I am Arshia Amiri, a newly graduated Doctor of Health Sciences from University of Eastern Finland (UEF) in the program of Welfare, Health and Management and my major subjects of interest are leadership, health economics, health and social services, health promotion and policy and empirical data analysis in health and medical sciences. To mention about my previous academic career, I have done two World Health Organization (WHO) projects, I have been teacher in university for 2 years and I have been junior researcher in UEF.
Now, I am studying in JAMK at Department of Health and Social Studies and I am organizing a new interesting research project as my postdoctoral research project with the application in neurological science and medical diagnosis methods. In this research project there would be a collaboration between different universities like University of Jyväskylä, University of Eastern Finland, University of Helsinki, etc. and I would like to call JAMK teachers and intelligent students for participating in this research. Below, I add the research proposal would be interesting and as you see, some researchers with background and experiences in neurology (fMRI imaging), medical physics, mathematics (inverse problems), applied medical statistics, computer science would be needed.
While participating this research project you would find academic benefits like scientific collaboration and publishing scientific articles. If you are interested to participate in this research project, you have more questions about it please send me email or leave a comment here.
Mapping the Brain’s Causal Relationships Using fMRI Data
Future of Neuroscientific Diagnosis Methods
The following research project would provide a new practical guideline based on the dynamic brain neuronal interaction, i.e. providing map of causal effect over the brain, to find a more reliable brain-related diagnosis method compared to stochastic diagnosis methods used in medical science nowadays. As the mechanism of the human brain is still obscure in the process of various brain diseases, this research project undertakes a new attempt to present a different technique of analyzing brain mechanisms with depicting the comprehensive brain map of directed causal effects over the neuronal populations interactions. For the first time, panel multivariate versions of Granger causality test – which have a more reliable result instead of bivariate tests used in previous studies – would be proposed to simulate the map of the brain neuronal interactions in fMRI data of different complex visuomotor tasks. While mapping directed causal interactions over the brain neuronal network, we would be able to quantitate the performance of each parts of brain dynamically and this lead us to introduce a new empirical neuroscientific tool would be applied in health science to diagnosis brain-related diseases and their progressions. Consequently, we would be able to produce a fMRI analyzer computer software to develop the potential of medical diagnosis methods from stochastic analyses to dynamic and more quantitative approaches designed for fMRI test.
2. Critical Need and Expected Scientific Impacts
The results of this research project are significantly significant to elucidate the mechanism of the brain neuronal interactions and causal relationships between brain regions (brain-brain networks) and autonomic nervous system (ANS) outflow (brain-heart links) during the time, and also to provide new dynamic fMRI-based diagnosis method in the brain-related diseases which introduce a practical tool to measure the brain performances more exact and quantitative. Mapping of the brain’s causal relationships would provide us a new method in medical diagnosis which can be used in various practical situations included, but not limited to:
I. Building tools for prediction and prevention of key genomic medicine in complex diseases
II. Measurement the effect of brain tumor or stroke on neuronal populations and effective connectivity in the brain
III. Analyzing the brain-brain networks and brain-heart links in different metabolic conditions
IV. Measurement of coma in a dynamic process and prediction of brain death
V. Alzheimer and dementia diagnosis and its processes in elderly people
VI. Quantitate the effects of neuropsychiatric disorders on neuronal interactions
VII. Effects of pharmalogical treatments on the brain functions
VIII. Analyzing the effect of polypharmacy on the brain damage
IX. Monitoring the long-term effects of drugs, alcohol, nicotine, iodine deficiency etc. on the brain function
X. Analyzing the side effects of chemical and radiation therapy used for cancer treatment on the brain mechanism
3. Intervention to Previous Theoretical and Empirical Studies
To our knowledge, there exist several studies where tried to identify the effect of different neuronal brain regions based on bivariate Granger causality models or fixed-effect hypotheses means that in simulating the causal relationship between two different neuronal regions, they have assumed that the plausible effects of other neuronal population in the brain on the regions included in the Granger causality test is equal to zero and fixed. Here, we criticize previous studies which investigate the brain functional connectivity based on fixed-effect hypothesis and the intervention of this research project to the previous empirical studies would be removing this assumption from our model. In the following project, multivariate panel Granger causality approaches would be used to participate other neuronal regions as control variables in the statistical analysis of functional connectivity patterns in the brain. Hence, the results of this project would be more exact and reliable, statistically.
4. Research Methods and Material
To investigate presence, directions and magnitudes of full brain functional connectivity between neuronal populations network based on fMRI data we use an advanced panel multivariate econometrics analysis based on a priori specification of a model that contains non-preselected regions and connections between them. Econometrics mainstream will help us to evaluate the brain neuronal network using more adaptive methods with the nature of fMRI data and with less statistical limitations.
4.2 Data Management Plan
The data will be collected from Kuopio University Hospital, Massachusetts General Hospital and Department of Biomedicine and Prevention, University of Rome. The research material will be stored in the UEF Share Point Team Place, where is administered and regularly back-up by UEF IT Center and this allow access to them via internet to a safe repository during the possible mobility period.
5. Ethical Issues and Publication Plan
The ethical issues where we follow here are; firstly, respect of self-determination of the research target, secondly, avoiding injuring the targets of research, finally, privacy and data protection. The results of the research will be disseminated through peer-reviewed scientific journals, conference presentations and a monograph.