Parallel Odor Processing by Two Anatomically Distinct Olfactory Bulb Target Structures

Abstract

The olfactory cortex encompasses several anatomically distinct regions each hypothesized to provide differential representation and processing of specific odors. Studies exploring whether or not the diversity of olfactory bulb input to olfactory cortices has functional meaning, however, are lacking. Here we tested whether two anatomically major olfactory cortical structures, the olfactory tubercle (OT) and piriform cortex (PCX), differ in their neural representation and processing dynamics of a small set of diverse odors by performing in vivo extracellular recordings from the OT and PCX of anesthetized mice. We found a wealth of similarities between structures, including odor-evoked response magnitudes, breadth of odor tuning, and odor-evoked firing latencies. In contrast, only few differences between structures were found, including spontaneous activity rates and odor signal-to-noise ratios. These results suggest that despite major anatomical differences in innervation by olfactory bulb mitral/tufted cells, the basic features of odor representation and processing, at least within this limited odor set, are similar within the OT and PCX. We predict that the olfactory code follows a distributed processing stream in transmitting behaviorally and perceptually-relevant information from low-level stations.

Encoding and Representation of Intranasal CO2in the Mouse Olfactory Cortex

“…In contrast, similar inter-regional differences were not found in response to odor ( Fig. 7; Payton et al, 2012). This striking, and significant difference in the recruitment of olfactory cortex neurons by CO 2 stimulation suggests major inter-regional differences in the processing of CO 2 .…”

“…CO 2 was presented in a manner allowing its use as mostly a trigeminal (nonolfactory) stimulant . Isopentyl acetate was selected due to its robust representation in both the PCX and OT (Payton et al, 2012). While this odorant is capable of eliciting trigeminal sensation at high concentrations (Doty et al, 1978(Doty et al, , 1995Porter et al, 2005), for our initial characterization of CO 2 -evoked responses, we specifically used low concentrations of odor (ϳ10 ppm; see Materials and Methods), allowing this to serve as a simple olfactory-evoked comparison.…”

“…Some examples, however, of delayed excitatory responses to odorants among PCX neurons are present (Rennaker et al, 2007) perhaps reflecting that at their respectfully strong concentrations used, these odorants possessed a trigeminal component (Doty et al, 1978). In contrast, here we used a considerably low concentration of a single odorant, isopentyl acetate, known at higher concentrations to recruit a large portion of OT and PCX neurons (Payton et al, 2012), though at the concentration used herein recruited considerably less units (albeit while sparing likely trigeminal responsivity, as suggested by a significantly reduced representation of odor vs CO 2 in both structures (Fig. 7).…”

“…Classically, odorant-evoked responses in the olfactory cortex occur upon the first inhalation of odorant (Fig. 3) (Schoenbaum and Eichenbaum, 1995;Wilson, 2000;Rennaker et al, 2007;Chapuis and Wilson, 2011;Payton et al, 2012;Rampin et al, 2012). Some examples, however, of delayed excitatory responses to odorants among PCX neurons are present (Rennaker et al, 2007) perhaps reflecting that at their respectfully strong concentrations used, these odorants possessed a trigeminal component (Doty et al, 1978).…”

“…These time epochs were selected after exploration of example traces to encompass both time periods in which we observed either odor-evoked (0 -2 s, during stimulus) or CO 2 -evoked activity (0 -2, or 2-4 s after stimulus). For some analyses we calculated signal:noise ratios (s:n) as the average stimulus-evoked spike magnitude divided by the SD of the spontaneous firing (Payton et al, 2012;Varga and Wesson, 2013). This calculation differs from the standard ratio of stimulus-evoked spikes to all spikes, and was used to reduce variability in data due to trial-by-trial variability.…”