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Microsc Res Tech. 1994 Dec 1;29(5):329-43.

Construction and analysis of a database representing a neural map.

Author information

1
Department of Mathematics, University of California, Berkeley 94720.

Abstract

We describe the development and analysis of a quantitative database representing the global structural and functional organization of an entire sensory map. The database was derived from measurements of anatomical characteristics of a statistical sample of typical mechanosensory afferents in the cricket cercal sensory system. Anatomical characteristics of the neurons were measured quantitatively in three dimensions using a computer reconstruction system. The reconstructions of all neurons were aligned and scaled to a common standard set of dimensions, according to a highly reproducible set of intrinsic fiducial marks. The database therefore preserves accurate information about spatial relationships between the neurons within the ensemble. Algorithms were implemented to allow the integration of electrophysiological data about the stimulus/response characteristics of the reconstructed neurons into the database. The algorithms essentially map a physiological function onto a "field" representing the continuous distribution of synaptic terminals throughout the neural structure. Subsequent analysis allowed quantitative predictions of several important functional characteristics of the sensory map that emerge from its global organization. First, quantitative and testable predictions were made about ensemble response patterns within the map. The predicted patterns are presented as graphical images, similar to images that might be observed with activity-dependent dyes in the real neural system. Second, the synaptic innervation patterns from the sensory afferent map onto the dendrites of a postsynaptic target interneuron were predicted by calculating the overlap between the interneuron's dendrites with the afferent map. By doing so, several aspects of the stimulus/response properties of the interneuron were accurately predicted.

PMID:
7858313
DOI:
10.1002/jemt.1070290502
[Indexed for MEDLINE]

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