Literature DB >> 24004530

Local interneurons and projection neurons in the antennal lobe from a spiking point of view.

Anneke Meyer1, C Giovanni Galizia, Martin Paul Nawrot.   

Abstract

Local computation in microcircuits is an essential feature of distributed information processing in vertebrate and invertebrate brains. The insect antennal lobe represents a spatially confined local network that processes high-dimensional and redundant peripheral input to compute an efficient odor code. Social insects can rely on a particularly rich olfactory receptor repertoire, and they exhibit complex odor-guided behaviors. This corresponds with a high anatomical complexity of their antennal lobe network. In the honeybee, a large number of glomeruli that receive sensory input are interconnected by a dense network of local interneurons (LNs). Uniglomerular projection neurons (PNs) integrate sensory and recurrent local network input into an efficient spatio-temporal odor code. To investigate the specific computational roles of LNs and PNs, we measured several features of sub- and suprathreshold single-cell responses to in vivo odor stimulation. Using a semisupervised cluster analysis, we identified a combination of five characteristic features as sufficient to separate LNs and PNs from each other, independent of the applied odor-stimuli. The two clusters differed significantly in all these five features. PNs showed a higher spontaneous subthreshold activation, assumed higher peak response rates and a more regular spiking pattern. LNs reacted considerably faster to the onset of a stimulus, and their responses were more reliable across stimulus repetitions. We discuss possible mechanisms that can explain our results, and we interpret cell-type-specific characteristics with respect to their functional relevance.

Entities:  

Keywords:  Fano factor; cluster analysis; coefficient of variation; electrophysiology; honeybee; olfaction; response latency

Mesh:

Year:  2013        PMID: 24004530     DOI: 10.1152/jn.00260.2013

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  9 in total

1.  Comparative study of chemical neuroanatomy of the olfactory neuropil in mouse, honey bee, and human.

Authors:  Irina Sinakevitch; George R Bjorklund; Jason M Newbern; Richard C Gerkin; Brian H Smith
Journal:  Biol Cybern       Date:  2017-08-29       Impact factor: 2.086

2.  Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities.

Authors:  HaDi MaBouDi; Hideaki Shimazaki; Martin Giurfa; Lars Chittka
Journal:  PLoS Comput Biol       Date:  2017-06-22       Impact factor: 4.475

3.  Circuit and Cellular Mechanisms Facilitate the Transformation from Dense to Sparse Coding in the Insect Olfactory System.

Authors:  Rinaldo Betkiewicz; Benjamin Lindner; Martin P Nawrot
Journal:  eNeuro       Date:  2020-04-10

Review 4.  Olfactory coding in honeybees.

Authors:  Marco Paoli; Giovanni C Galizia
Journal:  Cell Tissue Res       Date:  2021-01-14       Impact factor: 5.249

5.  Novelty detection in early olfactory processing of the honey bee, Apis mellifera.

Authors:  Hong Lei; Seth Haney; Christopher M Jernigan; Xiaojiao Guo; Chelsea N Cook; Maxim Bazhenov; Brian H Smith
Journal:  PLoS One       Date:  2022-03-30       Impact factor: 3.240

6.  Early olfactory, but not gustatory processing, is affected by the selection of heritable cognitive phenotypes in honey bee.

Authors:  Meghan M Bennett; Chelsea N Cook; Brian H Smith; Hong Lei
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2020-11-17       Impact factor: 1.836

7.  Olfactory coding in the antennal lobe of the bumble bee Bombus terrestris.

Authors:  Marcel Mertes; Julie Carcaud; Jean-Christophe Sandoz
Journal:  Sci Rep       Date:  2021-05-26       Impact factor: 4.379

8.  Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe.

Authors:  Eli Shlizerman; Jeffrey A Riffell; J Nathan Kutz
Journal:  Front Comput Neurosci       Date:  2014-08-13       Impact factor: 2.380

Review 9.  Olfactory coding in the insect brain: data and conjectures.

Authors:  C Giovanni Galizia
Journal:  Eur J Neurosci       Date:  2014-04-03       Impact factor: 3.386

  9 in total

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