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

Mohammad Ziyad Kagdi

doi:10.1007/978-3-319-67834-4_18

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

Mohammad Ziyad Kagdi

School of Medicine, Medical Sciences & Nutrition

Research output: Chapter in Book/Report/Conference proceeding › Published conference 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 language	English
Title of host publication	Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016
Editors	Andrea Bracciali, Giulio Caravagna, David Gilbert, Roberto Tagliaferri
Publisher	Springer
Pages	220-234
Number of pages	15
ISBN (Electronic)	9783319678344
ISBN (Print)	9783319678337
DOIs	https://doi.org/10.1007/978-3-319-67834-4_18
Publication status	Published - 17 Oct 2017
Event	CIBB 2016: Computational Intelligence Methods for Bioinformatics and Biostatistics - University of Stirling, Stirling, United Kingdom Duration: 1 Sept 2016 → 3 Sept 2016 Conference number: 13 http://www.cs.stir.ac.uk/events/cibb2016/

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Publisher	Springer
Volume	10477
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	CIBB 2016
Country/Territory	United Kingdom
City	Stirling
Period	1/09/16 → 3/09/16
Internet address	http://www.cs.stir.ac.uk/events/cibb2016/

Bibliographical note

Acknowledgements

I would like to express my sincere gratitude to Dr. Rene te Boekhorst for his valued support and guidance extended to me.

Keywords

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

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Accepted Manuscript
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-67834-4_18
Accepted author manuscript, 840 KBLicence: Other

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 proceeding › Published conference 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)). doi: 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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Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this