We show that the main determinant of discrimination is the distance between ePN activity patterns. Experimental manipulations of this distance have graded and predictable behavioral consequences. iPN inhibition enhances the contrast between closely related odors by imposing a high-pass filter on ePN synapses in the LH that stretches the distances between overlapping odor representations. We considered rate code representations of odors in the ∼50 glomerular channels that constitute the front end of the fly olfactory system. Odors were denoted by vectors of ∼50 components, which indicated the mean spike frequencies in each glomerular channel.

Choosing experimental odors with characterized Vorinostat supplier ORN response spectra (Hallem and Carlson, 2006 and Hallem et al., 2004) allowed us to assign numerical values to check details 24 of these ∼50 components. We termed these 24 components the ORN activity vector (Figure 1A). The corresponding ePN activity vectors were calculated by applying a saturating transformation to each ORN activity vector component plus an inhibitory scaling factor (m) that reflects the activation of GABAergic antennal lobe interneurons

and alters the slope of the transformation as a function of total ORN activity ( Olsen et al., 2010) ( Figure 1A). Different glomeruli vary somewhat in their sensitivity to inhibition, but our calculations of ePN firing rates assumed a uniform scaling factor of m = 10.63 ( Luo et al., 2010 and Olsen et al., 2010). Varying m in the physiologically plausible range of 5 to 15 ( Luo et al., 2010 and Olsen et al., 2010) had little impact on our conclusions ( Figure S1 available online). Because glomerular connectivity between ORNs and ePNs is 1:1

( Jefferis et al., 2001 and Stocker et al., 1990), ePN activity vectors also have ∼50 components, one for the average spike frequency of each class of ePN. We could assign numerical values to 24 of these components by selecting odors with known ORN response spectra ( Figure 1A). ePN activity vectors were used to define two types of pairwise distance between odor representations (Kreher et al., 2008). The Euclidean distance is the length of the line segment 4-Aminobutyrate aminotransferase connecting the tips of two activity vectors in 24-dimensional space, reflecting the distribution of firing rates across the ePN population. Cosine distance measures the angle between two activity vectors. Large cosine distances indicate that the vectors are nearly orthogonal (suggesting little overlap of the corresponding neural activity patterns), whereas small distances indicate that the vectors are nearly parallel, and the activity patterns are similar in structure but not necessarily in magnitude. The main difference between the two metrics is that Euclidean distance is sensitive to scale (i.e.