Douglas Garrett
@garrettneuro.bsky.social
360 followers 550 following 21 posts
Senior Scientist and PI of the Lifespan Neural Dynamics Group @Max Planck UCL Centre for Computational Psychiatry and Ageing Research, MPI for Human Development, Berlin, Germany www.douglasdgarrett.com 🇨🇦➡️🇩🇪
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garrettneuro.bsky.social
Fantastic news Tom, no doubt they are stoked to have you!
garrettneuro.bsky.social
BOLD variability (especially on-task) typically has loads of behaviourally-relevant effects, at within- and between-subject levels. No amount of preprocessing/noise removal can kill those effects in our hands. For example: www.cell.com/neuron/pdf/S...
www.cell.com
garrettneuro.bsky.social
The majority of variance in BOLD has nothing to do with motion. MeanBOLD and SDBOLD are rarely highly correlated in any dataset I've seen, any ratio of the two (e.g., tSNR) makes interpretations unnecessarily difficult. Could start by linking mean and SD estimates you have separately to behaviour?
Reposted by Douglas Garrett
smfleming.bsky.social
This is happening tomorrow! 😅😅😅
smfleming.bsky.social
I'll be talking about all things metacognitive on 23rd Jan in a public lecture at the @royalsociety.org

It's free to attend and will also be broadcast live on the RS YouTube channel (no pressure then 😅)

royalsociety.org/science-even...
How the human brain thinks about itself | Royal Society
Royal Society Francis Crick Prize Lecture by Professor Stephen Fleming.
royalsociety.org
garrettneuro.bsky.social
Agreed...No doubt film is a major step forward over resting state, and is indeed an engaging task in its own right, especially when behavior is concurrently collected!
Reposted by Douglas Garrett
ndosenbach.bsky.social
The brain’s action-mode is created by a dedicated action-mode network (AMN) rdcu.be/d5odm. In the brain’s mode continuum, AMN sits opposite DMN’s default-mode, as yin-yang. AMN might be key in pain, apathy, Parkinson’s. New @natrevneurosci.bsky.social w/ Marc Raichle & @gordonneuro.bsky.social 🧵 ⬇️
Reposted by Douglas Garrett
cp-neuron.bsky.social
To start off 2025, we are very pleased to introduce a Special Issue on the Neuroscience of Aging, curated by Axel Guskjolen.
We hope you enjoy every single piece of it as much as we do!
www.cell.com/neuron/current
garrettneuro.bsky.social
PhD student @zoyamooraj.bsky.social et al. with a remarkable vision for the future of the cog neuro of human aging, now live in Neuron: www.cell.com/neuron/fullt....

Task-related function is the future y'all... there can be no substitutes if we want to understand cognitive aging.
garrettneuro.bsky.social
Curious to hear your take on the structure-function stance as well...no doubt you're one of those trying to do it right. Keep up the great work guy😤
garrettneuro.bsky.social
Outstanding man, congrats!
Reposted by Douglas Garrett
lipmpib.bsky.social
New LIP paper out now: Congratulations to colleagues Leo Waschke and Fabian Kamp and co-authors!
garrettneuro.bsky.social
Massive thanks to all co-authors (Waschke, Kamp, van den Elzen, Krishna, Lindenberger, and Rutishauser) and to @lipmpib.bsky.social @mpib-berlin.bsky.social for support of one of the most important projects I have had the pleasure to work on. Cheers!
garrettneuro.bsky.social
We thus propose that moment-to-moment spiking variability may provide a new window into how the hippocampus constructs memories from the "building blocks" of our sensory world.
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ALT: a blurred image of a brick wall with a blue sky in the background
media.tenor.com
garrettneuro.bsky.social
Crucially, we show that the more precisely hippocampal spiking variability tracks the composite (late-layer) features that comprise each individual stimulus, the better those stimuli are later remembered up to 30 minutes later. These effects were also *spatially specific* to the hippocampus.
garrettneuro.bsky.social
Hippocampus spiking entropy was coupled to image features in every.single.subject...with tighter coupling to more composite (late layer) than to simpler (early layer) image features.
garrettneuro.bsky.social
We used comp. vision models (HMAX & VGG16) to estimate the features of images presented to patients (N = 34) during memory encoding. We then estimated the coupling of hippocampal single-neuron variability (entropy) to image features via within-participant latent correlations.
garrettneuro.bsky.social
Ok, but what signature of hipp. spiking might track such features? We've shown that the variability of fMRI activity in visual cortex scales with the complexity of visual input (sciencedirect.com/science/arti...). Could this also be the case in the hippocampus during memory formation?
Higher performers upregulate brain signal variability in response to more feature-rich visual input
The extent to which brain responses differ across varying cognitive demands is referred to as “neural differentiation,” and greater neural differentia…
sciencedirect.com
garrettneuro.bsky.social
We argue that the architecture of multi-layer computational vision models can be used to differentiate between simple and composite visual features of any stimulus a participant may encode.
garrettneuro.bsky.social
More composite features might dominate due to the hippocampus’ hierarchical position and afferent projections, but “simple” features might still be crucial for detailed representations. How can we know?
garrettneuro.bsky.social
During memory formation, the hippocampus is presumed to represent and conjunct the “content” of stimuli. How does it do this? On which kind of sensory features does the hippocampus rely when memories are formed?
a fat man is wearing a blue and yellow striped shirt .
ALT: a fat man is wearing a blue and yellow striped shirt .
media.tenor.com
garrettneuro.bsky.social
Absolutely outstanding multi-modal work on uncertainty in the aging brain by @juliankosciessa.bsky.social et al., many years in the making. EEG, fMRI, comp modelling, sub vs. cortical, this one has it all!

Now live in Nature Communications: www.nature.com/articles/s41...