Multiple network properties overcome random connectivity to enable stereotypic sensory responses

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity

Using an insect mushroom body circuit to encode route memory in complex natural environments

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images

Integration of the olfactory code across dendritic claws of single mushroom body neurons

In the olfactory system, sensory inputs are arranged in different glomerular channels, which respond in combinatorial ensembles to the various chemical features of an odor. We investigated where and how this combinatorial code is read out deeper in the brain. We exploited the unique morphology of neurons in the Drosophila mushroom body, which receive input on large dendritic claws. Imaging odor responses of these dendritic claws revealed that input channels with distinct odor tuning converge on individual mushroom body neurons. We determined how these inputs interact to drive the cell to spike threshold using intracellular recordings to examine mushroom body responses to optogenetically controlled input. Our results provide an elegant explanation for the characteristic selectivity of mushroom body neurons: these cells receive different types of input and require those inputs to be coactive to spike. These results establish the mushroom body as an important site of integration in the fly olfactory system