Swathi Kiran@Center for Brain Recovery at BU
@swathikiran.bsky.social
810 followers 140 following 250 posts
Brain imaging, aphasia, stroke recovery, neuroscience, bilingualism, connectivity, language in the brain
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swathikiran.bsky.social
This morning, the Center for Brain Recovery received a special visit from Boston University's community resource dog, Bean!

Bean immediately brightened up the office and brought plenty of play and cuddles to the CBR team.

Thanks for stopping by our center, Bean!
swathikiran.bsky.social
Join us Monday, September 29th from 4:00 pm to 5:00 pm ET for a talk by Rhoda Au, Professor at Boston University Chobanian & Avedisian School of Medicine, as well as a PI of the Framingham Heart Study Brain Aging Program.

Register now at http://bit.ly/47ORaie
swathikiran.bsky.social
Congratulations! The impact of your work is huge across so many fields!
swathikiran.bsky.social
#BilingualAphasia #Stroke #AphasiaRecovery #Generalization
swathikiran.bsky.social
💡 Takeaway: Semantic feature-based treatment promotes gains across languages and linguistic domains in Spanish-English bilinguals with aphasia
💭 Next: How do dose, intensity, and individual differences shape transfer?
📂 Open dataset coming: http://osf.io/mcu36
swathikiran.bsky.social
Results showed:
1) Improvement for trained and untrained naming targets (direct transfer)
2) Gains in select semantic processing tasks (near transfer)
3) Improved overall language function (WAB-AQ) but not domain-general cog (both far transfer)
🎉 Benefits across both languages
swathikiran.bsky.social
📢 New Bilingual Aphasia Research!

“Measurement of cross-language and cross-domain generalization following semantic feature-based anomia treatment in bilingual aphasia”

By Marissa Russell-Meill, Erin Carpenter, Manuel J. Marte, Michael Scimeca, Claudia Peñaloza & Swathi Kiran
swathikiran.bsky.social
Excited to be editing this special issue with @qzhever.bsky.social on this super current topic of “Neural Basis of Language Processing in the Wild” see link for submission guidelines
swathikiran.bsky.social
Over the coming weeks, we’ll continue releasing presentations from the N.E.W. Conference. Subscribe to stay updated: youtube.com/@bucenterfor...
Boston University Center for Brain Recovery
youtube.com
swathikiran.bsky.social
His presentation highlights his research into human navigational behavior across diverse global populations. Using innovative tools such as video games, Spiers and his team have uncovered new insights into how individuals orient themselves in complex environments—from urban grids to open waters.
swathikiran.bsky.social
Join us Monday, September 15th from 4:00 pm to 5:00 pm ET for a talk by Simona Mancini, Ikerbasque Research Associate Professor / Neurolinguistics and Aphasia group leader at the Basque Center on Cognition Brain and Language.

Register now at https://bit.ly/45LjrF1
swathikiran.bsky.social
💡 Takeaway: Integrating rs-fMRI + DTI + structure better captures post-stroke brain reorganization.
Predicting severity is the first step—next is predicting recovery.
📂 Open dataset coming: http://osf.io/mcu36
#Neurorehab #Stroke #MLinNeuro #AphasiaRecovery
swathikiran.bsky.social
Limitations:
⚠️ Fewer data points for severe aphasia (WAB-R AQ < 20)
⚠️ Minor processing differences across cohorts
Still, robust findings with nested cross-validation and supervised feature selection (RFE) 💪
swathikiran.bsky.social
🔥 SVR outperformed RF consistently.
💡 Best combo = resting-state functional connectivity (rs-fMRI FC) + spared white matter (PSW) + demographics
✅ RMSE: 15.82
✅ r: 0.73
💡 Best single predictor = (rs-fMRI FC)

#MachineLearning #Neuroimaging
swathikiran.bsky.social
🧠 Goal: Predict aphasia severity (WAB-R AQ) post-stroke using machine learning + multimodal MRI
🏥 76 individuals with chronic aphasia
🧪 Imaging: Structural MRI, DTI, rs-fMRI
🧮 Models: Support Vector Regression (SVR) and Random Forest (RF)
swathikiran.bsky.social
📢 New in NeuroImage:
“Aphasia severity prediction using a multi-modal machine learning approach”
by Xinyi Hu, Maria Varkanitsa, Emerson Kropp, Margrit Betke, Prakash Ishwar & Swathi Kiran
🔗 doi.org/10.1016/j.ne...
#Aphasia #NeuroAI #StrokeRecovery
Aphasia severity prediction using a multi-modal machine learning approach
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI…
doi.org
swathikiran.bsky.social
📢 New Research from the BU Center for Brain Recovery:
CBR researchers examined how to predict aphasia severity (WAB-R AQ) post-stroke using machine learning + multimodal MRI.

Read more: doi.org/10.1016/j.ne...

#Stroke #AphasiaRecovery #MachineLearning #Neuroimaging #Neurorehab #MLinNeuro #Research
swathikiran.bsky.social
I think most of the treatments reviewed in this paper target practicing phonological access- it’s actually quite non specific IMO - that’s why the review finds generalization to untrained words and in some treatments even the control words
swathikiran.bsky.social
Over 60% of this year's Neuroscience of the Everyday World (N.E.W.) Conference attendees were students/trainees!

Thank you to all of our student/trainee attendees who shared their research in the form of a poster or talk and congratulations to our 18 travel award winners!

#NEWconf2025
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Thank you to all of our Day 2 speakers, sponsors, and attendees!

And thank you to our collaborators, Tianqiao and Chrissy Chen Institute and Boston University Neurophotonics Center. #NEWconf2025
swathikiran.bsky.social
Symposium 3 Speakers:
Daniel Ferris, University of Florida
Simon Ladouce, University of Leuven
Matthew Rizzo, University of Nebraska Medical Center
Ying Choon Wu, University of California, San Diego