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pro vyhledávání: '"Gallant, Jack L"'
Autor:
Slivkoff, Storm, Gallant, Jack L.
Over the past few decades, neuroscience experiments have become increasingly complex and naturalistic. Experimental design has in turn become more challenging, as experiments must conform to an ever-increasing diversity of design constraints. In this
Externí odkaz:
http://arxiv.org/abs/2012.02361
Akademický článek
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The functional relationship between an input and a sensory neuron's response can be described by the neuron's stimulus-response mapping function. A general approach for characterizing the stimulus-response mapping function is called system identifica
Externí odkaz:
http://arxiv.org/abs/1811.01043
Publikováno v:
In NeuroImage 1 December 2022 264
Publikováno v:
In Cortex October 2021 143:127-147
Much of the human cortex seems to be organized into topographic cortical maps. Yet few quantitative methods exist for characterizing these maps. To address this issue we developed a modeling framework that can reveal group-level cortical maps based o
Externí odkaz:
http://arxiv.org/abs/1504.03622
Autor:
Bilenko, Natalia Y., Gallant, Jack L.
Canonical correlation analysis (CCA) is a valuable method for interpreting cross-covariance across related datasets of different dimensionality. There are many potential applications of CCA to neuroimaging data analysis. For instance, CCA can be used
Externí odkaz:
http://arxiv.org/abs/1503.01538
Akademický článek
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The human brain is adept at solving difficult high-level visual processing problems such as image interpretation and object recognition in natural scenes. Over the past few years neuroscientists have made remarkable progress in understanding how the
Externí odkaz:
http://arxiv.org/abs/1407.5104