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We're very excited to announce our new user-friendly Jupyter notebook BrainIAK tutorials for advanced fMRI data analysis in Python, which can be freely downloaded or run on the cloud.</div>

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software: <a href="https://brainiak.org/tutorials/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://brainiak.org/tutorials/&source=gmail&ust=1558555668448000&usg=AFQjCNHAo9jXunBbN4dkW8i4Lss84ukDow" style="color: rgb(17, 85, 204);" class="">https://brainiak.<wbr class="">org/tutorials/</a></div>

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preprint: <a href="https://osf.io/j4sbc/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://osf.io/j4sbc/&source=gmail&ust=1558555668448000&usg=AFQjCNETgr3Tn_eSqJ8ZRm8CU-htOODYIw" style="color: rgb(17, 85, 204);" class="">https://osf.io/<wbr class="">j4sbc/</a></div>

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Techniques covered include MVPA, RSA, searchlight, functional connectivity, inter-subject correlation, shared response modeling, event segmentation using HMMs, and real-time fMRI.</div>

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This work was led by Manoj Kumar and Cameron Ellis in collaboration with the Brain-Inspired Computing Lab at Intel, based on courses taught by Nick Turk-Browne at Yale and Ken Norman and Peter Ramadge at Princeton. </div>

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