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Updated: Jun 15, 2026

New Methods to Study Gustatory Coding
Published on: June 29, 2017
Central gustatory neurons integrate taste quality information from four appendages in the moth Heliothis virescens
Pål Kvello1, Kari Jørgensen, Hanna Mustaparta
1Neuroscience Unit, Department of Biology, Norwegian University of Science and Technology, Olav Kyrres Gate 9, N-7489 Trondheim, Norway.
Abstract:
Discrimination between edible and noxious food, crucial for animal survival, is based on separate gustatory receptors for phagostimulants and deterrents. In the moth Heliothis virescens, gustatory receptor neurons (GRNs) tuned to phagostimulants like sucrose and deterrents like quinine, respectively, have indicated a labeled line mechanism for mediating appetitive and aversive information to the CNS. In the present study, we have investigated the central gustatory neurons (CGNs) in this moth as an approach to understand how gustatory information is coded in the CNS. Intracellular recordings from CGNs in the suboesophageal ganglion (SOG) combined with fluorescent staining revealed a large diversity of CGN types responding to sucrose, quinine, water, and mechanosensory stimuli applied to the antennae, the proboscis, and the right tarsus. The CGNs responded with varying tuning breadth to tastants applied to more than one appendage. This integration of information across stimuli and appendages, contradict a simple labeled line mechanism in the CNS for coding identity and location of taste stimuli. Instead the distinct pattern of activity found in an ensemble of CGNs, suggests a population coding mechanism. Staining revealed that the majority of the CGNs were confined locally within the SOG/tritocerebrum, whereas others projected to the deutocerebrum, protocerebrum, frontal ganglion, and thoracic ganglia. Some CGNs were reconstructed and registered into the H. virescens standard brain atlas, showing dendritic overlap with the previously described GRN projections. In general, the physiology and morphology of the CGNs suggested multifunctional properties, where a single CGN might belong to several networks executing different functions.
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