ArticlePLoS computational biology2017
Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 29 citations in OpenAlex.
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- Chronic larval exposure to thiacloprid impairs honeybee antennal selectivity, learning and memory performances.Frontiers in physiology · 2023Article
- Honey bees respond to multimodal stimuli following the principle of inverse effectiveness.The Journal of experimental biology · 2022Article
- Bumblebees Use Sequential Scanning of Countable Items in Visual Patterns to Solve Numerosity Tasks.Integrative and comparative biology · 2020Article
- Ants resort to heuristics when facing relational-learning tasks they cannot solve.Proceedings. Biological sciences · 2020Article
- Bumblebees Learn a Relational Rule but Switch to a Win-Stay/Lose-Switch Heuristic After Extensive Training.Frontiers in behavioral neuroscience · 2020Article
- Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth.Journal of the Royal Society, Interface · 2019Article
- Honeybees foraging for numbers.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2019Review
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4 authors at 3 institutions in 3 countries.
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No grant is acknowledged in the PubMed record.
Abstract
The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons' outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life.
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