A biophysical network model displaying the role of basal ganglia pathways in action selection

Cem Yucelgen; Berat Denizdurduran; Selin Metin; Rahmi Elibol; Neslihan Serap Sengor

doi:10.1007/978-3-642-33269-2_23

A biophysical network model displaying the role of basal ganglia pathways in action selection

Cem Yucelgen^*, Berat Denizdurduran, Selin Metin, Rahmi Elibol, Neslihan Serap Sengor

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Basal ganglia circuits are known to have role in a wide range of behaviour spanning from movement initiation to high order cognitive processes as reward related learning. Here, the intention is to have a biophysically realistic model of basal ganglia circuit for voluntary motor action selection. The ultimate aim is to provide a framework for models which could help comprehension of complex processes. To fulfill this aim a model capable of simulating direct, indirect and hyperdirect pathways with modified Hodgkin-Huxley neuron model is proposed. This model considers more neural structures than the works similar in the literature and can simulate activity of neurons in the neural structures taking part in action selection. The model proposed is shown to be versatile as the simulation results obtained are similar to the neuron activity recordings of the considered neural structures published previously.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
Pages	177-184
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-33269-2_23
Publication status	Published - 2012
Event	22nd International Conference on Artificial Neural Networks, ICANN 2012 - Lausanne, Switzerland Duration: 11 Sept 2012 → 14 Sept 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7552 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Artificial Neural Networks, ICANN 2012
Country/Territory	Switzerland
City	Lausanne
Period	11/09/12 → 14/09/12

Keywords

action selection
Basal ganglia
computational model

Access to Document

10.1007/978-3-642-33269-2_23

Cite this

Yucelgen, C., Denizdurduran, B., Metin, S., Elibol, R., & Sengor, N. S. (2012). A biophysical network model displaying the role of basal ganglia pathways in action selection. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings (PART 1 ed., pp. 177-184). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7552 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-33269-2_23

Yucelgen, Cem ; Denizdurduran, Berat ; Metin, Selin et al. / A biophysical network model displaying the role of basal ganglia pathways in action selection. Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 1. ed. 2012. pp. 177-184 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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abstract = "Basal ganglia circuits are known to have role in a wide range of behaviour spanning from movement initiation to high order cognitive processes as reward related learning. Here, the intention is to have a biophysically realistic model of basal ganglia circuit for voluntary motor action selection. The ultimate aim is to provide a framework for models which could help comprehension of complex processes. To fulfill this aim a model capable of simulating direct, indirect and hyperdirect pathways with modified Hodgkin-Huxley neuron model is proposed. This model considers more neural structures than the works similar in the literature and can simulate activity of neurons in the neural structures taking part in action selection. The model proposed is shown to be versatile as the simulation results obtained are similar to the neuron activity recordings of the considered neural structures published previously.",

keywords = "action selection, Basal ganglia, computational model",

author = "Cem Yucelgen and Berat Denizdurduran and Selin Metin and Rahmi Elibol and Sengor, {Neslihan Serap}",

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Yucelgen, C, Denizdurduran, B, Metin, S, Elibol, R & Sengor, NS 2012, A biophysical network model displaying the role of basal ganglia pathways in action selection. in Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7552 LNCS, pp. 177-184, 22nd International Conference on Artificial Neural Networks, ICANN 2012, Lausanne, Switzerland, 11/09/12. https://doi.org/10.1007/978-3-642-33269-2_23

A biophysical network model displaying the role of basal ganglia pathways in action selection. / Yucelgen, Cem; Denizdurduran, Berat; Metin, Selin et al.
Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 1. ed. 2012. p. 177-184 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7552 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sengor, Neslihan Serap

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AB - Basal ganglia circuits are known to have role in a wide range of behaviour spanning from movement initiation to high order cognitive processes as reward related learning. Here, the intention is to have a biophysically realistic model of basal ganglia circuit for voluntary motor action selection. The ultimate aim is to provide a framework for models which could help comprehension of complex processes. To fulfill this aim a model capable of simulating direct, indirect and hyperdirect pathways with modified Hodgkin-Huxley neuron model is proposed. This model considers more neural structures than the works similar in the literature and can simulate activity of neurons in the neural structures taking part in action selection. The model proposed is shown to be versatile as the simulation results obtained are similar to the neuron activity recordings of the considered neural structures published previously.

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Yucelgen C, Denizdurduran B, Metin S, Elibol R, Sengor NS. A biophysical network model displaying the role of basal ganglia pathways in action selection. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 1 ed. 2012. p. 177-184. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-33269-2_23

A biophysical network model displaying the role of basal ganglia pathways in action selection

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