There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Elvira Brattico |
| Institution: | University of Bari Aldo Moro |
| Department: | Department of Education, Psychology, Communication |
| Country: | |
| Proposed Analysis: | We propose an MRI and fMRI study aimed to investigate the relation between complex endophenotic biomarkers of functional connectivity of the resting brain in Alzheimer’s Disease (AD) patients and their cognitive reserve. We would like to compare 200 mild, moderate and severe AD patients with 200 controls (patients with self-reported memory complaints who are not diagnosed with mild cognitive impairment or dementia). The analysis of the MRI data will include a pre-processing phase through the use of the SPM12 package for Matlab, where the EPI images will be realigned and then co-registered with the reference template. For the fMRI data, the artifacts will be cleaned by removing the components identified with Independent Component Analysis (ICA) and analyses will then be carried out using open-source code packages such as SPM and FSL. Both anatomical and functional static connectivity matrices will be calculated using the Pearson correlation index and analysed with graph theory. Demographic and behavioral variables will be included in the analysis as covariates. This will allow to identify the recurrent resting-state patterns and their characteristics in terms of duration, probability of occurring and the way in which they alternate. The data relating to neurophysiological fingerprints of neural connectivity will finally be correlated with the neuropsychological data relating to social isolation. The principal investigators of this study are Prof. Elvira Brattico (University of Bari Aldo Moro & Aarhus University, Denmark) and Prof. Giancarlo Logroscino (Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase), and it includes the following collaborators: Prof. Morten Kringelbach and Dr. Leonardo Bonetti (Oxford University), Prof. Peter Vuust and Dr. Massimo Lumaca (Aarhus University). |
| Additional Investigators | |
| Investigator's Name: | Giancarlo Logroscino |
| Proposed Analysis: | We propose an MRI and fMRI study aimed to investigate the relation between complex endophenotic biomarkers of functional connectivity of the resting brain in Alzheimer’s Disease (AD) patients and their cognitive reserve. We would like to compare 200 mild, moderate and severe AD patients with 200 controls (patients with self-reported memory complaints who are not diagnosed with mild cognitive impairment or dementia). The analysis of the MRI data will include a pre-processing phase through the use of the SPM12 package for Matlab, where the EPI images will be realigned and then co-registered with the reference template. For the fMRI data, the artifacts will be cleaned by removing the components identified with Independent Component Analysis (ICA) and analyses will then be carried out using open-source code packages such as SPM and FSL. Both anatomical and functional static connectivity matrices will be calculated using the Pearson correlation index and analysed with graph theory. Demographic and behavioral variables will be included in the analysis as covariates. This will allow to identify the recurrent resting-state patterns and their characteristics in terms of duration, probability of occurring and the way in which they alternate. The data relating to neurophysiological fingerprints of neural connectivity will finally be correlated with the neuropsychological data relating to social isolation. The principal investigators of this study are Prof. Elvira Brattico (University of Bari Aldo Moro & Aarhus University, Denmark) and Prof. Giancarlo Locroscino (Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase), and it includes the following collaborators: Prof. Morten Kringelbach and Dr. Leonardo Bonetti (Oxford University), Prof. Peter Vuust and Dr. Massimo Lumaca (Aarhus University). |
| Investigator's Name: | Fulvia Campo |
| Proposed Analysis: | We propose an MRI and fMRI study aimed to investigate the relation between complex endophenotic biomarkers of functional connectivity of the resting brain in Alzheimer’s Disease (AD) patients and their cognitive reserve. We would like to compare 200 mild, moderate and severe AD patients with 200 controls (patients with self-reported memory complaints who are not diagnosed with mild cognitive impairment or dementia). The analysis of the MRI data will include a pre-processing phase through the use of the SPM12 package for Matlab, where the EPI images will be realigned and then co-registered with the reference template. For the fMRI data, the artifacts will be cleaned by removing the components identified with Independent Component Analysis (ICA) and analyses will then