Novel Approaches in Treating Major Depressive Disorder (Depression)


Milena Čukić Radenković
Department for General Physiology and Biophysics, University of Belgrade, Belgrade, Serbia and Amsterdam Health and Technology Institute, HealthInc, Amsterdam, the Netherlands

Series: New Developments in Medical Research
BISAC: MED105000

Depression is a serious problem. Serious problems often need a complex solution. In her description of novel approaches to treating depression, Dr. Čukić is summarizing her results from the beginning of her scientific endeavor. As an engineer of electronics with a strong background in theoretical physics, biophysicist and neuroscientist, she aims at filling in the gap between disciplines needed to bring the innovation in the treatment of depression. Starting from the history of electrical and magnetic stimulation important for this field, she is combining the knowledge from biophysics and electromagnetic to explain how both modalities of stimulation can affect our neural tissue.

Reviewing the most essential concepts in physiological complexity, she illustrates all the relevant research in different attempts to understand how we can detect the very subtle changes characteristic for a disorder. Those can be recognized from several electrical signals recorded from the body (electrophysiological signals). Fractal and nonlinear measures are in use for several decades, but are still not widely utilized in clinical practice due to deeply rooted obsolete mathematical models originated from the 19th century. Connecting the powerful models from machine learning (data mining) with measures of complexity and irregularity, Dr. Čukić demonstrates how their synergy can bring innovative solutions in psychiatry. She tackles crucial questions like “Should scientific research in psychiatry go online?”

One of the central questions she is trying to answer is why two modalities of electromagnetic stimulation-rTMS and tDCS- are effective in treatments of depression. A combination of fractal and nonlinear analysis and a well-performed machine learning can become a useful addition to present practice: decision support solution. We can consider it a test which is accessible, easy to use and cost-effective in comparison to many other methodologies tested in contemporary scientific literature. The question is, how long it takes that something scientifically proven translates to clinical practice. Remember how long it took for all doctors to start washing their hands. We can only hope this translation would be faster. Many people need that badly.
(Imprint: Nova Medicine and Health)



Table of Contents



Chapter 1. On Depression (Plus Novel Trends)

Chapter 2. On Electric Stimulation for Depression

Chapter 3. Brain-Shift tDCS Induced: An EEG Study
Milena Čukić Radenković, Miodrag Stokić, Slavoljub Radenković, Miloš Ljubisavljević and Dragoljub Donald Pokrajac

Chapter 4. On Magnetic Stimulation for Depression

Chapter 5. Physiological Complexity and Depression

Chapter 6. Why rTMS and tDCS are Effective in MDD

Chapter 7. Machine Learning for Depression Detection and Forecasting

Chapter 8. How Long until Something Confirmed in Research Be Translated to Clinical Practice

Chapter 9. Where To?


About the Author

This book is written for anyone interested in navigating herself or loved one to a more efficient treatment of depression. It is also for those who are clinical professionals who are working with depressive patients, and taking care of them. It can be interested for researchers in neuroscience, medicine/clinical psychology and psychiatry, but also those who are working in mental health institutions and daily hospitals, as well as in nursery homes for elderly. The book can be important for understanding the extent of knowledge about treating depression not limited to medication and psychology.

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