RERUN
Claim 24

Does the brain's wiring predict where Parkinson's spreads?

Authors' own code

The study said the brain's wiring predicts where Parkinson's-like damage spreads in mice. The Lab retraced it: ✓ same result.

Whose code is this?

Henderson and colleagues' own R code, run on their published data with packages from the date of the code. It's a settled showcase, so there was no forecasting. The same result also came from an independent rebuild (claim 21).

See the code

If the brain's wiring predicts where Parkinson's spreads, it gives researchers a map of what to protect.

Cited by 302 studies

What this result means

We test one thing: does this code and data give this number? That's not the same as the science being right. The forecast price never changes the verdict.

See the proof
0.696match score, where 1 is perfect, the paper says. Counts if between 0.691 and 0.701.
Where the number comes fromPearson's r 0.696 (Henderson et al.)Table 2 of the ReScience C article, which quotes the original paper

The exact claim as posted

Authors' own code: brain-wiring model predicts spread of Parkinson's-linked protein in mice, r = 0.696

Henderson et al. (Nature Neuroscience, 2019) modelled how alpha-synuclein, the protein linked to Parkinson's disease, spreads along the mouse brain's wiring. They report that the model's predictions match lab measurements with a correlation of 0.696 at 3 months. This re-runs the authors' own R code on their published data, with packages from the code's date. It's a settled showcase, not a forecast.

RERUNCLAIM #0024

Does the brain's wiring predict where Parkinson's spreads?

Measured in
match score, where 1 is perfect
Paper says
0.696
Counts if
0.691 to 0.701
Lab got
0.69605221
VerdictNumbers check out
53d87974c67eef800814Nov 05, 2026

This result is final

Paper said 0.696. We got 0.69605221.

The code and data produced the same result. That doesn't prove the study's method is right.

This slip is the Lab's .

✓ Verified on NEAR. See the contract's history

See the full receipt

  1. People forecast
  2. Forecasting ends
  3. The Lab retraces it
  4. Verdict posted, open to challenge
  5. Winners collect

What we didn't check

  • Whether the sample was fair or large enough.
  • Whether test data leaked into training or tuning.
  • Whether the result holds on new data.
  • Whether the study's method was the right one for its question.
  • Whether results in mice carry over to people.

No forecasting on this claim. It was posted with the result already known.

The evidence

See the full receipt

How much evidence is behind this?

Each step is a tougher test. Only the first one decides who wins the market.

  1. 1. ✓

    The Lab's retrace of the code and data named in the claim

    The Lab retraced the code and data and got a number inside the claim's range. YES wins.

  2. 2. –

    Stress test: does the number depend on luck?

    Fetching the extra runs…

  3. 3. –

    Rebuilt from the description (experimental)

    Fetching the AI's rebuild…

Coming next: a data-leakage check, for the same rows in training and test data, and a maths check on the statistics a paper reports. Neither has run on this claim.

Even all three steps can't prove the science is true. They show how well this result stands up to checking.

Verified

Your browser just re-checked these itself, so you don't have to trust this site.

Checking…

What the Lab retraces

Source
https://doi.org/10.1038/s41593-019-0457-5
M. X. Henderson, E. J. Cornblath, et al., MIT
Code, at this exact version
https://github.com/ejcorn/connectome_diffusion
commit b967d0851f66073a0bfe25d39374466639b9685f
Commands
r4.4
$ mkdir -p /work/.rlib
$ Rscript --vanilla -e "install.packages(c('R.matlab','RColorBrewer','cowplot','expm','ggplot2','lm.beta','stringr','viridis'), lib='/work/.rlib', repos='https://packagemanager.posit.co/cran/2020-02-28', Ncpus=2)"
$ Rscript --vanilla -e "params<-list(basedir='./',opdir='out/',grps='NTG');source('code/packages.R');source('code/process/process_pathconn.R');source('code/process/getLout.R');grp<-'NTG';source('code/diffmodel/analyzespread.R');cat('r3',format(r.SC[2],digits=8),'\n')" > rerun_output.txt
Where the result is read
rerun_output.txt using regex r3 ([0-9.]+)
Data files
None
Limits
2 CPU, 4 GB, 15 minutes
53d87974c67eef8008149ef40f0448812042bff87db91a0683551e921a3b2e75
Show the claim exactly as stored on the blockchain
{"artifact":{"commit":"b967d0851f66073a0bfe25d39374466639b9685f","data":[],"entrypoint":"Rscript --vanilla -e \"params<-list(basedir='./',opdir='out/',grps='NTG');source('code/packages.R');source('code/process/process_pathconn.R');source('code/process/getLout.R');grp<-'NTG';source('code/diffmodel/analyzespread.R');cat('r3',format(r.SC[2],digits=8),'\\n')\" > rerun_output.txt","output":{"extractor":{"expr":"r3 ([0-9.]+)","type":"regex"},"path":"rerun_output.txt"},"repo_url":"https://github.com/ejcorn/connectome_diffusion","runtime":"r4.4","setup":["mkdir -p /work/.rlib","Rscript --vanilla -e \"install.packages(c('R.matlab','RColorBrewer','cowplot','expm','ggplot2','lm.beta','stringr','viridis'), lib='/work/.rlib', repos='https://packagemanager.posit.co/cran/2020-02-28', Ncpus=2)\""]},"metric":{"comparison":"within_tolerance","name":"correlation between predicted and measured pathology at 3 months","reported_value":"0.696","tolerance":{"type":"abs","value":"0.005"}},"private_data":null,"resources":{"cpu":2,"max_minutes":15,"mem_gb":4},"source":{"authors":"M. X. Henderson, E. J. Cornblath, et al.","doi":"10.1038/s41593-019-0457-5","license":"MIT","type":"paper","url":"https://doi.org/10.1038/s41593-019-0457-5"},"statement":"Henderson et al. (Nature Neuroscience, 2019) modelled how alpha-synuclein, the protein linked to Parkinson's disease, spreads along the mouse brain's wiring. They report that the model's predictions match lab measurements with a correlation of 0.696 at 3 months. This re-runs the authors' own R code on their published data, with packages from the code's date. It's a settled showcase, not a forecast.","title":"Authors' own code: brain-wiring model predicts spread of Parkinson's-linked protein in mice, r = 0.696","version":1}

Community notes

Notes are people's own words, kept on the blockchain. They never change a verdict, and the Lab's AI never reads them. Posting costs a little NEAR for storage, and what isn't used comes back.