Pattern Recognition in the Olfactory System of the Locust: Priming, Gain Control and Coding Issues

learning;neurobiology;neuroscience;sensitization;Biology, and Computational and Neural Systems

Backer, Alejandro (Alex) ; Laurent, Gilles J.

University:California Institute of Technology

Department:Biology

关键词: learning;    neurobiology;    neuroscience;    sensitization;    Biology, and Computational and Neural Systems;   

Others  :  https://thesis.library.caltech.edu/4610/2/Thesis.pdf

美国|英语

来源: Caltech THESIS

【 摘 要 】

Object recognition requires both specificity, to ensure that stimuli with distinct behavioral relevanceare distinguished, and invariance, to ensure that different instances of the same stimulusare recognized as the same under varied conditions (intensity, pitch, position,...). Psychophysicalstudies show that an odor can be perceived as identical over significant ranges of concentrations.Whether concentration invariance results, at least in part, from low-level neural phenomena ratherthan cognitive grouping is so far unknown.

I explore, firstly, the contribution of projection neurons (PNs) in the antennal lobe of thelocust, the analog of the vertebrate olfactory bulb, to the recognition of odor identity across concentrations;and secondly, what role spike timing, neuronal identity, and synchronization among neuronalassemblies play in the encoding and decoding of odor information by downstream neurons.

I show the following:
A novel computerized odor delivery system capable of delivering binary mixtures in arbitrary ratios and with arbitrary timecourses selected in real-time.
The locust can recognize odors, and shows innate olfactory preferences.

PNs solve the task of encoding both odorant concentration and odorant identity, independentlyof concentration, in three ways. First, by multiplexing information in different response dimensionsusing a code that involves neuronal identity, spike timing (on a timescale slower thanpreviously believed) and synchronization across a neuronal assembly. Second, via a novel phenomenonof experience-dependent plasticity that contributes to PNs’ invariance to concentration andsensitizes PNs after exposure to an odor at high concentration, contrary to the adaptation exhibitedby receptors. Third, a phenomenon of gain control, whereby excitatory and inhibitory responses balanceout massive changes in receptor activity as a function of odorant concentration, maintains theoutput of PNs within a small dynamic range.

A further mechanism of gain control contributing to keep the activity of early olfactory circuitsrelatively constant across the wide dynamic range of odorant concentrations in the air is thephysical chemistry of odorant reception confers the olfactory system invariance to odorant volatility,a physical property that has hitherto been believed to play a fundamental role in an odorant’s effectiveness.

Response patterns sometimes exhibit stable representations over large composition rangesand then abrupt transitions as a function of concentration and mixture composition, suggesting thedifference between “same” and “different” odors may be delineated by sharp boundaries in odorspace.

Finally, how is the distributed code for odors in PN assemblies decoded? I show thatalthough synchronization among PN assemblies does not augment stimulus information in PN temporalresponses, it is necessary for the read-out of odor information by downstream neurons.In sum, early olfactory circuits appear to employ plasticity, gain control and temporal codingacross synchronizing neuronal assemblies to solve the odor recognition problem across multipleconcentrations.

Appendices show that the variability of PN responses is correlated across neurons, showhow to produce non-cyclic Winnerless Competition (WLC) and a learning rule that causes randomnetworks to self-organize into WLC, present an exact hypothesis test for binomial distributions,improvements to sliding-window cross-correlation and to the K-nearest neighbor classification algorithm,a combinatorial analysis of the connectivity between the locust antennal lobes and mushroombodies, a didactic exposition of Victor and Purpura’s spike cost-based metric and an experimentshowing heterogeneity along the length of the locust antenna.