Optimal Control of Nonlinear Networks Dynamics with Applications to Brain Stimulation in Alzheimer's Disease

Simple item page
dc.contributor.advisorSotero-Diaz, Roberto Carlos
dc.contributor.authorSánchez Rodríguez, Lázaro Miguel
dc.contributor.committeememberMonchi, Oury
dc.contributor.committeememberForkert, Nils Daniel
dc.contributor.committeememberKiss, Zelma
dc.contributor.committeememberVasudevan, Kris
dc.date2018-02
dc.date.accessioned2018-01-05T00:24:13Z
dc.date.available2018-01-05T00:24:13Z
dc.date.issued2017-12-20
dc.description.abstractBrain stimulation can modulate the activity of neural circuits impaired by Alzheimer’s disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients’ biological variability. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework.en_US
dc.identifier.citationSánchez Rodríguez, L. M. (2017). Optimal control of nonlinear networks dynamics with applications to brain stimulation in Alzheimer's disease (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/5234
dc.identifier.urihttp://hdl.handle.net/1880/106238
dc.language.isoenen_US
dc.publisher.facultyCumming School of Medicineen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectoptimal controlen_US
dc.subjectnetwork theoryen_US
dc.subjectAlzheimer's diseaseen_US
dc.subjectbrain stimulationen_US
dc.subjectnonlinear dynamicsen_US
dc.subject.classificationNeuroscienceen_US
dc.subject.classificationEngineeringen_US
dc.subject.classificationEngineering--Biomedicalen_US
dc.titleOptimal Control of Nonlinear Networks Dynamics with Applications to Brain Stimulation in Alzheimer's Diseaseen_US
dc.typemaster thesisen_US
thesis.degree.disciplineEngineering – Biomedicalen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrue
ucalgary.thesis.checklistI confirm that I have submitted all of the required forms to Faculty of Graduate Studies. (See <a href="http://grad.ucalgary.ca/current/thesis/ethesis">http://grad.ucalgary.ca/current/thesis/ethesis</a> for more details)en_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2017_sanchezrodriguez_lazaro.pdf
Size:
2.68 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.74 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations