P1‐002: Monitoring cholinergic activty in the progression of Alzheimer's disease using an EEG index based on cholinergic activity

The only medications indicated for treatment of mild AD are the cholinesterase inhibitors. The effects of the medicines are measured by cognitive tests and by caregiver reports but there are no direct biological means of evaluating treatment effects. A theoretically possible method is to measure the cholinergic response of these drugs in the brain. It has been proposed that the EEG changes seen in AD are primarily a reflection of cholinergic dysfunction. We postulate that by establishing a “cholinergic index” in EEG registration, the treatment effects of cholinergic drugs could be measured and thereby the treatment response. In a clinical trial where 110 healthy elderly participants participated an EEG registration was obtained from each participant before and after a 0.15 mg im administration of scopolamine. Since scopolamine affects the cholinergic neurotransmitter system, a cholinergic EEG index was created by applying Statistical Pattern Recognition (SPR) to a large set of EEG features, by considering the group before and after scopolamine administration as two distinct groups. The resulting classifier results in an index that correlates with the cholinergic activity in the subject.A longitudinal study with 40 AD patients over 1–3 years (4–11 visits) was performed. The cholinergic index was calculated for each participant at each visit. The EEG cholinergic index constructed by SPR is shown to correlate with the state of the cholinergic system, by comparing the index calculated for the individuals in the group before and after administration of scopolamine.The cholinergic index of the individuals in the longitudinal study is correlated to their clinical state, and is used to group the subjects into responders and non-responders to treatment based on cholinergic activity levels based on the cholinergic index. Following a more substantial clinical validation and an easy access to the methodology, we expect this application of clinical EEG to become important in measuring the effect of treatment. Furthermore this approach could be valuable in following the progression of AD. The underlying technology is well known, widely available and inexpensive in relation to other imaging techniques.