Poster A2, Thursday, August 16, 10:15 am – 12:00 pm, Room 2000AB

Early Detection of Alzheimer's Disease: Combining EEG and Pupillometry to Assess Automatic and Controlled Language Processing Dynamics

Nicole Amichetti1, Elena Festa1, William Heindel1;1Brown University

The ability to detect presymptomatic individuals who are at greatest risk for progressing to Alzheimer's disease (AD) is critical for the effective application of therapeutic strategies. However, biological markers alone are insufficient to identify at-risk individuals given the presence of AD pathology in a large number of cognitively healthy elderly. Standard neuropsychological assessments also fail to detect the earliest cognitive changes as compensatory processes moderate the relationship between pathology and cognitive performance. That is, two individuals can display similar levels of performance despite substantial differences in the pathological burden placed on neural systems. The transition from healthy aging to AD can be viewed as a breakdown of homeostasis due to the combined presence of two AD-related pathological changes: A breakdown in bottom-up integration processes within perceptual and memory representation systems due to a disruption of functional connectivity among posterior cortical regions, leading to greater reliance on top-down compensatory processes; and a disruption within frontotemporal white matter pathways mediating these top-down compensatory control processes. Given this view, the simultaneous assessment of the efficiency of bottom-up perceptual processes and integrity of recruited counteracting top-down control systems can provide insight into the homeostatic health of the aging brain and will allow for the identification of at-risk yet currently asymptomatic elderly. Language impairment is observed frequently AD, often early in disease progression. Also, language impairment signals greater risk for developing AD in prodromal individuals. Therefore, we employ concurrent electrophysiological (EEG) and pupillometry measures to systematically assess the dynamics of automatic and controlled language processing in patients with prodromal AD and cognitively healthy elderly with high or low biomarker risk of AD. This study employs an 'anomalous sentence paradigm' to systematically vary task difficulty and measure underlying effort required in real-time. Of interest is the N400 component which reflects automatic and controlled semantic integration and its amplitude is modulated by the degree of integration difficulty as determined by the sentence context. For example, the sentence "The dog came inside and drank the water" elicits a small N400 amplitude, whereas, "The dog came inside and drank the mustache" with its anomalous, ending word elicits a larger amplitude. Sentences are presented in an auditory manner, counterbalanced across three conditions: 1) sentences which are highly contextually constrained and contain a highly probable final word (as predicted by the preceding context); 2) moderately contextually constrained sentences with a low-moderately probable final word; 3) sentences which are highly contextually constrained and contain an anomalous or highly improbable final word. Neural activity is simultaneously recorded with pupil dilation, as task-evoked cognitive effort recruited to compensate for either increasing task difficulty or diminished cognitive ability can be measured via pupil dilation, an indirect marker of LC-NE activity. Results are discussed in terms of neural activity patterns and cognitive effort required for semantic integration and compared across cognitively healthy, impaired, and at-risk elderly. Also discussed is the relationship between frontal theta oscillations and pupil dilation across task conditions differing in required allocation of cognitive effort, a topic yet unexplored in at risk individuals.

Topic Area: Control, Selection, and Executive Processes