78 citations · 130 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
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…
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…
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pulkit Agrawal, Dustin Stansbury, Jitendra Malik +1
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 n…