Literature DB >> 10454377

Spatiotemporal structure of olfactory inputs to the mushroom bodies.

G Laurent1, K MacLeod, M Stopfer, M Wehr.   

Abstract

A requirement to understand mushroom body (MB) function is to characterize the operations (or transformations) that they impose on incoming signals. Understanding the nature of these integrative operations requires an understanding of the inputs from other brain areas. By inputs we mean not only the anatomical pathways leading to the MBs, but also the dynamic structure of the inflow of sensory (and other) signals. Neurons are complex, capacitative, and generally nonlinear devices that transform barrages of neurochemical packets into electrical waveforms. Their modes of operation are intrinsically time dependent and therefore, their functions or roles in a circuit cannot be inferred only from structural data. Thanks to elegant anatomical, behavioral, genetic, and molecular (for review, see Crittenden et al. 1998; Hammer and Menzel 1998; Heisenberg 1998; Wolf et al. 1998) studies, there is convincing evidence that MB circuits are involved, at least in fruit flies and honeybees, in some forms of odor integration and learning. In vivo electrophysiological studies of MB neurons, however, are rare and mainly restricted to individual (or small populations of) so-called extrinsic neurons, that is, those whose processes link MBs with other brain areas (Schildberger 1983, 1984; Homberg 1984; Hammer 1993; Mauelshagen 1993; Li and Strausfeld 1997). Kaulen et al. (1984) examined extracellular potentials in the MBs of bees, using current source density analysis, and more recently, Laurent and Naraghi (1994) provided a description of stimulus-evoked activity in Kenyon cells (KCs), the intrinsic neurons of the MBs, using intracellular recordings. In this short review we will summarize the recent results from our laboratory in an attempt to provide a description of the spatiotemporal structure of olfactory inputs to the MBs and their intrinsic neurons. We will focus only on the encoding of odor quality. We will then speculate on the possible role of MB circuits for olfactory processing.

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Year:  1998        PMID: 10454377      PMCID: PMC311249     

Source DB:  PubMed          Journal:  Learn Mem        ISSN: 1072-0502            Impact factor:   2.460


  42 in total

1.  Multiple sites of associative odor learning as revealed by local brain microinjections of octopamine in honeybees.

Authors:  M Hammer; R Menzel
Journal:  Learn Mem       Date:  1998 May-Jun       Impact factor: 2.460

2.  Simulations of cortical pyramidal neurons synchronized by inhibitory interneurons.

Authors:  W W Lytton; T J Sejnowski
Journal:  J Neurophysiol       Date:  1991-09       Impact factor: 2.714

3.  Vector reconstruction from firing rates.

Authors:  E Salinas; L F Abbott
Journal:  J Comput Neurosci       Date:  1994-06       Impact factor: 1.621

Review 4.  Synchronous oscillations in neuronal systems: mechanisms and functions.

Authors:  C M Gray
Journal:  J Comput Neurosci       Date:  1994-06       Impact factor: 1.621

5.  Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model.

Authors:  X J Wang; G Buzsáki
Journal:  J Neurosci       Date:  1996-10-15       Impact factor: 6.167

6.  A mechanism for generation of long-range synchronous fast oscillations in the cortex.

Authors:  R D Traub; M A Whittington; I M Stanford; J G Jefferys
Journal:  Nature       Date:  1996-10-17       Impact factor: 49.962

7.  Distinct mechanisms for synchronization and temporal patterning of odor-encoding neural assemblies.

Authors:  K MacLeod; G Laurent
Journal:  Science       Date:  1996-11-08       Impact factor: 47.728

8.  Odour encoding by temporal sequences of firing in oscillating neural assemblies.

Authors:  M Wehr; G Laurent
Journal:  Nature       Date:  1996-11-14       Impact factor: 49.962

Review 9.  Making waves in the neocortex.

Authors:  B W Connors; Y Amitai
Journal:  Neuron       Date:  1997-03       Impact factor: 17.173

10.  Local interneurons and information processing in the olfactory glomeruli of the moth Manduca sexta.

Authors:  T A Christensen; B R Waldrop; I D Harrow; J G Hildebrand
Journal:  J Comp Physiol A       Date:  1993-10       Impact factor: 1.836

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  8 in total

Review 1.  What do the mushroom bodies do for the insect brain? an introduction.

Authors:  M Heisenberg
Journal:  Learn Mem       Date:  1998 May-Jun       Impact factor: 2.460

2.  Decoding temporal information through slow lateral excitation in the olfactory system of insects.

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Journal:  J Comput Neurosci       Date:  2003 Sep-Oct       Impact factor: 1.621

3.  Olfactory modulation by dopamine in the context of aversive learning.

Authors:  Andrew M Dacks; Jeffrey A Riffell; Joshua P Martin; Stephanie L Gage; Alan J Nighorn
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4.  Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee.

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Journal:  Front Neuroeng       Date:  2011-12-28

5.  Brain composition in Godyris zavaleta, a diurnal butterfly, Reflects an increased reliance on olfactory information.

Authors:  Stephen H Montgomery; Swidbert R Ott
Journal:  J Comp Neurol       Date:  2014-12-30       Impact factor: 3.215

6.  Choline Transporter regulates olfactory habituation via a neuronal triad of excitatory, inhibitory and mushroom body neurons.

Authors:  Runa Hamid; Hitesh Sonaram Sant; Mrunal Nagaraj Kulkarni
Journal:  PLoS Genet       Date:  2021-12-16       Impact factor: 5.917

7.  Coding of odors by temporal binding within a model network of the locust antennal lobe.

Authors:  Mainak J Patel; Aaditya V Rangan; David Cai
Journal:  Front Comput Neurosci       Date:  2013-04-25       Impact factor: 2.380

8.  Modelling Odor Decoding in the Antennal Lobe by Combining Sequential Firing Rate Models with Bayesian Inference.

Authors:  Dario Cuevas Rivera; Sebastian Bitzer; Stefan J Kiebel
Journal:  PLoS Comput Biol       Date:  2015-10-09       Impact factor: 4.475

  8 in total

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