Prey Capture

Background:

Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, which intercept their prey in midair with a 95% success rate (Olberg et. al, 2007). Target-selective descending neurons (TSDNs) are thought to command the dragonfly trajectory during fast aerial attacks for the following reasons (Gonzalez, 2012):

Each TSDN has particular preference for target location, direction, and size.
TSDNs receive information about the position and direction of a small target and relay it to all three ganglia (prothoracic, mesothoracic, and metathoracic).
In the absence of a moving target, the activity of TSDNs is zero.
The axon diameters of TSDNs are among the largest found in the ventral nerve cord, providing a high conduction speed necessary for the behavior.
Electrical stimulation of individual TSDNs alters the position/angle of the wings.

For these reasons, scientists believe it is important to examine whether TSDNs use a population vector to accurately code prey direction and control wing movement.

Recent Study:

Scientists aimed to understand the information sent to the wings when a target moves across the dragonfly visual field. More specifically, they tested whether a population vector algorithm could successfully decode the dire

To test this, they carried out intracellular recordings and confocal imaging of the TSDNs in the dragonfly species Libellula luctuosa. Each TSDN type showed a unique direction tuning curve and receptive field (Fig. 2). Although TSDNs do not sample the visual space equally, the overlapping direction tuning curves and receptive fields of the different TSDNs suggest that the population vector from all TSDN responses could code a change in the prey’s bearing (Fig. 3). The study’s results show that the population vector of the TSDNs codes the prey direction with extreme accuracy in all of the 360° tested (Gonzalez, 2012).

Figure 3. The visual receptive fields of the TSDNs combine to create an area of increased sensitivity to target movement near the midline (Gonzalez, 2012).

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Figure 1. Graphical representation of a dragonfly TSDN population vector. Contributing TSDN vectors (green), stimulus direction (yellow), and population vector (red) are shown (Gonzalez, 2012).

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ctional component of the descending information. The population vector (Fig. 1) could allow the steering system to act on autopilot, providing the fast reaction speed displayed by dragonflies during predatory behavior.

Figure 2. Polar plots show the directional preference of each recorded TSDN (red dots) and their mean direction tuning distribution (black bars) (Gonzalez, 2012).

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Conclusion:

This prey detection system in dragonflies relies on a low number of cells performing with high accuracy. The functional significance of the results is that the integration of signals and calculation of motor output seem to occur at the thoracic ganglia, and not in the brain; all of the TSDNs target the dorsal part of mesothoracic and the metathoracic ganglia dedicated to motor/efferent fibers. Therefore, if the TSDN branching pattern does not filter the electrical activity in a ganglion-specific manner, the information provided by each TSDN should be available nearly simultaneously to both the fore and hind wings of the targeted side (Gonzalez, 2012).

Application:

Computer modeling suggests that this algorithm could drive an airborne target interception system successfully (Gonzalez, 2012).

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Figure 4. Accuracy of population vector vs. number of TSDN’s (Gonzalez, 2012).

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The study found that, on average, if the population vector is calculated with six or more TSDN types, the vector is not significantly different from the target direction (t test, mean difference left wing, 1.23 ± 3.72° SD, P = 0.089; right wing, 1.19469 ± 3.49° SD, P = 0.07624) (Gonzalez, 2012). Even just three TSDN types are sufficient to provide a population vector accurate to within 10° of the presented target direction (Fig. 4) (Gonzalez, 2012).

References:

Gonzalez-Bellido, P. T., Peng, H., Yang, J., Georgopoulos, A.P., and Olberg, R.M. (2012). Eight Pairs of Descending Visual Neurons in the Dragonfly Give Wing Motor Centers

Accurate Population Vector of Prey Direction. Proceedings of the National Academy of Sciences, 110 (2), 696-701.

Olberg RM, Seaman RC, Coats MI, Henry AF (2007) Eye movements and target fixation during dragonfly prey-interception flights. J Comp Physiol A Neuroethol Sens Neural Behav

Physiol 193(7):685–693.

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