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Yaroslav O. Halchenko

Researcher at Dartmouth College

Publications -  127
Citations -  9310

Yaroslav O. Halchenko is an academic researcher from Dartmouth College. The author has contributed to research in topics: Computer science & Neuroimaging. The author has an hindex of 30, co-authored 113 publications receiving 6275 citations. Previous affiliations of Yaroslav O. Halchenko include Karolinska Institutet & New Jersey Institute of Technology.

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Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python

TL;DR: Nipype solves issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows, and provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, and reduces the learning Curve.

seaborn: Statistical data visualization

TL;DR: Seaborn as discussed by the authors is a library for making statistical graphics in Python that provides a high-level interface to matplotlib and integrates closely with pandas data structures, which makes it easy to translate questions about data into graphics that can answer them.
Journal ArticleDOI

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

TL;DR: The Brain Imaging Data Structure (BIDS) is developed, a standard for organizing and describing MRI datasets that uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
Journal ArticleDOI

A common, high-dimensional model of the representational space in human ventral temporal cortex.

TL;DR: A high-dimensional model of the representational space in human ventral temporal (VT) cortex in which dimensions are response-tuning functions that are common across individuals and patterns of response are modeled as weighted sums of basis patterns associated with these response tunings is presented.