activity
20152020
most citedPrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex

10 citations · 12 across the 4 of their papers we have counts for

collaborators

5 papers

q-bio.NC2020

Design of Complex Experiments Using Mixed Integer Linear Programming

Storm Slivkoff, Jack L. Gallant

Over the past few decades, neuroscience experiments have become increasingly complex and naturalistic. Experimental design has in turn become more challenging, as experiments must…

cs.CY2020

A New Age of Computing and the Brain

Polina Golland, Jack Gallant, Greg Hager +4

The history of computer science and brain sciences are intertwined. In his unfinished manuscript "The Computer and the Brain," von Neumann debates whether or not the brain can be t…

q-bio.NC2018

The unified maximum a posteriori (MAP) framework for neuronal system identification

Michael C. -K. Wu, Fatma Deniz, Ryan J. Prenger +1

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 characteriz…

q-bio.QM201510 cited

PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex

Alexander G. Huth, Thomas L. Griffiths, Frederic E. Theunissen +1

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…

q-bio.QM20152 cited

Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

Natalia Y. Bilenko, Jack L. Gallant

Canonical correlation analysis (CCA) is a valuable method for interpreting cross-covariance across related datasets of different dimensionality. There are many potential applicatio…