Alzheimer's disease and dementia are the most common neurodegenerative disorder. Since the number of individuals with AD and dementia is expected to increase considerably in the near future, reliable treatment and diagnosis are critical. Since EEG and neurophysiological technique could be used as a cost-effective screening tool for early detection and diagnosis of the Mild Cognitive Impairment (MCI) stage it may change the objectives of treatment: if dementia could be reliably diagnosed in an early stage, medical treatments would, become curative: they may be used to delay or, hopefully, even bring the disease progress to a halt.
Our long-term research objective is to develop signal processing methods that improve the specificity for diagnosing dementia; we wish to discover signal features that not only significantly differ in AD patients, but also allow us to reliably separate AD patients and control subjects. This approach is valuable for clinical purposes (as diagnostic tool for dementia), and it also more fundamentally contributes to a better understanding of brain dynamics of MCI patients.
The main focus of this Research Topic will be on the most recent developments and ideas in the field of EEG and neurophysiology which will enable us to extract features that improve the specificity for diagnosing AD and dementia. Potential topics include, but are not limited to:
• Quantitative EEG evaluation in diagnosis and prognosis of dementia and AD
• Neurohysiological tecnique advances (ERP, TMA, TDCc etc;) in dementia and AD
• Possible disease model based on neurophysiology in dementia and AD
• EEG and neurophysiological indexes as biomarkers in dementia and AD
• Contribution of neurophysiology about the difference between preclinical and clinical AD
Alzheimer's disease and dementia are the most common neurodegenerative disorder. Since the number of individuals with AD and dementia is expected to increase considerably in the near future, reliable treatment and diagnosis are critical. Since EEG and neurophysiological technique could be used as a cost-effective screening tool for early detection and diagnosis of the Mild Cognitive Impairment (MCI) stage it may change the objectives of treatment: if dementia could be reliably diagnosed in an early stage, medical treatments would, become curative: they may be used to delay or, hopefully, even bring the disease progress to a halt.
Our long-term research objective is to develop signal processing methods that improve the specificity for diagnosing dementia; we wish to discover signal features that not only significantly differ in AD patients, but also allow us to reliably separate AD patients and control subjects. This approach is valuable for clinical purposes (as diagnostic tool for dementia), and it also more fundamentally contributes to a better understanding of brain dynamics of MCI patients.
The main focus of this Research Topic will be on the most recent developments and ideas in the field of EEG and neurophysiology which will enable us to extract features that improve the specificity for diagnosing AD and dementia. Potential topics include, but are not limited to:
• Quantitative EEG evaluation in diagnosis and prognosis of dementia and AD
• Neurohysiological tecnique advances (ERP, TMA, TDCc etc;) in dementia and AD
• Possible disease model based on neurophysiology in dementia and AD
• EEG and neurophysiological indexes as biomarkers in dementia and AD
• Contribution of neurophysiology about the difference between preclinical and clinical AD
