Nick Souter
@nicksouter.bsky.social
Postdoctoral Research Fellow at University of Sussex, studying ways of measuring the carbon footprint of fMRI data preprocessing and analysis 🌱🧠
And another thank you to the whole @bhdonostia.bsky.social organising team for inviting me to speak about the carbon footprint of neuroimaging computing!
(I think the subtitles shown on the screen here were from people all over the room, not me just mumbling incoherently)
(I think the subtitles shown on the screen here were from people all over the room, not me just mumbling incoherently)
November 22, 2025 at 11:12 AM
And another thank you to the whole @bhdonostia.bsky.social organising team for inviting me to speak about the carbon footprint of neuroimaging computing!
(I think the subtitles shown on the screen here were from people all over the room, not me just mumbling incoherently)
(I think the subtitles shown on the screen here were from people all over the room, not me just mumbling incoherently)
A massive thank you to the team who actually did the hard work of putting this together:
MONIKA UTROSA
CLÉMENTINE LÉVY-FIDEL
FÁBIO LOBATO
GABRIEL PIŠVEJC
Everything we developed is available open source on GitHub: github.com/NickESouter/...
MONIKA UTROSA
CLÉMENTINE LÉVY-FIDEL
FÁBIO LOBATO
GABRIEL PIŠVEJC
Everything we developed is available open source on GitHub: github.com/NickESouter/...
November 22, 2025 at 11:12 AM
A massive thank you to the team who actually did the hard work of putting this together:
MONIKA UTROSA
CLÉMENTINE LÉVY-FIDEL
FÁBIO LOBATO
GABRIEL PIŠVEJC
Everything we developed is available open source on GitHub: github.com/NickESouter/...
MONIKA UTROSA
CLÉMENTINE LÉVY-FIDEL
FÁBIO LOBATO
GABRIEL PIŠVEJC
Everything we developed is available open source on GitHub: github.com/NickESouter/...
This week I attended my first ever hackathon with @bhdonostia.bsky.social! We put together a functioning dashboard to estimate the carbon footprint of MRI data collection 🧠
You can access the neuro-impact-calculator here: nicksouter.shinyapps.io/neuro-impact...
(Not yet optimised for phones) 🧵
You can access the neuro-impact-calculator here: nicksouter.shinyapps.io/neuro-impact...
(Not yet optimised for phones) 🧵
November 22, 2025 at 11:12 AM
This week I attended my first ever hackathon with @bhdonostia.bsky.social! We put together a functioning dashboard to estimate the carbon footprint of MRI data collection 🧠
You can access the neuro-impact-calculator here: nicksouter.shinyapps.io/neuro-impact...
(Not yet optimised for phones) 🧵
You can access the neuro-impact-calculator here: nicksouter.shinyapps.io/neuro-impact...
(Not yet optimised for phones) 🧵
9. Use existing data
Running analysis on previously collected and preprocessed data is a great way to test hypotheses without using additional energy to preprocess it yourself. We provide a table describing different open access datasets.
Running analysis on previously collected and preprocessed data is a great way to test hypotheses without using additional energy to preprocess it yourself. We provide a table describing different open access datasets.
February 8, 2024 at 10:56 AM
9. Use existing data
Running analysis on previously collected and preprocessed data is a great way to test hypotheses without using additional energy to preprocess it yourself. We provide a table describing different open access datasets.
Running analysis on previously collected and preprocessed data is a great way to test hypotheses without using additional energy to preprocess it yourself. We provide a table describing different open access datasets.
5. Tidy up "junk" files
Energy is needed to store and backup data. you can reduce your footprint by deleting files you don't need. For #fMRIPrep, junk files make up to 96% of total size.
Our tool fMRIPrepCleanup, automatically finds/removes this data: github.com/NickESouter/...
Energy is needed to store and backup data. you can reduce your footprint by deleting files you don't need. For #fMRIPrep, junk files make up to 96% of total size.
Our tool fMRIPrepCleanup, automatically finds/removes this data: github.com/NickESouter/...
February 8, 2024 at 10:54 AM
5. Tidy up "junk" files
Energy is needed to store and backup data. you can reduce your footprint by deleting files you don't need. For #fMRIPrep, junk files make up to 96% of total size.
Our tool fMRIPrepCleanup, automatically finds/removes this data: github.com/NickESouter/...
