Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance

Mohammad Ziyad Kagdi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Dendrites, the most conspicuous elements of neurons, extensively determine a cell’s capacity to recognise synaptic inputs. Investigating its structure and morphological properties unravels the functioning mechanism of neurons that cooperates the process of learning and memory. This research systematically generates a varying topology of dendrites in a multi-compartmental model of a neuron with passive properties and it further explores a cell’s integration ability of complex synaptic potentials. The neurons receive an equal number of binary input patterns of synaptic activity and the performance of a cell is gauged by calculating the signal to noise ratio between amplitudes of somatic voltage. The objective is to analyse the types of input pattern in combination with morphological properties that may strengthen or weaken the somatic response. Finally, an evolutionary algorithm produces a fine variety of branching structures calculating the weighted sum of synaptic inputs, further identifying the impact of membrane and morphological properties on neuronal performance.
Original languageEnglish
Title of host publicationComputational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016
EditorsAndrea Bracciali, Giulio Caravagna, David Gilbert, Roberto Tagliaferri
PublisherSpringer
Pages220-234
Number of pages15
ISBN (Electronic)9783319678344
ISBN (Print)9783319678337
DOIs
Publication statusPublished - 17 Oct 2017
EventCIBB 2016: Computational Intelligence Methods for Bioinformatics and Biostatistics - University of Stirling, Stirling, United Kingdom
Duration: 1 Sep 20163 Sep 2016
Conference number: 13
http://www.cs.stir.ac.uk/events/cibb2016/

Publication series

NameLecture Notes in Computer Science (LNCS)
PublisherSpringer
Volume10477
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceCIBB 2016
CountryUnited Kingdom
CityStirling
Period1/09/163/09/16
Internet address

Fingerprint

Neurons
Dendrites
Synaptic Potentials
Aptitude
Signal-To-Noise Ratio
Learning
Membranes
Research

Keywords

  • Dendritic morphology
  • Synaptic integration
  • Synaptic plasticity
  • Hebbian learning
  • Pattern recognition
  • Evolutionary algorithm

Cite this

Kagdi, M. Z. (2017). Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance. In A. Bracciali, G. Caravagna, D. Gilbert, & R. Tagliaferri (Eds.), Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016 (pp. 220-234). (Lecture Notes in Computer Science (LNCS); Vol. 10477). Springer . https://doi.org/10.1007/978-3-319-67834-4_18

Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance. / Kagdi, Mohammad Ziyad.

Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. ed. / Andrea Bracciali; Giulio Caravagna; David Gilbert; Roberto Tagliaferri. Springer , 2017. p. 220-234 (Lecture Notes in Computer Science (LNCS); Vol. 10477).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kagdi, MZ 2017, Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance. in A Bracciali, G Caravagna, D Gilbert & R Tagliaferri (eds), Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science (LNCS), vol. 10477, Springer , pp. 220-234, CIBB 2016, Stirling, United Kingdom, 1/09/16. https://doi.org/10.1007/978-3-319-67834-4_18
Kagdi MZ. Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance. In Bracciali A, Caravagna G, Gilbert D, Tagliaferri R, editors, Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Springer . 2017. p. 220-234. (Lecture Notes in Computer Science (LNCS)). https://doi.org/10.1007/978-3-319-67834-4_18
Kagdi, Mohammad Ziyad. / Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance. Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. editor / Andrea Bracciali ; Giulio Caravagna ; David Gilbert ; Roberto Tagliaferri. Springer , 2017. pp. 220-234 (Lecture Notes in Computer Science (LNCS)).
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