Journal article
Modelling ECT effects by connectivity changes in cortical neural networks
Neurocomputing (Amsterdam), v 69(10), pp 1341-1347
2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Biomathematical methods were applied to investigate how cortical neurodynamics depends on network connectivity. In particular, we study changes in the EEG pattern of depressed patients, following electroconvulsive therapy (ECT). The aim is to gain a better understanding of the neural mechanisms responsible for these changes, which include clear phase shifts in the EEG dynamics. This understanding is intended to provide clinical guidance in predicting ECT dose and response in depressed patients.
Metrics
Details
- Title
- Modelling ECT effects by connectivity changes in cortical neural networks
- Creators
- Y Gu - Department of Biometry and Engineering, SLU, Uppsala, SwedenG Halnes - Department of Biometry and Engineering, SLU, Uppsala, SwedenH Liljenström - Department of Biometry and Engineering, SLU, Uppsala, SwedenD von Rosen - Department of Biometry and Engineering, SLU, Uppsala, SwedenB Wahlund - Neurotec, Karolinska Intitutet, Huddinge University Hospital, 141 86 Stockholm, SwedenH Liang - School of Health Information Sciences, University of Texas at Houston, Houston, TX 77030, USA
- Publication Details
- Neurocomputing (Amsterdam), v 69(10), pp 1341-1347
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000237873900076
- Scopus ID
- 2-s2.0-33748795616
- Other Identifier
- 991014877889304721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
Source: SDGs in the Output
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence