Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Modeling basal ganglia circuits with mass model equations Bazal çekirdek devrelerinin yiǧin modeli denklemleri ile modellenmesi
Date
2017-02-23
Author
Elibol, Rahmi
Şengör, Neslihan Serap
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
241
views
0
downloads
Cite This
© 2016 IEEE.In order to understand the cognitive processes, motor actions and the behavioral deficits and neurological disorders rising due to malfunctioning of the related neuronal structures, models at different levels are proposed in computational neuroscience. Models developed considering the nonlinear and distributed working principles of neural structures help to reconstruct the processes but are far away from giving an explicit understanding of the phenomena due to their complexity. However, it is not possible to understand these processes thoroughly with very simple models. To build a relation between these different levels of models and to build a mechanism for understanding these processes, in this work linear model approach is considered. Basal ganglia circuits which are effective in motor action initiation, decision making and action selection is considered and in order to guide through more complex computational models and to understand the working principle, a linear system approach is considered. Though the model proposed is very simple, it gives enough insight to understand the role of basal ganglia circuits and the model is able to show the role of dopamine on modulating the inputs from cortex.
Subject Keywords
Basal Ganglia circuits
,
direct and indirect pathway
,
Dopamine
,
hyper-direct pathway
,
mass model
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85016093284&origin=inward
https://hdl.handle.net/11511/98280
DOI
https://doi.org/10.1109/tiptekno.2016.7863131
Conference Name
2016 Medical Technologies National Conference, TIPTEKNO 2016
Collections
Graduate School of Informatics, Conference / Seminar
Suggestions
OpenMETU
Core
A computational model of basal ganglia circuits investigating the role of dopamine on direct and indirect pathways Bazal Çekirdek Devrelerinde Dopaminin Doǧrudan ve Dolayli Yolaklara Etkisine Ilişkin Bir Hesaplamali Model
Elibol, Rahmi; Şengör, Neslihan Serap (2016-01-06)
© 2015 IEEE.Due to the investigations carried out in neuroscience, it has been clear that basal ganglia circuits are not active only in motor actions but also take part in cognitive processes. With recent studies on processes as decision making and behavioral deficits as addiction, the role of basal ganglia in these processes has been revealed without suspicion. The activity in direct and indirect pathways, two of the three most mentioned pathways of basal ganglia, is known to be modified by neurotransmitte...
A model on building and modifying the stimulus action association in the brain Beyinde Uyaran Hareket Ilişkisinin Oluşmasi ve Uyarlanmasina Dair Bir Model
Ercelik, Emec; Elibol, Rahmi; Şengör, Neslihan Serap (2015-06-19)
© 2015 IEEE.It is expected that building computational models of neural structures taking part in generating cognitive processes and emotions would not only help us understanding the brain but also give us clues to diagnose and develop treatment for neurological disorders and diseases. In this work, a computational model of cognitive task, goal directed behavior is considered. The cortex-basal ganglia-thalamus loop which is known to be effective in goal directed behavior has been modeled. In the model, the ...
Longitudinal data analysis with statistical and machine learning methods in neuroscience
Çakar, Serenay; Gökalp Yavuz, Fulya; Department of Statistics (2022-8)
Exploration of brain activity under different conditions has been subject to many neuroscience studies. The recent developments in cognitive studies provide the opportunity to work on neural correlates of specific cognitive processes such as working memory, decision making, response inhibition, perception, and sensation. Brain response studies constitute multidimensional, multilevel or nested data sets formed by different parts of the brain of individuals. Hence, it is of significant importance to implement...
Impact of antibiotic induced gut microbiota alteration on cognitive abilities and behaviours of mice
Ceylani, Taha; Gözen, Ayşe Gül; Doğru, Ewa; Department of Biology (2018)
Recently arising studies with animal models show that there is a bidirectional communication between gut microbiota and central nervous system (CNS) through neural, endocrine and immune pathways which influences brain function and behavior. Apparently, gut microbiota may play a role in the regulation of anxiety, mood, cognition, and pain sensation. Gut microbiota may cause gastrointestinal disorders, such as irritable bowel syndrome (IBS), which can be comorbid with stress-related psychiatric conditions inf...
Multi-subject brain decoding using deep learning techniques
Velioğlu, Burak; Yarman Vural, Fatoş Tunay; Ertekin Bolelli, Şeyda; Department of Computer Engineering (2016)
In this study, a new method is proposed for analyzing and classifying images obtained by functional magnetic resonance imaging (fMRI) from multiple subjects. Considering the multi level structure of the brain and success of deep learning architectures on extracting hierarchical representations from raw data, these architectures are used in this thesis. Initially, the S500 data set collected in the scope of Human Connectome Project (HCP) is used to train formed deep neural networks in an unsupervised fashion...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
R. Elibol and N. S. Şengör, “Modeling basal ganglia circuits with mass model equations Bazal çekirdek devrelerinin yiǧin modeli denklemleri ile modellenmesi,” presented at the 2016 Medical Technologies National Conference, TIPTEKNO 2016, Antalya, Türkiye, 2017, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85016093284&origin=inward.