be carried out using open-source code packages such as SPM and FSL. Both anatomical and functional static connectivity matrices will be calculated using the Pearson correlation index and analysed with graph theory. Demographic and behavioral variables will be included in the analysis as covariates. This will allow to identify the recurrent resting-state patterns and their characteristics in terms of duration, probability of occurring and the way in which they alternate. The data relating to neurophysiological fingerprints of neural connectivity will finally be correlated with the neuropsychological data relating to social isolation. The principal investigators of this study are Prof. Elvira Brattico (University of Bari Aldo Moro & Aarhus University, Denmark) and Prof. Giancarlo Locroscino (Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase), and it includes the following collaborators: Prof. Morten Kringelbach and Dr. Leonardo Bonetti (Oxford University), Prof. Peter Vuust and Dr. Massimo Lumaca (Aarhus University). |
| Investigator's Name: | Francesco Carlomagno |
| Proposed Analysis: | We propose an MRI and fMRI study aimed to investigate the relation between complex endophenotic biomarkers of functional connectivity of the resting brain in Alzheimer’s Disease (AD) patients and their cognitive reserve. We would like to compare 200 mild, moderate and severe AD patients with 200 controls (patients with self-reported memory complaints who are not diagnosed with mild cognitive impairment or dementia). The analysis of the MRI data will include a pre-processing phase through the use of the SPM12 package for Matlab, where the EPI images will be realigned and then co-registered with the reference template. For the fMRI data, the artifacts will be cleaned by removing the components identified with Independent Component Analysis (ICA) and analyses will then be carried out using open-source code packages such as SPM and FSL. Both anatomical and functional static connectivity matrices will be calculated using the Pearson correlation index and analysed with graph theory. Demographic and behavioral variables will be included in the analysis as covariates. This will allow to identify the recurrent resting-state patterns and their characteristics in terms of duration, probability of occurring and the way in which they alternate. The data relating to neurophysiological fingerprints of neural connectivity will finally be correlated with the neuropsychological data relating to social isolation. The principal investigators of this study are Prof. Elvira Brattico (University of Bari Aldo Moro & Aarhus University, Denmark) and Prof. Giancarlo Locroscino (Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase), and it includes the following collaborators: Prof. Morten Kringelbach and Dr. Leonardo Bonetti (Oxford University), Prof. Peter Vuust and Dr. Massimo Lumaca (Aarhus University). |
| Investigator's Name: | Massimo Lumaca |
| Proposed Analysis: | We propose an MRI and fMRI study aimed to investigate the relation between complex endophenotic biomarkers of functional connectivity of the resting brain in Alzheimer’s Disease (AD) patients and their cognitive reserve. We would like to compare 200 mild, moderate and severe AD patients with 200 controls (patients with self-reported memory complaints who are not diagnosed with mild cognitive impairment or dementia). The analysis of the MRI data will include a pre-processing phase through the use of the SPM12 package for Matlab, where the EPI images will be realigned and then co-registered with the reference template. For the fMRI data, the artifacts will be cleaned by removing the components identified with Independent Component Analysis (ICA) and analyses will then be carried out using open-source code packages such as SPM and FSL. Both anatomical and functional static connectivity matrices will be calculated using the Pearson correlation index and analysed with graph theory. Demographic and behavioral variables will be included in the analysis as covariates. This will allow to identify the recurrent resting-state patterns and their characteristics in terms of duration, probability of occurring and the way in which they alternate. The data relating to neurophysiological fingerprints of neural connectivity will finally be correlated with the neuropsychological data relating to social isolation. The principal investigators of this study are Prof. Elvira Brattico (University of Bari Aldo Moro & Aarhus University, Denmark) and Prof. Giancarlo Locroscino (Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase), and it includes the following collaborators: Prof. Morten Kringelbach and Dr. Leonardo Bonetti (Oxford University), Prof. Peter Vuust and Dr. Massimo Lumaca (Aarhus University). |
