期刊
JOURNAL OF NEUROSCIENCE
卷 39, 期 43, 页码 8497-8509出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.1431-19.2019
关键词
predictive gain modulation; target detection; insect vision; priming; selective attention; winner-takes-all
资金
- Australian Research Council's Future Fellowship Scheme [FF180100466]
- Australian Government Research Training Program (RTP)
- Swedish Research Council [VR 2014-4904, VR 2018-03452]
- Swedish Foundation for International Cooperation in Research and Higher Education (STINT)
- Swedish Research Council [2018-03452] Funding Source: Swedish Research Council
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据