythmic movement pattern with multiple frequency components
In order to determine whether this is true for single-trial models simulating the data from other individuals, we repeated the same experiment with different Pattern Formation networks (Equation 5), i.e., after setting the frequency characteristics (Figure 2) according to the frequency spectra measured from four further animals. In all of these cases, we found the same result: the antennal movement pattern substantially deteriorated for phase differences beyond ±15◦ with regard to the natural reference
Summary
A basic element of autonomous intelligent behaviors is the ability to actively explore the surrounding environment with different sensing systems (Beer, 2000; Nelson and MacIver, 2006; Prescott et al, 2011). While mammals like cats and rats use active whisker movements to detect and scan objects in the vicinity of their body (Cramer et al, 2007; Prescott et al, 2011), many walking insects and crustaceans continuously search and sample the space ahead with their antennae or feelers (Staudacher et al, 2005). In their ground plan, all higher insects carry two antennae with two actuated joints per antenna. The study and modeling of adaptive changes in coordination of insect antennal movements is of general interest to adaptive coordination of limbs, and of particular relevance to active sensing
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