Slide 1

Slide 1 text

Ivan ([email protected]) Papers We Love #022 Aug 29, 2016 http://www.pnas.org/content/early/2016/06/27/1602413113.full

Slide 2

Slide 2 text

No content

Slide 3

Slide 3 text

f?

Slide 4

Slide 4 text

No content

Slide 5

Slide 5 text

the most common software packages for fMRI analysis … can result in false-positive rates of up to 70%. These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results. a bug that's been sitting in a package for 15 years, fixed in May 2015, produced bad results. “ “

Slide 6

Slide 6 text

randcraw says: …For a couple years now philosophers have insisted that fMRI images prove there is no such thing as free will. pfooti says: The dead salmon study seems relevant here in discussion of how fMRI is used. “ “

Slide 7

Slide 7 text

honkhonkpants says: Doesn't sound like a straight up bug, but rather unsound statistical methods which can happen with or without software… greenyoda replies: I'd say it's a bug, since the unsound statistical methods are incorporated into the three most common software packages… “ “

Slide 8

Slide 8 text

No content

Slide 9

Slide 9 text

MAGNETIC RESONANCE IMAGING (MRI)

Slide 10

Slide 10 text

“FMRI SCANNER” MRI + STIMULATION + RESPONSE by James Dankert, http://slideplayer.com/slide/6939789/

Slide 11

Slide 11 text

MR IMAGES: ANATOMY

Slide 12

Slide 12 text

MR IMAGES: PHYSIOLOGY functional MRI diffusion MRI (Dr. Rose, UQCCR) perfusion MRI

Slide 13

Slide 13 text

FMRI 101 rest (normal condition) increased activity (stimulus) Blood Oxygenation Level Dependent (BOLD) effect brain activity -> local increase on blood flow -> [oxy/deoxy hemoglobin] -> MR signal change (1-5%)

Slide 14

Slide 14 text

No content

Slide 15

Slide 15 text

FMRI 101 EPI acquisition (brain volume) 10 to 15 slices, ~5mm each 64x64 to 128x128 in-plane res. (2 to 4mm) ~50 to 100K voxels/volume 100 to 200 volumes every 2 to 3 seconds Data Acquisition

Slide 16

Slide 16 text

FMRI 101 Data Analysis 1. Pre processing: motion correction, slice-timing, (spatial smoothing) 2. Statistical analysis: t-test, correlation, OLS, PCA, ICA, … 3. Visualization

Slide 17

Slide 17 text

No content

Slide 18

Slide 18 text

METHODS • Resting state fMRI date from 499 subjects • 4 simulated activation conditions (2 block-, 2 event-related) • 4 levels of spatial smoothing • one- or two-sample t-test • voxel or cluster level inference

Slide 19

Slide 19 text

RESULTS Fig.1. Results for one-sample t test, showing estimated FWE rates

Slide 20

Slide 20 text

RESULTS Fig. 2. Results for two-sample t test and ad hoc cluster-wise inference, showing estimated FWE rates for 6 mm of smoothing

Slide 21

Slide 21 text

No content

Slide 22

Slide 22 text

WHAT DOES IT MEAN? • Is all of fMRI junk science? NO • Is it a software bug? NO (AFNI’s 3dClustSim was a minor issue) • What about “philosophical/political” fMRI studies? ??? (read with a big grain of salt) • What about the “Salmon study”? GOOD STORY for STATS 102 (multiple comparisons)

Slide 23

Slide 23 text

http://blogs.discovermagazine.com/neuroskeptic/2016/07/07/false-positive-fmri-mainstream/ http://blogs.warwick.ac.uk/nichols/entry/bibliometrics_of_cluster/

Slide 24

Slide 24 text

time Hemodynamic Response Function OPEN DATA jballanc says: The real takeaway lesson from this research should be the vital importance of Open Data to the modern scientific enterprise “ adapted from https://xkcd.com/54/