Preattentive facilitation of target trajectories in a dragonfly visual neuron.

The ability to pursue targets in visually cluttered and distraction-rich environments is critical for predators such as dragonflies. Previously, we identified Centrifugal Small-Target Motion Detector 1 (CSTMD1), a dragonfly visual neuron likely involved in such target-tracking behaviour. CSTMD1 exhibits facilitated responses to targets moving along a continuous trajectory. Moreover, CSTMD1 competitively selects a single target out of a pair. Here, we conducted in vivo, intracellular recordings from CSTMD1 to examine the interplay between facilitation and selection, in response to the presentation of paired targets. We find that neuronal responses to both individual trajectories of simultaneous, paired targets are facilitated, rather than being constrained to the single, selected target. Additionally, switches in selection elicit suppression which is likely an important attribute underlying target pursuit. However, binocular experiments reveal these results are constrained to paired targets within the same visual hemifield, while selection of a target in one visual hemifield establishes ocular dominance that prevents facilitation or response to contralaterally presented targets. These results reveal that the dragonfly brain preattentively represents more than one target trajectory, to balance between attentional flexibility and resistance against distraction.

The visual neuroecology of anisoptera.

Dragonflies belong to the oldest known lineage of flying animals, found across the globe around streams, ponds and forests. They are insect predators, specialising in ambush attack as aquatic larvae and rapid pursuit as adults. Dragonfly adults hunt amidst swarms in conditions that confuse many predatory species, and exhibit capture rates above 90%. Underlying the performance of such a remarkable predator is a finely tuned visual system capable of tracking targets amidst distractors and background clutter. The dragonfly performs a complex repertoire of flight behaviours, from near-motionless hovering to acute turns at high speeds. Here, we review the optical, neuronal, and behavioural adaptations that underlie the dragonflies' ability to achieve such remarkable predatory success.

A Target-Detecting Visual Neuron in the Dragonfly Locks on to Selectively Attended Targets.

The visual world projects a complex and rapidly changing image onto the retina of many animal species. This presents computational challenges for those animals reliant on visual processing to provide an accurate representation of the world. One such challenge is parsing a visual scene for the most salient targets, such as the selection of prey amid a swarm. The ability to selectively prioritize processing of some stimuli over others is known as 'selective attention'. We recently identified a dragonfly visual neuron called 'Centrifugal Small Target Motion Detector 1' (CSTMD1) that exhibits selective attention when presented with multiple, equally salient targets. Here we conducted in vivo, electrophysiological recordings from CSTMD1 in wild-caught male dragonflies (Hemicordulia tau), while presenting visual stimuli on an LCD monitor. To identify the target selected in any given trial, we uniquely modulated the intensity of the moving targets (frequency tagging). We found that the frequency information of the selected target is preserved in the neuronal response, while the distracter is completely ignored. We also show that the competitive system that underlies selection in this neuron can be biased by the presentation of a preceding target on the same trajectory, even when it is of lower contrast than an abrupt, novel distracter. With this improved method for identifying and biasing target selection in CSTMD1, the dragonfly provides an ideal animal model system to probe the neuronal mechanisms underlying selective attention.SIGNIFICANCE STATEMENT We present the first application of frequency tagging to intracellular neuronal recordings, demonstrating that the frequency component of a stimulus is encoded in the spiking response of an individual neuron. Using this technique as an identifier, we demonstrate that CSTMD1 'locks on' to a selected target and encodes the absolute strength of this target, even in the presence of abruptly appearing, high-contrast distracters. The underlying mechanism also permits the selection mechanism to switch between targets mid-trial, even among equivalent targets. Together, these results demonstrate greater complexity in this selective attention system than would be expected in a winner-takes-all network. These results are in contrast to typical findings in the primate and avian brain, but display intriguing resemblance to observations in human psychophysics.

Polymorphisms that affect GABA neurotransmission predict processing of aversive prediction errors in humans.

Learning is one of our most adaptive abilities, allowing us to adjust our expectations about future events. Aberrant learning processes may underlie disorders such as anxiety, motivating the search for the neural mechanisms that underpin learning. Animal studies have shown that the neurotransmitter GABA is required for the computation of prediction errors, the mismatches between anticipated and experienced outcomes, which drive new learning. Given that evidence from human studies is lacking, we sought to determine whether these findings extend to humans. Here, in two samples of Caucasian individuals, we investigated whether genetically determined individual differences in GABA neurotransmission predict the P3 event-related potential, an EEG component known to reflect prediction error processing. Consistent with the results of animal studies, we show that a weighted genetic risk score computed from the number of GABRB2 rs1816072 A alleles (associated with increased expression of the GABAA receptor ß2 subunit gene) and the number of ErbB4 rs7598440 T alleles (associated with increased GABA concentration) predicts optimal prediction error processing during aversive classical conditioning with both visual (Experiment 1, N = 90; p = .010) and auditory (Experiment 2; N = 92; p = .031) unconditioned stimuli. Our finding that optimal processing of aversive prediction errors is reduced in individuals genetically predisposed towards decreased GABA neurotransmission suggests a potential mechanism linking GABA and anxiety. Specifically, reduced GABA signalling via GABAA receptors could result in aberrant learning from aversive experiences and vulnerability to anxiety disorders.