Rapid odor classification by divergent networking along the olfactory path
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1
Max Planck Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Germany
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2
Arizona State University, School of Life Sciences, United States
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3
Arizona State University, Mathematical, Computational, and Modeling Sciences Center, United States
Using the insect brain (honey bee) as a model we here concentrated on the influence of divergent connections between two subsequent neuropiles along the olfactory path. Divergency along a neuronal path is thought to be necessary to increase the degree of separation between incoming stimuli. In the present study we show that it is rather the speed of separation which is increased due to divergent connections than the separation itself.
In the honey bee, several hundred Projection Neuron (PN) axons from the primary olfactory processing center, the Antennal Lobe (AL), diverge onto a few hundred thousand intrinsic Kenyon Cells (KCs) in the next layer of processing in the Mushroom Bodies (MB). After being processed into the MB the Information is converged to a few hundred Extrinsic Neurons (ENs). We recorded responses of PNs (N=111) and ENs (N=75) to two odors and their mixture. Inter alia we analyzed the response latencies of single units as well as the related population response latencies by calculating the Euclidean Distances between the different odor representations. Odor stimuli were equally well classified by each ensemble. Surprisingly, the EN ensemble started separating approximately 20 milliseconds earlier than the PN ensemble and reached maximum separation 60-120 ms earlier. Simultaneous recordings showed that a few PNs respond 10 to 70 ms before the ENs, and they probably initiate the EN ensemble response. We suggest that a function of projection of fewer (PN) dimensions onto higher (KC) dimensions in the MB is to facilitate rapid odor classification rather than the classification itself. Further processing by the AL network at a longer timescale may provide more detailed information necessary for implementing other qualities of odors or plasticity.
Acknowledgements
This research was funded by NIH NCRR RR014166 to BH Smith, and by a subcontract of NIH NIDCD (DC007997) to BH Smith.
Keywords:
extracellular recording,
Honey bee,
Insect brain,
multi unit recording,
Olfaction
Conference:
BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.
Presentation Type:
Poster
Topic:
neurons, networks and dynamical systems (please use "neurons, networks and dynamical systems" as keywords)
Citation:
Strube-Bloss
MF,
Herrera-Valdez
M and
Smith
B
(2011). Rapid odor classification by divergent networking along the olfactory path.
Front. Comput. Neurosci.
Conference Abstract:
BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011.
doi: 10.3389/conf.fncom.2011.53.00216
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Received:
15 Aug 2011;
Published Online:
04 Oct 2011.
*
Correspondence:
Dr. Martin F Strube-Bloss, Max Planck Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Jena, Germany, martin.strube-bloss@uni-bielefeld.de