Baptiste Couvy-Duchesne

Happy to share our latest paper, the work of @clarajiang.bsky.social who trained brain-based predictors of depression on the UK Biobank (N=7,500 curated cases and matched controls) using AI/deeplearning as well as efficient statistical learning (BLUP). See thread below for a summary of findings

We concluded that depression does not have a strong signature in the grey matter, and that other brain MRI sequences (e.g. diffusion, or functional MRI) may be required to accurately predict depression.

Happy to share our latest paper, the work of @clarajiang.bsky.social who trained brain-based predictors of depression on the UK Biobank (N=7,500 curated cases and matched controls) using AI/deeplearning as well as efficient statistical learning (BLUP). See thread below for a summary of findings

Our results highlight the difficulty to predict depression from structural brain MRI, which was previously reported in papers from the ENIGMA-MDD consortium.

Happy to share our latest paper, the work of @clarajiang.bsky.social who trained brain-based predictors of depression on the UK Biobank (N=7,500 curated cases and matched controls) using AI/deeplearning as well as efficient statistical learning (BLUP). See thread below for a summary of findings

Notably, the simple and efficient BLUP predictor outperformed the Deep Learning ResNet predictor, which is not unusual for brain-based predictors with these sample sizes.

Happy to share our latest paper, the work of @clarajiang.bsky.social who trained brain-based predictors of depression on the UK Biobank (N=7,500 curated cases and matched controls) using AI/deeplearning as well as efficient statistical learning (BLUP). See thread below for a summary of findings

I have always wondered if there is a best method/software to process T1w image (at a vertex/voxel wise level). Elise Delzant has some answers in her first published paper from her PhD. She compared FreeSurfer, CAT12 and FSL across several traits and analyses (association, prediction).

Still, we hope our results can help researchers make informed decisions when selecting a processing. And that it can encourage others to evaluate other image processing options (e.g., different software versions, non-default settings).

I have always wondered if there is a best method/software to process T1w image (at a vertex/voxel wise level). Elise Delzant has some answers in her first published paper from her PhD. She compared FreeSurfer, CAT12 and FSL across several traits and analyses (association, prediction).

To make things even more complicated, it may also depend on the trait you are interested in. On average FSL VBM does a good job, but for some traits like Alzheimer's disease or maternal smoking, FreeSurfer may yield more significant associations.

I have always wondered if there is a best method/software to process T1w image (at a vertex/voxel wise level). Elise Delzant has some answers in her first published paper from her PhD. She compared FreeSurfer, CAT12 and FSL across several traits and analyses (association, prediction).

Elise's results also confirm that the choices of processing have important consequences on the results, which contributes to the reproducibility crisis. See results below for the same individuals and same trait (maternal smoking around birth - associated regions vary depending on processing)

I have always wondered if there is a best method/software to process T1w image (at a vertex/voxel wise level). Elise Delzant has some answers in her first published paper from her PhD. She compared FreeSurfer, CAT12 and FSL across several traits and analyses (association, prediction).

Our latest paper is out! A well powered high resolution mapping of the grey-matter regions associated with Alzheimer's, progression to Alzheimer's disease, cognition and functioning. @drbreaky.bsky.social @barkhof.bsky.social @michelleklupton.bsky.social

Our latest paper is out! A well powered high resolution mapping of the grey-matter regions associated with Alzheimer's, progression to Alzheimer's disease, cognition and functioning. @drbreaky.bsky.social @barkhof.bsky.social @michelleklupton.bsky.social

Interestingly, the brain regions associated with Alzheimer's, disease progression and cognition overlapped suggesting some of the same regions are implicated. Some regions stand out being associated with many traits.

Our latest paper is out! A well powered high resolution mapping of the grey-matter regions associated with Alzheimer's, progression to Alzheimer's disease, cognition and functioning. @drbreaky.bsky.social @barkhof.bsky.social @michelleklupton.bsky.social

We have also estimated that there should be at least 5 times more regions that remain to be identified (difference between the morphometricity and variance currently explained by the identified regions). Even more data will be needed!

Our latest paper is out! A well powered high resolution mapping of the grey-matter regions associated with Alzheimer's, progression to Alzheimer's disease, cognition and functioning. @drbreaky.bsky.social @barkhof.bsky.social @michelleklupton.bsky.social

Our high-resolution approach makes it possible to identify sub-regions of the hippocampus (or of the amygdala) that are involved, which can orient research towards specific brain regions/networks or cell populations.

Our latest paper is out! A well powered high resolution mapping of the grey-matter regions associated with Alzheimer's, progression to Alzheimer's disease, cognition and functioning. @drbreaky.bsky.social @barkhof.bsky.social @michelleklupton.bsky.social

Here is our latest publication (the first from our Lemerend consortium) that looks at early risk factors of neurodegenerative disorders. Thank you to all the authors, and in particular the fantastic team of analysts!

Likewise for medical conditions, which are associated with future risk of neurodegenerative disorders.

Here is our latest publication (the first from our Lemerend consortium) that looks at early risk factors of neurodegenerative disorders. Thank you to all the authors, and in particular the fantastic team of analysts!

We focused on associations that were consistent across the different countries - hence, they cannot be attributed to specific health systems, bias in the data or the type of medical records (primary, hospital).

Here is our latest publication (the first from our Lemerend consortium) that looks at early risk factors of neurodegenerative disorders. Thank you to all the authors, and in particular the fantastic team of analysts!