Energy is needed to store and backup data. you can reduce your footprint by deleting files you don't need. For #fMRIPrep, junk files make up to 96% of total size.
Our tool fMRIPrepCleanup, automatically finds/removes this data: github.com/NickESouter/...
4b. Time and location matter
You can also consider choosing cloud computing services based in countries/regions with lower average carbon intensity.
2022 data for countries and US states ⬇️
You can also consider choosing cloud computing services based in countries/regions with lower average carbon intensity.
2022 data for countries and US states ⬇️
February 8, 2024 at 10:53 AM
4b. Time and location matter
You can also consider choosing cloud computing services based in countries/regions with lower average carbon intensity.
2022 data for countries and US states ⬇️
You can also consider choosing cloud computing services based in countries/regions with lower average carbon intensity.
2022 data for countries and US states ⬇️
4a. Time and location matter
The carbon intensity of electricity peaks at busy times and drops overnight and at the weekend. By scheduling preprocessing/analysis to run at low intensity times, you can use the same amount of energy while emitting less carbon.
Data for the UK ⬇️
The carbon intensity of electricity peaks at busy times and drops overnight and at the weekend. By scheduling preprocessing/analysis to run at low intensity times, you can use the same amount of energy while emitting less carbon.
Data for the UK ⬇️
February 8, 2024 at 10:53 AM
4a. Time and location matter
The carbon intensity of electricity peaks at busy times and drops overnight and at the weekend. By scheduling preprocessing/analysis to run at low intensity times, you can use the same amount of energy while emitting less carbon.
Data for the UK ⬇️
The carbon intensity of electricity peaks at busy times and drops overnight and at the weekend. By scheduling preprocessing/analysis to run at low intensity times, you can use the same amount of energy while emitting less carbon.
Data for the UK ⬇️
Last week we ran the first 'Environmental impacts of computing (EIC) in health & life sciences research' workshop, at the Wellcome Trust in London 🌱 🖥️
You can now find recordings of all our spreakers on YouTube!
www.youtube.com/playlist?lis...
We discussed a number of topics... 🧵
You can now find recordings of all our spreakers on YouTube!
www.youtube.com/playlist?lis...
We discussed a number of topics... 🧵
November 17, 2023 at 2:27 PM
Last week we ran the first 'Environmental impacts of computing (EIC) in health & life sciences research' workshop, at the Wellcome Trust in London 🌱 🖥️
You can now find recordings of all our spreakers on YouTube!
www.youtube.com/playlist?lis...
We discussed a number of topics... 🧵
You can now find recordings of all our spreakers on YouTube!
www.youtube.com/playlist?lis...
We discussed a number of topics... 🧵
On November 7th, we're hosting the first 'Environmental impacts of computing in health & life sciences research' workshop, at the Wellcome Trust in London!
eicworkshop.info
Come along to learn more about the carbon footprint of your research computing, and how it can be reduced 🌱
eicworkshop.info
Come along to learn more about the carbon footprint of your research computing, and how it can be reduced 🌱
October 5, 2023 at 11:07 AM
On November 7th, we're hosting the first 'Environmental impacts of computing in health & life sciences research' workshop, at the Wellcome Trust in London!
eicworkshop.info
Come along to learn more about the carbon footprint of your research computing, and how it can be reduced 🌱
eicworkshop.info
Come along to learn more about the carbon footprint of your research computing, and how it can be reduced 🌱
Here's the preprint for my final PhD paper, and my first fMRI study! 🧠
We found that dissociable default mode network (DMN) subnetworks support retrieval of contextual and emotional associations, seperately from processing of retrieval demands
www.biorxiv.org/content/10.1...
We found that dissociable default mode network (DMN) subnetworks support retrieval of contextual and emotional associations, seperately from processing of retrieval demands
www.biorxiv.org/content/10.1...
October 3, 2023 at 10:40 AM
Here's the preprint for my final PhD paper, and my first fMRI study! 🧠
We found that dissociable default mode network (DMN) subnetworks support retrieval of contextual and emotional associations, seperately from processing of retrieval demands
www.biorxiv.org/content/10.1...
We found that dissociable default mode network (DMN) subnetworks support retrieval of contextual and emotional associations, seperately from processing of retrieval demands
www.biorxiv.org/content/10.1...