A transformation from temporal to ensemble coding in a model of piriform cortex

Abstract

Different coding strategies are used to represent odor information at various stages of the mammalian olfactory system. A temporal latency code represents odor identity in olfactory bulb (OB), but this temporal information is discarded in piriform cortex (PCx) where odor identity is instead encoded through ensemble membership. We developed a spiking PCx network model to understand how this transformation is implemented. In the model, the impact of OB inputs activated earliest after inhalation is amplified within PCx by diffuse recurrent collateral excitation, which then recruits strong, sustained feedback inhibition that suppresses the impact of later-responding glomeruli. Simultaneous OB-PCx recordings indicate that indeed, over a single sniff, the earliest-active OB inputs are most effective at driving PCx activity. We model increasing odor concentrations by decreasing glomerulus onset latencies while preserving their activation sequences. This produces a multiplexed cortical odor code in which activated ensembles are robust to concentration changes while concentration information is encoded through population synchrony. Our model demonstrates how PCx circuitry can implement multiplexed ensemble-identity/temporal-concentration odor coding.

Mixture Coding and Segmentation in the Anterior Piriform Cortex

“…Normalization has been found in many cortical regions and has been proposed as a canonical computation performed by cortical circuits that allows them to encode variables monotonically without saturating (Carandini and Heeger, 2012). Our finding of mixture response normalization is in line with studies that demonstrated normalization of responses to increasing concentrations of odorants Franks, 2017, 2018;Stern et al, 2018). Several mechanisms may contribute to the sublinear summation of odorant responses.…”

“…Importantly, piriform cortex is also expected to contribute to sublinear summation of mixture components due to local inhibitory circuits. These circuits have been shown to normalize responses to increasing concentrations of odors (Bolding and Franks, 2018;Stern et al, 2018). Whether increasing stimulus intensity by increasing concentration or by adding more odorants produces equivalent normalization is unknown.…”

Complex neural representation of odour information in the olfactory bulb

“…However, direct evidence is needed in future studies which should combine the electrophysiological recording and optical calcium recordings of the axons projecting to the OB in behaving animals. Studying odour representation by monitoring multi‐site olfactory centres. While the OB is an important olfactory centre for odour representation, other olfactory centres are also involved . Monitoring the neural activity from multiple olfactory centres could provide important information on how the whole system represents odours.…”

Expectation-induced modulation of metastable activity underlies faster coding of sensory stimuli

“…Network models with clustered architecture provide a parsimonious explanation for the state sequences that have been observed ubiquitously in alert mammalian cortex, during both task engagement 17,18,46,47 and inter-trial periods. 11,39,40 In addition, this type of models accounts for various physiological observations such as stimulus-induced reduction of trial-to-trial variability 11,14,15,48 , neural dimensionality 16 , and firing rate multistability 11 (see also 49,50 ). In particular, models with metastable attractors have been used to explain the state sequences observed in rodent gustatory cortex during taste processing and decision making 11,45,51 .…”