Literature DB >> 2795148

Hundreds of neurons in the Aplysia abdominal ganglion are active during the gill-withdrawal reflex.

D Zecević1, J Y Wu, L B Cohen, J A London, H P Höpp, C X Falk.   

Abstract

A combination of optical and electrode recording methods was used to obtain an overview of the neuron activity in the Aplysia abdominal ganglion in response to a light touch to the siphon skin. Spike activity was detected in up to 150 different neurons. Habituation and sensitization of the gill-withdrawal reflex was accompanied by large changes in the number of activated neurons. It is likely that these recordings are incomplete; the actual number of activated neurons is estimated to be about 300 in the acutely sensitized preparation. While we presume that not all 300 of these neurons are involved in the gill-withdrawal reflex, the number of neurons is so large that it may be difficult to determine the role of each activated neuron with presently available experimental tools.

Mesh:

Year:  1989        PMID: 2795148      PMCID: PMC6569909     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  22 in total

1.  Distributed and partially separate pools of neurons are correlated with two different components of the gill-withdrawal reflex in Aplysia.

Authors:  M Zochowski; L B Cohen; G Fuhrmann; D Kleinfeld
Journal:  J Neurosci       Date:  2000-11-15       Impact factor: 6.167

Review 2.  Neuronal network analyses: premises, promises and uncertainties.

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Journal:  Cell Mol Neurobiol       Date:  2005-03       Impact factor: 5.046

4.  A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity.

Authors:  William N Frost; Jean Wang; Christopher J Brandon
Journal:  J Neurosci Methods       Date:  2007-01-13       Impact factor: 2.390

5.  Random insertion of split-cans of the fluorescent protein venus into Shaker channels yields voltage sensitive probes with improved membrane localization in mammalian cells.

Authors:  Lei Jin; Bradley Baker; Robbie Mealer; Lawrence Cohen; Vincent Pieribone; Arnd Pralle; Thomas Hughes
Journal:  J Neurosci Methods       Date:  2011-04-08       Impact factor: 2.390

Review 6.  Complexities and uncertainties of neuronal network function.

Authors:  David Parker
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-01-29       Impact factor: 6.237

7.  Distributed processing on the basis of parallel and antagonistic pathways simulation of the femur-tibia control system in the stick insect.

Authors:  A E Sauer; R B Driesang; A Büschges; U Bässler
Journal:  J Comput Neurosci       Date:  1996-09       Impact factor: 1.621

8.  Regeneration of a central synapse restores nonassociative learning.

Authors:  B K Modney; C L Sahley; K J Muller
Journal:  J Neurosci       Date:  1997-08-15       Impact factor: 6.167

Review 9.  Imaging with organic indicators and high-speed charge-coupled device cameras in neurons: some applications where these classic techniques have advantages.

Authors:  William N Ross; Kenichi Miyazaki; Marko A Popovic; Dejan Zecevic
Journal:  Neurophotonics       Date:  2014-12-22       Impact factor: 3.593

10.  Photon shot noise limits on optical detection of neuronal spikes and estimation of spike timing.

Authors:  Brian A Wilt; James E Fitzgerald; Mark J Schnitzer
Journal:  Biophys J       Date:  2013-01-08       Impact factor: 4.033

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