Literature DB >> 7373356

Distributed processing by visual interneurons of crayfish brain. II. Network organization and stimulus modulation of synaptic efficacy.

H L Wood, R M Glantz.   

Abstract

1. Multiple interactions were examined between five or six visual neurons simultaneously monitored in the circumesophageal connective. 2. A single neuron can make divergent connections to at least five other visual interneurons. 3. Conversely, a single cell may receive convergent inputs from up to four visual interneurons. 4. The convergent interactions are sufficiently intense so that 80--90% of a postsynaptic cell's visual activity can be attributed to observed network interactions. 5. Connectivity diagrams suggest that the descending interneurons, which arise in the visual neuropil of the brain, are organized into three interconnected layers: a) neurons that receive input from the optic nerve and project to other visual interneurons, b) neurons that both receive input and project to other descending interneurons in the brain--these cells exhibit a preponderance of reciprocal interactions, c) neurons that receive input from both the first and second network layers and project exclusively to the more caudal ganglia of the ventral nerve cord. 6. The network is systematically organized with respect to visual and nonvisual responsiveness. The cells of the first layer exhibit the strongest visual responses. The cells of the third layer exhibit spontaneous activity and the strongest tactile and/or proprioceptive responses. 7. The intensity of the network interactions is under stimulus control. The synaptic efficacy of a presynaptic spike can vary by over 100-fold as a consequence of stimulus presentation and/or location. The expressed organization of the network thus exhibits a dynamic, stimulus-dependent, plasticity. 8. The results indicate that the descending visual interneurons of the brain rather than forming a parallel tract actually constitute a complex distributed network. Furthermore, the results indicate the feasibility of population neural coding based on stimulus-dependent inpulse coordination in an array of neurons.

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Year:  1980        PMID: 7373356     DOI: 10.1152/jn.1980.43.3.741

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


  4 in total

1.  Binocular Neuronal Processing of Object Motion in an Arthropod.

Authors:  Florencia Scarano; Julieta Sztarker; Violeta Medan; Martín Berón de Astrada; Daniel Tomsic
Journal:  J Neurosci       Date:  2018-07-16       Impact factor: 6.167

2.  Morphological and physiological characterization of individual olfactory interneurons connecting the brain and eyestalk ganglia of the crayfish.

Authors:  C D Derby; D N Blaustein
Journal:  J Comp Physiol A       Date:  1988-10       Impact factor: 1.836

3.  Colour representation of biomedical data.

Authors:  J P de Valk; W J Epping; A Heringa
Journal:  Med Biol Eng Comput       Date:  1985-07       Impact factor: 2.602

4.  Stimulus dependent neural correlation: an example from the cochlear nucleus.

Authors:  H F Voigt; E D Young
Journal:  Exp Brain Res       Date:  1985       Impact factor: 1.972

  4 in total

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