Model for Olfactory Discrimination and Learning in<i>Limax</i>Procerebrum Incorporating Oscillatory Dynamics and Wave Propagation

Ermentrout, Bard; Wang, Jing W.; Flores, Jorge A.; Gelperin, Alan

doi:10.1152/jn.2001.85.4.1444

Cited by 37 publications

(30 citation statements)

References 72 publications

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“…Tables 1 and 2 show the details of LY-labeled neurons. As reported by Kimura et al (1998b) and Ermentrout et al (2001), a cluster of LY-labeled neurons was observed in one side of the PC lobe. Several LY-labeled neurons were observed in the PC lobe contralateral to the PC lobe classified as "labeled" and in the PC lobes classified as "unlabeled," though in these cases the LY-labeled neurons did not form a cluster (Table 1).…”

Section: Ly Uptakesupporting

confidence: 82%

“…The application of learned odors changes the frequency of the LFP oscillation (Kimura et al 1998a;Inoue et al 2006). In addition, when a fluorescent dye, Lucifer Yellow (LY), is injected into the body cavity after odor learning, some of the PC interneurons incorporate the dye (Kimura et al 1998b;Gelperin 1999;Ermentrout et al 2001). Since the incorporation of LY depends on conditioning treatment and the duration between conditioning and LY injection (Kimura et al 1998b), LY-labeled neurons are related to the formation of memory of learned odors.…”

mentioning

confidence: 99%

“…Since the incorporation of LY depends on conditioning treatment and the duration between conditioning and LY injection (Kimura et al 1998b), LY-labeled neurons are related to the formation of memory of learned odors. Although several computational models have been proposed to describe the behaviors of PC oscillation including learning-dependent LY labeling Ermentrout et al 1998Ermentrout et al , 2001Ermentrout et al , 2004, no model deals with odor-taste association.In this study, the relationships between conditioning strategies (appetitive or aversive) and LY labeling were investigated. Then, a simple model based on nonlinear oscillators was constructed to account for the results of the present and previous studies.…”

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confidence: 99%

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Internal representation and memory formation of odor preference based on oscillatory activities in a terrestrial slug

Sekiguchi¹,

Furudate²,

Kimura³

2010

Learn. Mem.

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The terrestrial slug Limax exhibits a highly developed ability to learn odors with a small nervous system. When a fluorescent dye, Lucifer Yellow (LY), is injected into the slug's body cavity after odor -taste associative conditioning, a group of neurons in the procerebral (PC) lobe, an olfactory center of the slug, is labeled by LY. We examined the relationships between conditioning strategies and LY labeling. The positions of LY-labeled neurons in the PC lobe after appetitive conditioning were more apical than those after aversive conditioning and did not depend on the conditioned odor, suggesting that the biological value of odors affected the position of LY-labeled neural clusters. A simple computational model consisting of two layers of oscillators with electrical synaptic interaction was constructed based on physiological features of the PC lobe, and showed that the oscillatory phase difference between the layers contributed to determination of the positions of LY-labeled neurons, suggesting that phase difference in oscillatory activity plays a role in the association of odors and the preference for them. (Wehr and Laurent 1996); and (6) they play roles in the mechanisms of fine odor discrimination (Stopfer et al. 1997;Teyke and Gelperin 1999).For terrestrial slugs, olfactory information is the most important means of recognizing the external world, and slugs exhibit various types of odor learning (Sahley et al. 1981(Sahley et al. , 1990Hopfield and Gelperin 1989;Suzuki et al. 1994). Slugs have two pairs of tentacles that sense odors via olfactory receptors at their tips. Odor information is transferred to the procerebral (PC) lobe, which is the lateral part of the cerebral ganglion and is specialized for olfactory information processing in terrestrial slugs and snails (Ratte and Chase 1997;Chase 2000;Zaitseva 2000). On the surface of the PC lobe, large numbers of cell bodies of interneurons are arranged and elongate their neuropils toward the inside of the PC lobe, where afferent fibers from the tentacles are projected (Kawahara et al. 1997). The PC exhibits oscillation of local field potentials (LFP) at 0.7 Hz (Gelperin and Tank 1990). It is thus suitable for study of the contribution of oscillation to information processing in a nervous system that features learning, and has been studied extensively (for reviews, see Gelperin 1999Gelperin , 2006Watanabe et al. 2008). For example, LFP oscillation is synchronized over the entire PC lobe, with wave propagation from apical to basal parts (Delany et al. 1994;Kawahara et al. 1997;Kimura et al. 1998c). The application of learned odors changes the frequency of the LFP oscillation (Kimura et al. 1998a;Inoue et al. 2006). In addition, when a fluorescent dye, Lucifer Yellow (LY), is injected into the body cavity after odor learning, some of the PC interneurons incorporate the dye (Kimura et al. 1998b;Gelperin 1999;Ermentrout et al. 2001). Since the incorporation of LY depends on conditioning treatment and the duration between conditioning and LY injection (Kimura...

