Dataset Information

Multimodal integration and stimulus categorization in putative mushroom body output neurons of the honeybee.

ABSTRACT: Flowers attract pollinating insects like honeybees by sophisticated compositions of olfactory and visual cues. Using honeybees as a model to study olfactory-visual integration at the neuronal level, we focused on mushroom body (MB) output neurons (MBON). From a neuronal circuit perspective, MBONs represent a prominent level of sensory-modality convergence in the insect brain. We established an experimental design allowing electrophysiological characterization of olfactory, visual, as well as olfactory-visual induced activation of individual MBONs. Despite the obvious convergence of olfactory and visual pathways in the MB, we found numerous unimodal MBONs. However, a substantial proportion of MBONs (32%) responded to both modalities and thus integrated olfactory-visual information across MB input layers. In these neurons, representation of the olfactory-visual compound was significantly increased compared with that of single components, suggesting an additive, but nonlinear integration. Population analyses of olfactory-visual MBONs revealed three categories: (i) olfactory, (ii) visual and (iii) olfactory-visual compound stimuli. Interestingly, no significant differentiation was apparent regarding different stimulus qualities within these categories. We conclude that encoding of stimulus quality within a modality is largely completed at the level of MB input, and information at the MB output is integrated across modalities to efficiently categorize sensory information for downstream behavioural decision processing.

SUBMITTER: Strube-Bloss MF

PROVIDER: S-EPMC5830775 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Multisensory integration plays a central role in perception, as all behaviors usually require the input of different sensory signals. For instance, for a foraging honeybee the association of a food source includes the combination of olfactory and visual cues to be categorized as a flower. Moreover, homing after successful foraging using celestial cues and the panoramic scenery may be dominated by visual cues. Hence, dependent on the context, one modality might be leading and influence the processing of other modalities. To unravel the complex neural mechanisms behind this process we studied honeybee mushroom body output neurons (MBON). MBONs represent the first processing level after olfactory-visual convergence in the honeybee brain. This was physiologically confirmed in our previous study by characterizing a subpopulation of multisensory MBONs. These neurons categorize incoming sensory inputs into olfactory, visual, and olfactory-visual information. However, in addition to multisensory units a prominent population of MBONs was sensitive to visual cues only. Therefore, we asked which visual features might be represented at this high-order integration level. Using extracellular, multi-unit recordings in combination with visual and olfactory stimulation, we separated MBONs with multisensory responses from purely visually driven MBONs. Further analysis revealed, for the first time, that visually driven MBONs of both groups encode detailed aspects within this individual modality, such as light intensity and light identity. Moreover, we show that these features are separated by different MBON subpopulations, for example by extracting information about brightness and wavelength. Most interestingly, the latter MBON population was tuned to separate UV-light from other light stimuli, which were only poorly differentiated from each other. A third MBON subpopulation was neither tuned to brightness nor to wavelength and encoded the general presence of light. Taken together, our results support the view that the mushroom body, a high-order sensory integration, learning and memory center in the insect brain, categorizes sensory information by separating different behaviorally relevant aspects of the multisensory scenery and that these categories are channeled into distinct MBON subpopulations.

Project description:In the insect brain, the mushroom body is a higher order brain area that is key to memory formation and sensory processing. Mushroom body (MB) extrinsic neurons leaving the output region of the MB, the lobes and the peduncle, are thought to be especially important in these processes. In the honeybee brain, a distinct class of MB extrinsic neurons, A3 neurons, are implicated in playing a role in learning. Their MB arborisations are either restricted to the lobes and the peduncle, here called A3 lobe connecting neurons, or they provide feedback information from the lobes to the input region of the MB, the calyces, here called A3 feedback neurons. In this study, we analyzed the morphology of individual A3 lobe connecting and feedback neurons using confocal imaging. A3 feedback neurons were previously assumed to innervate each lip compartment homogenously. We demonstrate here that A3 feedback neurons do not innervate whole subcompartments, but rather innervate zones of varying sizes in the MB lip, collar, and basal ring. We describe for the first time the anatomical details of A3 lobe connecting neurons and show that their connection pattern in the lobes resemble those of A3 feedback cells. Previous studies showed that A3 feedback neurons mostly connect zones of the vertical lobe that receive input from Kenyon cells of distinct calycal subcompartments with the corresponding subcompartments of the calyces. We can show that this also applies to the neck of the peduncle and the medial lobe, where both types of A3 neurons arborize only in corresponding zones in the calycal subcompartments. Some A3 lobe connecting neurons however connect multiple vertical lobe areas. Contrarily, in the medial lobe, the A3 neurons only innervate one division. We found evidence for both input and output areas in the vertical lobe. Thus, A3 neurons are more diverse than previously thought. The understanding of their detailed anatomy might enable us to derive circuit models for learning and memory and test physiological data.

Dataset Information

Multimodal integration and stimulus categorization in putative mushroom body output neurons of the honeybee.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets