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Richard Levy

Researcher at Cornell University

Publications -  46
Citations -  2793

Richard Levy is an academic researcher from Cornell University. The author has contributed to research in topics: Frontotemporal dementia & Cognition. The author has an hindex of 22, co-authored 44 publications receiving 2501 citations. Previous affiliations of Richard Levy include New York University & Johns Hopkins University.

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FEATURE ARTICLE Apathy and the Functional Anatomy of the Prefrontal Cortex--Basal Ganglia Circuits

Richard Levy, +1 more
TL;DR: The clinical signs of apathy are a common feature of prefrontal and basal ganglia lesions or dysfunctions and can therefore help to improve our understanding of the functional anatomy of the prefrontal--basal ganglia system as discussed by the authors.
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Abnormal Cerebellar Development and Foliation in BDNF−/− Mice Reveals a Role for Neurotrophins in CNS Patterning

TL;DR: Behavioral and biochemical data suggest that BDNF acts as an anterograde or an autocrine-paracrine factor to regulate survival and morphologic differentiation of developing CNS neurons, and thereby affects neural patterning.
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Recommendations to distinguish behavioural variant frontotemporal dementia from psychiatric disorders

TL;DR: The goal of the present paper was to review the existing literature on the diagnosis of bvFTD and its differential diagnosis with primary psychiatric disorders to provide consensus recommendations on the clinical assessment and clarify the role of 18F-fluorodeoxyglucose PET for the exclusion of b vFTD.
Proceedings ArticleDOI

Lightning-2: a high-performance display subsystem for PC clusters

TL;DR: A renderer that achieves 106 Mtri/s on an 8-node cluster using Lightning-2 to perform sort-last depth compositing is demonstrated, and it is demonstrated that this renderer can be upgraded across multiple generations of graphics accelerators with little effort.
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Visualization of disconnection syndromes in humans.

TL;DR: This paper proposes an approach to clinico-anatomical correlation, based on a standardized atlas of white matter tracts derived from diffusion tensor imaging tractography, which will help researchers and clinicians to identify the neural bases of cognitive abilities and the behavioral consequences of brain lesions.