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We assessed the cortical processing of self-movement stimuli in aging and Alzheimer's disease (AD). Our goal was to identify distinguishing effects on neural mechanisms related to driving and navigation. Young (YNC) and older (ONC) normal controls, and early AD patients (EAD) viewed real-world videos and dot motion stimuli simulating self-movement scenes. We recorded visual motion event related potentials (VMERPs) to stimulus motion coherence and speed. Aging delays motion evoked N200s, whereas AD diminishes response amplitudes. Early Alzheimer's disease patients respond to increments in motion coherence, but they are uniquely unresponsive to increments in motion speed that simulate accelerating self-movement. AD-related impairments of self-movement processing may have grave consequences for driving safety and navigational independence.

Navigational impairments limit the quality of life in aging and Alzheimer's disease (AD). These impairments limit way-finding, even in familiar environments, leading to the withdrawal from driving and independent living. Autonomous navigation greatly relies on the visual processing of optic flow, the patterned visual motion that accompanies self-movement (Gibson, 1950). We previously found that AD patients, and a subset of neuropsychologically intact older adults, have selectively increased perceptual thresholds for optic flow (O'Brien et al., 2001). The critical role of optic flow processing in the navigational impairments of aging and AD has been supported by combining the psychophysical analysis of optic flow perception with behavioral assessments of real-world navigation (Mapstone et al., 2003 and Monacelli et al., 2003). Those studies suggest that navigational impairments in aging and AD reflect cortical deficits of optic flow processing that block access to the visual cues about self-movement heading and speed. Visual motion processing has been previously studied by using event related potentials (ERPs) evoked by horizontally moving dot patterns or gratings in normal subjects (Kubová et al., 1990 and Bach and Ullrich, 1994). Such stimuli evoke a negative wave peaking at around 200 ms after motion onset (N200 response). We later modified these techniques by using random dot stimuli that simulate the radial pattern of optic flow and were able to evoke posterior N200s in older adults and AD patients, and relate them to navigational deficits in AD (Kavcic et al., 2006). Furthermore, linking these deficits to responses evoked by the sudden presentation of a stationary dot pattern revealed cortical hyperresponsiveness in our most mildly impaired patients, raising the possibility that early hyperresponsiveness might be a precursor to more profound deficits (Fernandez et al., 2007). To better understand the neural mechanisms and behavioral implications of navigational impairments in aging and AD we varied the motion coherence and speed in real-world video clips of optic flow. Those pilot studies are followed by detailed analysis of responsiveness to simulated optic flow. We find that coherence and speed have different effects on motion responses highlighting behaviorally important distinctions between aging and early AD.