BrainIAK: The Brain Imaging Analysis Kit

• DOI: 10.31219/osf.io/db2ev
• Publication Date: 2020-12-09T22:45:33Z
• Authors: Manoj Kumar; Michael Anderson; James Antony; Christopher Balda...; Paula Pacheco Brooks; Ming Bo Cai; Po-Hsuan Cameron ...; Cameron Thomas Ellis; Gregory Henselman...; David Huberdeau; J. Benjamin Hutch...; Y. Peeta Li; Qihong Lu; Jeremy R. Manning; Anne C. Mennen; Samuel A. Nastase; Hugo Richard; Anna C. Schapiro; Nicolas W Schuck; Michael Shvartsman; Narayanan Sundaram; Daniel Suo; Javier S. Turek; David Turner; Vy Vo; Grant Wallace; Yida Wang; Jamal A. Williams; Hejia Zhang; Xia Zhu; Mihai Capota; Jonathan D. Cohen; Uri Hasson; Kai Li; Peter J. Ramadge; Nicholas Turk-Browne; Theodore L. Willke; Kenneth A. Norman
• Keywords: Python; Leverage (statistics); Laptop

Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis cognition. Here, we describe Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally-optimized solutions to key problems in advanced fMRI analysis. A variety techniques are presently included BrainIAK: intersubject correlation (ISC) and functional connectivity (ISFC), alignment via shared response model (SRM), full matrix analysis (FCMA), Bayesian version representational similarity (BRSA), event segmentation using hidden Markov models, topographic factor (TFA), inverted encoding models (IEM), simulator uses noise characteristics from real (fmrisim), some emerging methods. These have been optimized leverage efficiencies high performance compute (HPC) clusters, same code can be seamlessly transferred laptop cluster. For each aforementioned techniques, problem technique is meant solve, how it solves problem; also include example Jupyter notebook annotated bibliography papers used and/or described technique. In addition sections describing various BrainIAK, future applications BrainIAK real-time fMRI, tutorials developed online facilitate learning computational innovations contribute BrainIAK. We hope this manuscript helps readers understand might useful their research.