Kendrick Kay

Kendrick Kay


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 March 2008 in Nature
Verified
Journal Article
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KKKendrick Kay
Kendrick Kay
TNThomas Naselaris
Thomas Naselaris
RPRyan J. Prenger
Ryan J. Prenger
JGJack Gallant
Jack Gallant

1 May 2011 in NeuroImage
Verified
Journal Article
Closed access
TNThomas Naselaris
Thomas Naselaris
KKKendrick Kay
Kendrick Kay
SNShinji Nishimoto
Shinji Nishimoto
JGJack Gallant
Jack Gallant

16 December 2021 in Nature Neuroscience
Verified
Journal Article
Closed access
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EAEmily J. Allen
Emily J. Allen
GSGhislain St-Yves
Ghislain St-Yves
YWYihan Wu
Yihan Wu
JBJesse L. Breedlove
Jesse L. Breedlove
JPJacob S. Prince
Jacob S. Prince
KKKendrick Kay
Kendrick Kay

1 September 2009 in Neuron
Verified
Journal Article
Closed access
TNThomas Naselaris
Thomas Naselaris
RPRyan J. Prenger
Ryan J. Prenger
KKKendrick Kay
Kendrick Kay
MOMichael Oliver
Michael Oliver
JGJack Gallant
Jack Gallant

15 July 2013 in Journal of Neurophysiology
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Journal Article
Closed access
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KKKendrick Kay
Kendrick Kay
JWJonathan Winawer
Jonathan Winawer
AMAviv Mezer
Aviv Mezer
BWBrian A. Wandell
Brian A. Wandell
Neurons within a small (a few cubic millimeters) region of visual cortex respond to stimuli within a restricted region of the visual field. Previous studies have characterized the population response of such neurons using a model that sums contrast linearly across the visual field. In this study, we tested linear spatial summation of population responses using blood oxygenation level-dependent (BOLD) functional MRI. We measured BOLD responses to a systematic set of contrast patterns and discovered systematic deviation from linearity: the data are more accurately explained by a model in which a compressive static nonlinearity is applied after linear spatial summation. We found that the nonlinearity is present in early visual areas (e.g., V1, V2) and grows more pronounced in relatively anterior extrastriate areas (e.g., LO-2, VO-2). We then analyzed the effect of compressive spatial summation in terms of changes in the position and size of a viewed object. Compressive spatial summation is consistent with tolerance to changes in position and size, an important characteristic of object representation.

3 November 2013 in Nature Medicine
Verified
Journal Article
Open access
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AMAviv Mezer
Aviv Mezer
JYJason D Yeatman
Jason D Yeatman
NSNikola Stikov
Nikola Stikov
KKKendrick Kay
Kendrick Kay
Nam-Joon ChoNam-Joon Cho
Nam-Joon Cho
BWBrian A Wandell
Brian A Wandell
There is an urgent need for quantitative magnetic resonance approaches for assessing brain development, as well as for studying the effects of drugs on neural tissue inflammation. Aviv Mezer and colleagues have developed a neuroimaging method for the quantification of local tissue volume and tissue-surface interaction, producing reliable quantitative measurements across a range of scanners. They apply their method to both the healthy brain and individuals with relapsing-remitting multiple sclerosis. Here, we describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent quantitative estimate of MTV can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second, we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.