Subspecialty Programs

The Alzheimer's Disease and Memory Disorders Center

Efficacy of Quantitative EEG Neurocognitive Training in Early-Stage Alzheimer's Disease

Elena Festa Martino, Principal Investigator

Alzheimer's disease (AD) is the most common form of dementia in the elderly, accounting for roughly 50% of all reported cases. Although the rapid growth in the elderly population has increased the prevalence of AD, no real effective treatment of the disease has emerged. One novel and potentially fruitful approach that has yet to be evaluated is the use of electroencephalographic (EEG) neurofeedback training (NFT) in conjunction with current pharmacological treatments. NFT, a form of biofeedback in which the subject trains to control attributes of brain wave activity, has previously been found to be successful in reducing the cognitive deficits in children with ADHD. Until more effective biological treatments emerge, behavioral interventions such as NFT that have the potential to not only delay the progressive deterioration in AD patients' cognitive function, but to also make real improvements in current functioning, need to be systematically investigated.

Both the neuropathological and cognitive changes seen in AD suggest that NFT may prove to be particularly effective in this population. First, AD pathology displays a strong predilection for those cortical lamina and cell types that support feedforward, feedback, and lateral cortical connections within limbic and neocortical association areas, producing a disruption in the corticocortical projections that connect distinct but functionally related cortical regions. In a recent study, we found behavioral evidence that this disruption of corti co cortical projections leads to a specific impairment in integrating sensory features across distinct cortical pathways. Also consistent with the disruption in corti co cortical projections, quantitative EEG (qEEG) studies have found decreases in EEG coherence (i.e., changes in the synchronization of regional cortical activity) in AD not seen in normal aging4-6. Given that NFT is thought to particularly enhance effective interactions across cortical regions, NFT may help to counteract the functional disconnectivity associated with the disease.

Second, AD patients have been found to have neuronal loss in such subcortical regions as the basal forebrain and the locus coeruleus, along with corresponding decrements in neocortical levels of cholinergic and noradrenergic markers, respectively. These projection systems have been found to play critical roles in attention and alerting, and both types of disturbances have previously been observed in AD7. Consistent with these findings, a number of qEEG studies have demonstrated relative power decreases in higher frequency bands (e.g., alpha & beta) along with increases in lower frequency bands (e.g., delta & theta); such power spectra changes have previously been associated with deficits in alertness and attention in other patient populations (e.g., children with ADHD) - perhaps due in part to similar noradrenergic deficits8. NFT has previously been used most effectively to ameliorate the attentional deficits in ADHD by modifying cortical activity through reinforcement to increase high frequency activity while simultaneously decreasing low frequency activity (e.g., theta suppression/alpha enhancement). Given that AD patients display similar power spectral profile abnormalities as well as similar attentional impairments as patients with ADHD, this type of NFT protocol may also prove extremely effective in AD patients.

The purpose of this project is therefore to systematically assess the efficacy of NFT in enhancing cognitive performance in AD. Separate groups of elderly and AD patients will receive true NFT, mock NFT, or no training across a six-month time period. Assessments will occur at several time points within this period to track the relative changes in cognitive function concurrent with changes in brain activity across the groups. We will examine overall cognitive status using standard neuropsychological tests, brain wave activity using qEEG analyses, and specific aspects of cognitive function that should be particularly sensitive to NFT in AD patients (i.e., sensory integration, attention, and alerting) using a computerized neurocognitive battery.  Contact Elena Festa-Martino at 863-9168.

Funded by the Alzheimer's Association