{"action":"created","issue":{"url":"https://api.github.com/repos/brainiak/brainiak/issues/384","repository_url":"https://api.github.com/repos/brainiak/brainiak","labels_url":"https://api.github.com/repos/brainiak/brainiak/issues/384/labels{/name}","comments_url":"https://api.github.com/repos/brainiak/brainiak/issues/384/comments","events_url":"https://api.github.com/repos/brainiak/brainiak/issues/384/events","html_url":"https://github.com/brainiak/brainiak/pull/384","id":366580867,"node_id":"MDExOlB1bGxSZXF1ZXN0MjIwMjE5NTYy","number":384,"title":"WIP: Revamped ISC analyses with additional statistical tests","user":{"login":"snastase","id":3496566,"node_id":"MDQ6VXNlcjM0OTY1NjY=","avatar_url":"https://avatars2.githubusercontent.com/u/3496566?v=4","gravatar_id":"","url":"https://api.github.com/users/snastase","html_url":"https://github.com/snastase","followers_url":"https://api.github.com/users/snastase/followers","following_url":"https://api.github.com/users/snastase/following{/other_user}","gists_url":"https://api.github.com/users/snastase/gists{/gist_id}","starred_url":"https://api.github.com/users/snastase/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/snastase/subscriptions","organizations_url":"https://api.github.com/users/snastase/orgs","repos_url":"https://api.github.com/users/snastase/repos","events_url":"https://api.github.com/users/snastase/events{/privacy}","received_events_url":"https://api.github.com/users/snastase/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":14,"created_at":"2018-10-04T00:41:55Z","updated_at":"2018-10-22T03:46:32Z","closed_at":null,"author_association":"NONE","pull_request":{"url":"https://api.github.com/repos/brainiak/brainiak/pulls/384","html_url":"https://github.com/brainiak/brainiak/pull/384","diff_url":"https://github.com/brainiak/brainiak/pull/384.diff","patch_url":"https://github.com/brainiak/brainiak/pull/384.patch"},"body":"I'm re-working and expanding the ISC (and ISFC) code to accommodate several new features. We can now compute either pairwise or leave-one-out ISCs (rather than just leave-one-out). All analyses now also accept 'mean' or 'median' as summary statistics. I've increased the flexibility of inputs to the core ISC functions, and tried to standardize output geometries (time points by voxels). I've moved statistical tests out of the core ISC and ISFC functions—these are now separate functions. In addition to phase randomization, I've added a circular time-shifting test (Kauppi et al., 2014), and group-level permutation and bootstrap tests (Chen et al., 2016). Both the phase randomization and circular time-shift randomization tests operate on the data themselves and call the core ISC function internally to recompute ISCs on the randomized data. Two changes to the phase randomization code: no more randomization across voxels (as this disrupts the spatial autocorrelation of fMRI data), and in the leave-one-out approach, only the left-out subject is phase randomized per iteration. If all subjects are randomized, then N-1 are averaged, the Nth subject will always be correlated with what is effectively a flat time series, yielding an overly tight null distribution and inflated false positive rates (FPRs). Group-level bootstrap and permutation tests operate directly on the ISC values and should better control FPRs (Chen et al., 2016). For pairwise ISCs, bootstrap resampling of subjects and group relabeling operate at the row/column level, not at the level of individual pairs (therefore respecting the correlation structure among pairs). Updated and expanded tests. No statistical tests for ISFC yet, but working on it. I would also recommend changing the module/filename from \"isfc.py\" to \"isc.py\", despite the ISC values being a subset of the ISC values, I think ISC is conceptually superordinate and we may want to add things like spatial ISC in the future (which does not fit under the ISFC heading). NB: This is my first major PR, so apologies if I'm missing anything obvious."},"comment":{"url":"https://api.github.com/repos/brainiak/brainiak/issues/comments/431735404","html_url":"https://github.com/brainiak/brainiak/pull/384#issuecomment-431735404","issue_url":"https://api.github.com/repos/brainiak/brainiak/issues/384","id":431735404,"node_id":"MDEyOklzc3VlQ29tbWVudDQzMTczNTQwNA==","user":{"login":"qihongl","id":7212521,"node_id":"MDQ6VXNlcjcyMTI1MjE=","avatar_url":"https://avatars3.githubusercontent.com/u/7212521?v=4","gravatar_id":"","url":"https://api.github.com/users/qihongl","html_url":"https://github.com/qihongl","followers_url":"https://api.github.com/users/qihongl/followers","following_url":"https://api.github.com/users/qihongl/following{/other_user}","gists_url":"https://api.github.com/users/qihongl/gists{/gist_id}","starred_url":"https://api.github.com/users/qihongl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/qihongl/subscriptions","organizations_url":"https://api.github.com/users/qihongl/orgs","repos_url":"https://api.github.com/users/qihongl/repos","events_url":"https://api.github.com/users/qihongl/events{/privacy}","received_events_url":"https://api.github.com/users/qihongl/received_events","type":"User","site_admin":false},"created_at":"2018-10-22T03:46:32Z","updated_at":"2018-10-22T03:46:32Z","author_association":"MEMBER","body":"ah and for line 612: \r\n\r\n`n_groups ` is referred before assignment. Consider replacing `n_groups` as `np.unique(group_assignment)`? "}}
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