What the fly's nose tells the fly's brain

Abstract

The fly olfactory system has a three-layer architecture: The fly's olfactory receptor neurons send odor information to the first layer (the encoder) where this information is formatted as combinatorial odor code, one which is maximally informative, with the most informative neurons firing fastest. This first layer then sends the encoded odor information to the second layer (decoder), which consists of about 2,000 neurons that receive the odor information and "break" the code. For each odor, the amplitude of the synaptic odor input to the 2,000 second-layer neurons is approximately normally distributed across the population, which means that only a very small fraction of neurons receive a large input. Each odor, however, activates its own population of large-input neurons and so a small subset of the 2,000 neurons serves as a unique tag for the odor. Strong inhibition prevents most of the second-stage neurons from firing spikes, and therefore spikes from only the small population of large-input neurons is relayed to the third stage. This selected population provides the third stage (the user) with an odor label that can be used to direct behavior based on what odor is present.

Keywords: Marr motif; fly brain; olfaction; theory.

Fig. 1.

Schematic representation of the Marr motif. Four sensory neurons at the left (circles represent their cell bodies) send their axons to two regions of neuropil (dotted circles) in the first (encoder) stage of the three-stage circuit. Additional circuitry (not illustrated) produces interactions between the two neuropil regions. Dendrites of the two stage 1 projection neurons (cell bodies of precerebellar neurons are the circles) collect and format the sensory information as a combinatorial code. This coded information is then sent over the precerebellar neuron axons to stage 2 (decoder). Synaptic connections (dark dots) are made on the dendrites of four stage 2 neurons (granule cell bodies represented by four circles), and the output, the broken code, is sent at the right of the diagram to stage 3 (not represented). Additional circuitry responsible for breaking the combinatorial code in the second stage is not shown.

Fig. 2.

Observed probability distribution for fraction of neurons (ordinate) with projection neuron firing rates greater than or equal to the value given on the abscissa (spikes per second). Data from ref. . An exponential probability distribution with an average rate of 162 spikes per second is superimposed on the observed distribution.

Fig. 3.

Probability distributions for Kenyon cell claw number and its effect on the depolarization of Kenyon cells by projection neurons. (A) Graphs for cumulative probability of claw number (non-γ Kenyon cell Left, γ type Right). The smooth curves are binomial distributions. (B) Calculated probability distribution for depolarization of Kenyon cells by antennal lobe input (solid curve), a normal probability distribution (light dotted). The heavy dotted curves to the left of the solid curve is the distribution for non-γ Kenyon cells (Left), and for γ Kenyon cells (Right).

Fig. S1.

Relative frequency of a KC sampling a glomerulus vs. glomerulus number. Non-γ KCs in A and γ KCs in B. Data from Carron et al. (16), Fig. S2. Smooth lines according to a distribution (see Nonuniform Sampling of Glomeruli by KCs).

Fig. S2.

Properties of the antennal lobe projection neuron synapses onto KCs. (A) The cumulative distribution function for synaptic strength at 16 single claw synapses [the mean amplitude (mV) for the first EPSP]. The fitted straight line has a slope of 0.85 (B). Cumulative histogram for all EPSP amplitudes (235 observations) scaled for each claw to have a mean = 1. This histogram has been fitted to a Γ distribution function with scale factor = 4 and shape factor = 4.