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Section: Ly Uptakesupporting

confidence: 82%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Internal representation and memory formation of odor preference based on oscillatory activities in a terrestrial slug

Sekiguchi¹,

Furudate²,

Kimura³

2010

Learn. Mem.

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“…Several attempts have been made to understand odor discrimination in models of the olfactory system [17,51,13,26,9,3,32,19]. The model discussed here is, however, fundamentally different in providing a classification scheme that solely relies on the fan-in, fan-out properties of synaptic connections, the known locus of learning in the MB and otherwise entirely non-specific connectivity.…”

Section: Discussionmentioning

confidence: 99%

Self-organization in the olfactory system: one shot odor recognition in insects

Nowotny¹,

Huerta²,

Abarbanel

et al. 2005

Biol Cybern

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Mikhail I (2005) Selforganization in the olfactory system: one shot odor recognition in insects. Biological Cybernetics, 93 (6). pp. 436-446. ISSN 1432-0770 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/1552/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. The date of receipt and acceptance will be inserted by the editorAbstract We show in a model of spiking neurons that synaptic plasticity in the mushroom bodies in combination with the general fan-in, fan-out properties of the early processing layers of the olfactory system might be sufficient to account for its efficient recognition of odors.For a large variety of initial conditions the model system consistently finds a working solution without any finetuning, and is, therefore, inherently robust. We demonstrate that gain control through the known feedforward inhibition of lateral horn interneurons increases the capacity of the system but is not essential for its general function. We also predict an upper limit for the number of odor classes Drosophila can discriminate based on the number and connectivity of its olfactory neurons.

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“…In fact, the PC exhibits a learned odor-specific change in the oscillatory frequency or amplitude of the spontaneous local field potential oscillation (Kimura et al, 1998a;Nikitin and Balaban, 2000;Inoue et al, 2006), and incorporation of Lucifer yellow dye into PC neurons specifically following odor-associative memory formation (Kimura et al, 1998b;Ermentrout et al, 2001;Sekiguchi et al, 2010). Future studies may reveal such discernible changes triggered in the TG by olfactory learning.…”

Section: Discussionmentioning

confidence: 99%

Olfactory Memory Storage and/or Retrieval Requires the Presence of the Exact Tentacle Used During Memory Acquisition in the Terrestrial SlugLimax

Koga

Matsuo

2016

Zoological Science

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Model for Olfactory Discrimination and Learning inLimaxProcerebrum Incorporating Oscillatory Dynamics and Wave Propagation

Cited by 37 publications

References 72 publications

Internal representation and memory formation of odor preference based on oscillatory activities in a terrestrial slug

Internal representation and memory formation of odor preference based on oscillatory activities in a terrestrial slug

Self-organization in the olfactory system: one shot odor recognition in insects

Olfactory Memory Storage and/or Retrieval Requires the Presence of the Exact Tentacle Used During Memory Acquisition in the Terrestrial SlugLimax

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