Mark Histed

Neuroscience, information processing, recurrent networks, brain stimulation, causality.
PI@NIH (pers opinions here only).
Prev: NEPA @MIT @UChicago
#ScienceMastodon #science #neuroscience

publications: https://markhisted.org/publications
Linktree: https://linktr.ee/markhisted

Last Notes

2026-05-06 21:04:24 UTC

- reply

So we choose a reasonable rigor std, do our best to peer review, & accept some errors, worked out by followup work.
(There are many issues w/ glam journals, over-selling, favoring huge labs—etc. But this 'some are wrong' issue is just the nature of reality.) /end

2026-05-06 21:04:19 UTC

- reply

This framework is well-worked out in theory—we must choose an error criterion ("wrong"), which comes w/ a cost in time/$.
This isn't ex it (need a cost term), bt same idea, fm David Heeger's notes.
Type 1/2 errors, sensitivity/specificity: same idea.
https://www.cns.nyu.edu/~david/handouts/sdt/sdt.html
https://fediscience.org/system/media_attachments/files/116/529/657/235/270/666/original/5c5c14adf5308acb.png

2026-05-06 21:04:13 UTC

- reply

Why not a bad thing?
Because these journals by def'n are publishing exciting, novel, possibly field-changing work.
You do NOT want to further encumber that work—CNS papers are far too long already—with a sky-high rigor standard. Or you will get rigor mortis of science.
3/

2026-05-06 21:04:08 UTC

- reply

Every scientific mentor I know, including me, tells all our first-year grad students this.
It's widely known inside science.
2/

2026-05-06 21:04:02 UTC

A good number of papers in Science and Nature are wrong...
and that's not a bad thing.
(What's something everyone in your field knows but people outside the field don't?)
1/

2025-12-27 20:03:21 UTC

Learned this week that both of my siblings live in Sears kit houses. They were solidly built - still in very good shape.

2025-11-15 16:04:03 UTC

Seen on DC Metro
🙄
https://fediscience.org/system/media_attachments/files/115/554/559/143/732/895/original/6d35ec93c2a48890.jpeg

2025-05-15 21:02:14 UTC

Despite some ups and downs at NIH, we do have an open position for a postbac and are considering candidates.
Our work is at the intersection of neuroscience and AI, and we aim to understand how the brain's densely connected recurrent networks operate. 🧪