Motor and Hippocampal Dependent Spatial Learning and Reference Memory Assessment in a Transgenic Rat Model of Alzheimer's Disease with Stroke

Alzheimer's disease (AD) is a debilitating neurodegenerative disease that results in neurodegeneration and memory loss. While age is a major risk factor for AD, stroke has also been implicated as a risk factor and an exacerbating factor. The co-morbidity of stroke and AD results in worsened stroke-related motor control and AD-related cognitive deficits when compared to each condition alone. To model the combined condition of stroke and AD, a novel transgenic rat model of AD, with a mutated form of amyloid precursor protein (a key protein involved in the development of AD) incorporated into its DNA, is given a small unilateral striatal stroke. For a model with the combination of both stroke and AD, behavioral tests that assess stroke-related motor control, locomotion and AD-related cognitive function must be implemented. The cylinder task involves a cost-efficient, multipurpose apparatus that assesses spontaneous forelimb motor use. In this task, a rat is placed in a cylindrical apparatus, where the rat will spontaneously rear and contact the wall of the cylinder with its forelimbs. These contacts are considered forelimb motor use and quantified during video analysis after testing. Another cost-efficient motor task implemented is the beam-walk task, which assesses forelimb control, hindlimb control and locomotion. This task involves a rat walking across a wooden beam allowing for the assessment of limb motor control through analysis of forelimb slips, hindlimb slips and falls. Assessment of learning and memory is completed with Morris water maze for this behavioral paradigm. The protocol starts with spatial learning, whereby the rat locates a stationary hidden platform. After spatial learning, the platform is removed and both short-term and long-term spatial reference memory is assessed. All three of these tasks are sensitive to behavioral differences and completed within 28 days for this model, making this paradigm time-efficient and cost-efficient.