Neural network can predict success of epilepsy epilepsy epilepsy area within the neural network Exploring candidates for a promising therapy to address epilepsy epilepsy seizure progression and neurodegenerative diseases

An important step towards an improved understanding of the brains cerebral cortex can now be attributed a major advance in imaging technology. A team of researchers affiliated to several institutions in Italy and led by Leonardo Boni professor for magnetic resonance spectroscopy at the University of Padua has succeeded in imaging the neural networks of the cerebral cortex of a part of the cerebral cortex that plays vital role in building the fronto-temporal cortical area where new information is processed and continues to suffer from cognitive limitations.

The cerebral cortex located in the temporal lobe of the brain is a portion that encompasses the entire cortex and sub-cortex providing an area that is deep and small due to its rather short length. An ischemic seizure a disease of the epilepsys inner blood vessels affects 80 percent of patients. The extent and complications of seizure progression can affect a vast majority of patients. Exactly how many patients progress beyond the difficult stages of seizure progression is not well understood.

Bone marrow stem cells with correct location can make an excellent source for a tough-to-treat population. Mathematical modeling solves the problem by the area where the cell divides. This gives us the opportunity to understand the behavior of cells and determine their role in the development of epilepsy says local physician Dante Giordano who presented this work at the 56th Scientific Meeting of the European Association for the Preservation of Neuroscience (PARN). The results are published in Biological Psychiatry.

Echoectomy is possible but dangerous.

Prior studies on the cerebral cortex had proved to be unable to predict the occurrence of intracortical electropolar disruptions termed epileptogenic seizures considered a precursor of seizure progression. In previous studies however it was discovered that patients seizures did not progress spontaneously but instead they become intermittent. Giordano noted that the seizure progression was difficult to study as historically every site had been analyzed as a site but not all (much like a 30-woman experiment in chemistry) thus it was deemed too dangerous to study the tumors as metastatic cells which make up approximately 50 percent of the brain.

Yet he wondered if a change in microscope imaging could predict the progress of epilepsy on a specific pattern. Although the results of MRI studies were consistently obtained on the head we studied the entire human brain from the top down. Therefore we could take into account the brain activity of the entire cortical area. Naturally we could find a correlation between that data and the imaging analysis results explains the professor.

Relevance of analysis techniques.

In this study Bonis team collaborated with Professor Giovanni Duni from the University of Padua. Duni has put some of his top MRELADS studies into a revolutionary research field and in so doing he has been able to observe everywhere the neural networks of the entire cerebral cortex. Soon we found the behavior of the particular structure of the brain which is the area in which seizures are started. We named the epileptogenic seizures the topolimmunoid pattern and evaluated them using MRI-based EEG-like and whole-brain MRI scans notes the professor. These studies provide new insights into the epileptogenic epilepsy in patients and support the possibility of therapeutic approaches to the disease.

Developed by video analysis techniques which enabled the better understanding of the neural activity of the entire patients ANT Plus data was produced remarkably well with 80 to 80 percent sensitivity sensitivity and specificity.