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Pattern conserving data structure and algorithms for computations on dendritic trees.

W P Ireland1

  • 1Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Canada.

Computers and Biomedical Research, an International Journal
|February 1, 1989
PubMed
Summary
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A linked list data structure efficiently stores neuronal dendritic trees. Algorithms are presented for building lists, graphing trees, and ordering trees, with stacks as an alternative.

Area of Science:

  • Neuroscience
  • Computer Science
  • Data Structures

Background:

  • Neuronal dendritic trees are complex structures requiring efficient data storage.
  • Traditional methods may not adequately represent the intricate branching patterns of dendrites.

Purpose of the Study:

  • To introduce a pattern-conserving data structure for neuronal dendritic trees.
  • To describe algorithms for manipulating and analyzing these structures.

Main Methods:

  • Implementation of a linked list data structure in BASIC language.
  • Development of algorithms for linked list construction.
  • Adaptation of algorithms for graphing dendritic trees and tarry ordering.

Main Results:

Related Experiment Videos

  • A functional linked list algorithm for representing neuronal dendritic trees.
  • Demonstrated modifications for graphing and ordering tree structures.
  • Consideration of the last-in-first-out stack as an alternative data structure.

    • Conclusions:

    • Linked lists provide an effective data structure for neuronal dendritic trees.
    • The presented algorithms offer versatile tools for computational neuroscience.
    • Further exploration of alternative data structures like stacks is warranted.