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Neuronal Processing of Complex Mixtures Establishes a Unique Odor Representation in the Moth Antennal Lobe
Animals typically perceive natural odor cues in their olfactory environment as a complex mixture of chemically diverse components. In insects, the initial representation of an odor mixture occurs in the first olfactory center of the brain, the antennal lobe (AL). The contribution of single neurons t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3128929/ https://www.ncbi.nlm.nih.gov/pubmed/21772814 http://dx.doi.org/10.3389/fncir.2011.00007 |
Sumario: | Animals typically perceive natural odor cues in their olfactory environment as a complex mixture of chemically diverse components. In insects, the initial representation of an odor mixture occurs in the first olfactory center of the brain, the antennal lobe (AL). The contribution of single neurons to the processing of complex mixtures in insects, and in particular moths, is still largely unknown. Using a novel multicomponent stimulus system to equilibrate component and mixture concentrations according to vapor pressure, we performed intracellular recordings of projection and interneurons in an attempt to quantitatively characterize mixture representation and integration properties of single AL neurons in the moth. We found that the fine spatiotemporal representation of 2–7 component mixtures among single neurons in the AL revealed a highly combinatorial, non-linear process for coding host mixtures presumably shaped by the AL network: 82% of mixture responding projection neurons and local interneurons showed non-linear spike frequencies in response to a defined host odor mixture, exhibiting an array of interactions including suppression, hypoadditivity, and synergism. Our results indicate that odor mixtures are represented by each cell as a unique combinatorial representation, and there is no general rule by which the network computes the mixture in comparison to single components. On the single neuron level, we show that those differences manifest in a variety of parameters, including the spatial location, frequency, latency, and temporal pattern of the response kinetics. |
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