The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study (GWAS) of late-onset Alzheimer disease (LOAD) using a 3 stage design consisting of a discovery stage (Stage 1) and two replication stages (Stages 2 and 3). Both joint and meta-analysis analysis approaches were used. We obtained genome-wide significant results at MS4A4A [rs4938933; Stages 1+2, meta-analysis (PM) = 1.7 × 10−9, joint analysis (PJ) = 1.7 × 10−9; Stages 1–3, PM = 8.2 × 10−12], CD2AP (rs9349407; Stages 1–3, PM = 8.6 × 10−9), EPHA1 (rs11767557; Stages 1–3 PM = 6.0 × 10−10), and CD33 (rs3865444; Stages 1–3, PM = 1.6 × 10−9). We confirmed that CR1 (rs6701713; PM = 4.6×10−10, PJ = 5.2×10−11), CLU (rs1532278; PM = 8.3 × 10−8, PJ = 1.9×10−8), BIN1 (rs7561528; PM = 4.0×10−14; PJ = 5.2×10−14), and PICALM (rs561655; PM = 7.0 × 10−11, PJ = 1.0×10−10) but not EXOC3L2 are LOAD risk loci1–3.

Art historians, artists, psychologists, and neuroscientists have long asserted that artists perceive the world differently than nonartists. Although empirical research on the nature and correlates of skilled drawing is limited, the available evidence supports this view: artists outperform nonartists on visual analysis and form recognition tasks and their perceptual advantages are correlated with and can be largely accounted for by drawing skill. The authors propose an integrative model to explain these results, derived from research in psychology and cognitive neuroscience on how category knowledge, attention, and motor plans influence visual perception. The authors claim that (a) artists' specialized, declarative knowledge of the structure of objects' appearances and (b) motor priming achieved via proceduralization and practice in an artistic medium both contribute to attention-shifting mechanisms that enhance the encoding of expected features in the visual field and account for artists' advantages in drawing and visual analysis. Suggestions for testing the model are discussed.

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Neuroscience of art might give us traction with aesthetic issues. However it can be seen to have trouble modeling the artistically salient semantic properties of artworks. So if meaning really matters, and it does, even in aesthetic contexts, the prospects for this nascent field are dim. The issue boils down to a question of whether or not we can get a grip on the kinds of constraints present and available to guide interpretive behavior in our engagement with works of fine art. I argue that biased competition models of selective attention can be used to solve this problem, generalize to the affective content of our responses to artworks, and so show that research in cognitive neuroscience is germane to the types of problems of interest within the philosophy of art.