Oscar Esteban (@oesteban) — Bluesky Profile

1 month ago

You can joke about Pam Bondi’s ridiculous unprofessionalism all you want, but I’m deeply shocked by it: She acts as if she fears absolutely no consequences, convinced that there will be no more political power transfers. — This should shake everyone to their core.

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2 months ago

@russpoldrack.org convincing you to prefer zarr over HDF5 in about 10 lines of code. Thanks Russ!

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2 months ago

👏Footage from London shows the moment activists removed the Islamic Republic’s flag from the Iranian embassy balcony and raised the Lion and Sun flag instead.

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2 months ago

Note: The link currently leads to a 404 error.

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3 months ago

It is newsworthy that the president of the United States is increasingly verbally abusive of women reporters and he should be asked about it.

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3 months ago

This may not be a signal of a dysfunctional administration (and supporting GOP). It's clear this second time things are even more dysfunctional than the first. That said, this may be a signal of divergent factions (openly totalitarian vs. barely democratic). Trump is moving forward.

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4 months ago

Congrats to @oesteban.bsky.social @markiewicz.bsky.social and the rest of the team!

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10 months ago

An example of T1w image before and after defacing. Defacing is typically implemented by zeroing the voxels around the face (left-hand side, panel “T1-weighted”). The “Background noise” panel shows two visualizations extracted from the MRIQC visual report, in which a window is applied to select the lowest intensities and then they are inverted to enhance patterns in the background. The red arrows indicate aliases along the anterior–posterior axis—which had the lowest bandwidth in the example—produced by eye motion. These aliases are straightforward to notice in front of the ocular globes in the “Background noise” panel of the “nondefaced” image because of the absence of signal sources. This aliasing also spreads in the opposite direction, overlapping brain tissue. However, this overlap is often very hard to notice against the signal of interest within the brain. The corresponding “defaced” version of the “Background noise” panel shows how defacing eliminates valuable information for quality assessment.

To protect an individual's #privacy, facial features are removed before data-sharing of human #neuroimaging data. @oesteban.bsky.social &co show that this procedure affects the quality ratings given by human raters but not automated image quality metrics @plosbiology.org 🧪 plos.io/3Gtr3lo

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1 year ago

Methods for analyzing large neuroimaging datasets A fully open-access book with a truly practical guide to analyzing large neuroimaging datasets. Get the book: https://link.springer.com/book/10.1007/978-1-0716-4260-3 Hosted on the Open Science...

Should also mention: associated OSF resource osf.io/d9r3x/ with links to code & demo videos. Again, huge tks to contributors incl. @oesteban.bsky.social @amarquand.bsky.social @engra.me @clarekelly.bsky.social @jivr.bsky.social @christiangaser.bsky.social

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