candy_lab

neuroimaging; functional PET-MRI; ultra-high field fMRI; brain physiology & metabolism; signal processing – CANDY lab @MGHMartinos

[candy_lab @candy_lab_]

A cartoon video on MRI created by our high-school intern (and incoming Harvard undergrad) Emma Yeon! Stay tuned for more installments on medical imaging! https://t.co/n7ISYQP7NP

[bioRxiv Neuroscience @biorxiv_neursci]

Energetic implications of fMRI-based nodal complex network metrics: a complex picture unfolds across diverse brain states https://t.co/1nmSnQPHdT #biorxiv_neursci

[candy_lab @candy_lab_]

A multi-year project finally comes out! Using EEG-fPET-fMRI, we reveal the intricate coordination of diverse physiological processes during the descent into NREM sleep and the cortical pathway facilitating sensory awakening! @MGHMartinos @NatureComms https://t.co/5VbXm3Ygbi

[candy_lab @candy_lab_]

Introducing CortiLag ICA — an ICA-based denoising pipeline for medium- and high-resolution fMRI data, potentially useful when relevant training data or multi-echo acquisitions are unavailable!
https://t.co/wM02IMmhtq

[Imaging Neuroscience @ImagingNeurosci]

New paper in Imaging Neuroscience by Jingyuan E. Chen, Jonathan R. Polimeni, et al:

Differentiating BOLD and non-BOLD signals in fMRI time series using cross-cortical depth delay patterns

https://t.co/94h0DEUG3z

[candy_lab @candy_lab_]

How much information can be extracted from fMRI physiological signals (“noise”)? Using HCP-A data, Dakota Fan from our lab demonstrates age-related, multi-parametric changes in brain vascular physiology and biomechanical properties! https://t.co/BWLQbPoa4L

[Communications Biology @CommsBio]

Functional MRI signatures of autonomic physiology in aging: Communications Biology, Published online: 27 August 2025; doi:10.1038/s42003-025-08703-7Functional magnetic resonance imaging signals linked to heart rate and respiration reveal age-related… https://t.co/7wZEJ31IoC

[candy_lab @candy_lab_]

fPET-FDG is an exciting method to track intra-scan glucose metabolism dynamics! Sean Coursey from our lab shows that baseline misspecification can introduce spurious metabolic activations—a small step toward more robust statistical analysis with fPET-FDG! https://t.co/yHAa4LaVDj

[Imaging Neuroscience @ImagingNeurosci]

New paper in Imaging Neuroscience by Sean E. Coursey, Jingyuan E. Chen, et al:

On the analysis of functional PET (fPET)-FDG: Baseline mischaracterization can introduce artifactual metabolic (de)activations

https://t.co/65svACSkEq