James Haxby

Co-Director of the Center for Open Neuroscience at Dartmouth College. Formerly directed Dartmouth Brain Imaging Center and Center for Cognitive Neuroscience. Recognized for developing and disseminating open research methodologies and influential datasets.

Contributions

Projects

HeuDiConv

Publications

A Common, High-Dimensional Model of the Representational Space in Human Ventral Temporal Cortex
A Model of Representational Spaces in Human Cortex
Attention alters animal and action representation in highly-distributed functionally-defined cortical parcels
Attention locally modulates the discriminability of high-level, task-relevant representations
Attention selectively reshapes the geometry of distributed semantic representation
Attention selectively reshapes the geometry of distributed semantic representation
Attentional allocation locally warps representational space
Behaviorally-relevant features of observed actions dominate cortical representational geometry in natural vision
Clustering cortical searchlights based on shared representational geometry
DataLad: distributed system for joint management of code, data, and their relationship
Decoding the neural representation of observed social and nonsocial human actions
Finding cortical patches of shared representations: a comparison of clustering algorithms on representational geometries, and the effect of cross-validation to reduce physiological noise
How the human brain represents perceived dangerousness or "predacity" of animals
Improving efficiency in cognitive neuroscience research with NeuroDebian
Investigation of the familiar face recognition model
Localizing functional regions of interest based on responses to dynamic naturalistic stimuli
Pattern classification precedes region-average hemodynamic response in early visual cortex.
PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data
PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data
Representation of biological classes in the human brain
ReproIn: automatic generation of shareable, version-controlled BIDS datasets from MR scanners
Scanning parameters for optimal decoding using a 32-channel head coil for fMRI
Statistical learning analysis in neuroscience: aiming for transparency
The animacy continuum in the human ventral vision pathway
The Individualized Neural Tuning Model: Precise and generalizable cartography of functional architecture in individual brains
The Individualized Neural Tuning Model: Precise and generalizable cartography of functional architecture in individual brains
Transmodal Analysis of Neural Signals