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/...
So, a CALL TO ACTION:
Are you currently in an institution where the energy usage of various MRI sequences is already being recorded? Are you in a position to start doing this? Please get in touch! We’d love to source some more representative input data and understand which factors matter most
Are you currently in an institution where the energy usage of various MRI sequences is already being recorded? Are you in a position to start doing this? Please get in touch! We’d love to source some more representative input data and understand which factors matter most
November 22, 2025 at 11:12 AM
So, a CALL TO ACTION:
Are you currently in an institution where the energy usage of various MRI sequences is already being recorded? Are you in a position to start doing this? Please get in touch! We’d love to source some more representative input data and understand which factors matter most
Are you currently in an institution where the energy usage of various MRI sequences is already being recorded? Are you in a position to start doing this? Please get in touch! We’d love to source some more representative input data and understand which factors matter most
A caveat, we’ve taken energy consumption metrics from specifications provided by scanner manufacturers. The numbers generated as output seem to be a pretty big underestimation of the impact we’d expect from fMRI research scanning. The numbers are probably more relevant to clinical scanning…
November 22, 2025 at 11:12 AM
A caveat, we’ve taken energy consumption metrics from specifications provided by scanner manufacturers. The numbers generated as output seem to be a pretty big underestimation of the impact we’d expect from fMRI research scanning. The numbers are probably more relevant to clinical scanning…
The tool takes input information including:
🟢 Field strength
🟢 Scanner model
🟢 Country in which data was collected
🟢 Year of data collection
🟢 Sample size
From this, it generates an environmental impact statement which can be popped into a grant application or journal paper
🟢 Field strength
🟢 Scanner model
🟢 Country in which data was collected
🟢 Year of data collection
🟢 Sample size
From this, it generates an environmental impact statement which can be popped into a grant application or journal paper
November 22, 2025 at 11:12 AM
The tool takes input information including:
🟢 Field strength
🟢 Scanner model
🟢 Country in which data was collected
🟢 Year of data collection
🟢 Sample size
From this, it generates an environmental impact statement which can be popped into a grant application or journal paper
🟢 Field strength
🟢 Scanner model
🟢 Country in which data was collected
🟢 Year of data collection
🟢 Sample size
From this, it generates an environmental impact statement which can be popped into a grant application or journal paper
Big thanks to @loiclnlg.bsky.social, Gabby Samuel, Chris Racey, @lincoln81.bsky.social, Nikhil Bhagwat, Raghav Selvan, and Charlotte Rae for all their work on this paper!
February 8, 2024 at 10:59 AM
Big thanks to @loiclnlg.bsky.social, Gabby Samuel, Chris Racey, @lincoln81.bsky.social, Nikhil Bhagwat, Raghav Selvan, and Charlotte Rae for all their work on this paper!
10. Talk about greener computing
Discussing the carbon footprint of data processing within your neuroimaging community will make it easier to think seriously about this issue. This will help in embedding sustainable ideas into standard practice 🌱
Discussing the carbon footprint of data processing within your neuroimaging community will make it easier to think seriously about this issue. This will help in embedding sustainable ideas into standard practice 🌱
February 8, 2024 at 10:57 AM
10. Talk about greener computing
Discussing the carbon footprint of data processing within your neuroimaging community will make it easier to think seriously about this issue. This will help in embedding sustainable ideas into standard practice 🌱
Discussing the carbon footprint of data processing within your neuroimaging community will make it easier to think seriously about this issue. This will help in embedding sustainable ideas into standard practice 🌱
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.
8. Reflect on what needs to be shared
It's good practice to share all raw neuroimaging data on platforms like OpenNeuro. But this storage still has a carbon footprint. Consider whether just sharing preprocessed files would be enough to allow others to make use of your data.
It's good practice to share all raw neuroimaging data on platforms like OpenNeuro. But this storage still has a carbon footprint. Consider whether just sharing preprocessed files would be enough to allow others to make use of your data.
February 8, 2024 at 10:56 AM
8. Reflect on what needs to be shared
It's good practice to share all raw neuroimaging data on platforms like OpenNeuro. But this storage still has a carbon footprint. Consider whether just sharing preprocessed files would be enough to allow others to make use of your data.
It's good practice to share all raw neuroimaging data on platforms like OpenNeuro. But this storage still has a carbon footprint. Consider whether just sharing preprocessed files would be enough to allow others to make use of your data.
7. Push for publicly owned centralised data storage
Large centralised data centres tend to be more efficient, but this often means relying on big tech comapnies to host data. Alternatives like EuropHPC JU may allow storage that is efficient & sustainable:
eurohpc-ju.europa.eu/index_en
Large centralised data centres tend to be more efficient, but this often means relying on big tech comapnies to host data. Alternatives like EuropHPC JU may allow storage that is efficient & sustainable:
eurohpc-ju.europa.eu/index_en
Homepage
The European High Performance Computing Joint Undertaking (EuroHPC JU) is a joint initiative between the EU, European countries and private partners to develop a World Class Supercomputing Ecosystem in Europe.
eurohpc-ju.europa.eu
February 8, 2024 at 10:55 AM
7. Push for publicly owned centralised data storage
Large centralised data centres tend to be more efficient, but this often means relying on big tech comapnies to host data. Alternatives like EuropHPC JU may allow storage that is efficient & sustainable:
eurohpc-ju.europa.eu/index_en
Large centralised data centres tend to be more efficient, but this often means relying on big tech comapnies to host data. Alternatives like EuropHPC JU may allow storage that is efficient & sustainable:
eurohpc-ju.europa.eu/index_en