Odors in olfactory bulb are defined by a short discrete temporal sequence: recognition by brute-force conversion to a spatial pattern (chunking)

TL;DR

This paper proposes that odors are represented by short, discrete sequences of neural events in the olfactory bulb, which can be converted into spatial patterns for recognition by cortical networks, supported by computational simulations.

Contribution

It introduces a novel 'brute force' approach where temporal sequences are transformed into spatial patterns for odor recognition, supported by neural plausibility and simulations.

Findings

Sharp event onset is biased toward specific gamma phases.

Odor signatures are discrete sequences of neural activity.

Simulations demonstrate the feasibility of converting sequences into spatial patterns.

Abstract

Mitral cells, the principal neurons in the olfactory bulb, respond to odorants by firing bursts of action potentials called sharp events. A given cell produces a sharp event at a fixed phase during the sniff cycle in response to a given odor; different cells have different phases. The olfactory bulb response to an odor is thus a sequence of sharp events. Here, we show that sharp event onset is biased toward certain phases of the ongoing gamma frequency oscillation. Thus, the signature of an odor is a discrete sequence. The fact that this sequence is relatively short suggests a new class of "brute force" solutions to the problem of odor recognition: cortex may contain a small number of modules, each forming a persistent snapshot of what occurs in a certain gamma cycle. Towards the end of the sniff, the collection of these snapshots forms a spatial pattern that could be recognized by standard attractor-based network mechanisms. We demonstrate the feasibility of this solution with simulations of simple network architectures having modules that represent gamma-cycle specific information. Thus "brute force" solutions for converting a discrete temporal sequence into a spatial pattern (chunking) are neurally plausible.