Abstract
Several neurological and neuropsychiatric conditions such as schizophrenia, depression, brain damage and neurodegenerative diseases are associated to alterations in the complex way the human brain processes information at both local and global scales. Quantifying the complexity of this "effective connectivity" in health and its alterations in pathological conditions are major challenges of today's neuroscience. In a series of recent studies, the candidate, in collaboration with international research groups, has demonstrated that the macro-scale complexity of the patterns of thalamocortical effective connectivity can be estimated noninvasively from electroencephalographic data by employing a novel measure called the Perturbation Complexity Index (PCI) (Casali et al., Science Translational Medicine, 2013). This measure was promptly highlighted by the scientific community as the most promising index for objectively determining the degree of brain function in comatose patients. Aiming to further develop the PCI from a technical and scientific perspective, we propose here a close collaboration between the group of Neuroengineering and Computation of the ICT/UNIFESP and the TMS/EEG laboratories at the University of Milan and the University of Pittsburgh in order to standardize the calculation of the PCI, validate its use in brain damaged patients and develop new tools to better characterize brain complexity. Different versions of the index will be tested in simulated signals and in TMS/EEG data recorded in healthy subjects and in patients suffering from conditions including schizophrenia, Alzheimer's disease and brain lesions. Pattern recognition techniques will then be applied to characterize the brain effective connectivity in these conditions. We hope this study will help us bring measures of brain complexity such as PCI closer to clinical application in neurology, ultimately leading to improvements in the accuracy of diagnosis and prognosis as well as in the establishment of management decisions. (AU)
Scientific publications
(7)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
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