MaBouDi HaDi, Shimazaki Hideaki, Giurfa Martin, Chittka Lars
School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.
RIKEN Brain Science Institute, Saitama, Japan.
PLoS Comput Biol. 2017 Jun 22;13(6):e1005551. doi: 10.1371/journal.pcbi.1005551. eCollection 2017 Jun.
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.
蜜蜂嗅觉系统是理解学习和记忆功能机制的一个成熟模型。嗅觉刺激首先在触角叶中进行处理，然后通过称为内侧和外侧触角叶束（m - ALT和l - ALT）的双路径传递到蘑菇体和侧角。最近的研究报告称，即使在m - ALT受损或蘑菇体被阻断后，蜜蜂仍能通过将气味与奖励信号关联来进行基本学习。为了验证外侧路径（l - ALT）足以进行基本学习的假设，我们用连接到侧角决策神经元（LHN）的投射神经元轴突对触角叶中的肾小球内局部计算进行建模。我们表明，从局部神经元到投射神经元的突触中的抑制性尖峰时间依赖性可塑性（通过暴露于不同刺激来模拟非联想可塑性）使投射神经元的输出去相关。去相关的强度由触角叶内对投射神经元的全局抑制性反馈调节。通过额外模拟触角叶中局部神经元之间突触可塑性的章鱼胺能修饰以及投射神经元与LHN连接，该模型可以区分和概括嗅觉刺激。虽然正向模式可以由l - ALT模型解释，但负向模式需要进一步处理和蘑菇体回路。因此，我们的模型通过l - ALT中气味处理的几个神经层解释了几种（但不是所有）类型的联想嗅觉学习和概括。作为非联想学习和联想学习相结合的结果，这种建模方法使我们能够将蜜蜂触角叶结构组织的变化与其一生中的行为表现联系起来。
