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Locus coeruleus connectivity at 3T based on individual localization using a neuromelanin sensitive sequence as compared to MNI space masks. Results largely converge, though the TPJ may be driven by other nuclei. Good news for atlas-based analyses! https://buff.ly/3b7auYk pic.twitter.com/WswNzQSHA5
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Is connectivity-based fMRI neurofeedback nothing but a (very expensive) breathing training? Given effectiveness of global signal regression motion may also play a role Unsurprising but convincing demonstration of how susceptible rs-FC is to physiology https://www.sciencedirect.com/science/article/pii/S1053811920300677 …pic.twitter.com/h1WkY5HuoJ
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“Using a term like nonlinear function is like referring to the bulk of zoology as the study of non-elephant animals.” – Stanislaw Ulampic.twitter.com/xkMN2gJDyZ
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Dimensions of schizophrenia psychopathology by
@jchen_ML_Psy 4 factor provide the most stable & generalizable representation based on ~2000 patients from 10+ sites: https://buff.ly/2NoYnLP Here is our new webtool to map data onto these dimensions !! http://webtools.inm7.de/sczDCTS/ pic.twitter.com/t2167qVTKt
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To be useful,
#MachineLearning on neuroimaging data needs to generalize across centers, but site specific effects are massive and a major challenge Excited to see this work by@chrisdav66 & team using ComBat for harmonization across datasets 6 lifespan https://buff.ly/3a9yjy1 pic.twitter.com/1h2dHw7dU1
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Patients with
#Autism show reproducible patterns of functional connectivity: https://buff.ly/2NuH8J3 by@DukartJuergen Or not? https://buff.ly/2To0SSj : stabilities across pipelines but not sites Problem: The samples in the second negative study are an order of magnitude smallerpic.twitter.com/N6cJUDMfyr
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Can you change your personality? Apparently: https://buff.ly/2u1wi6h The idea of stable personality always struck me odd as plasticity is probably *the* defining feature of the brain. Why should (only) personality be unaffected by experience or willful effort?
@WiringTheBrainpic.twitter.com/vKgajYIWdi
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Double Dipping in
#MachineLearning yields 80% accuracy on random data but is easily prevented by clean crossvalidation Bigger issue: overfitting by re-re-re-analysing datasets. Data-sharing will help, but ultimately it's prospective, prepregisterd tests https://buff.ly/30dPk5G pic.twitter.com/p6IMzvkyFn
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The "pain-matrix" in the human brain revealed by our
@sattertt@annakxu new meta-analysis: Preregistered, ~5000 screened papers, >200 included experiments Core regions consistently recruited regardless of stimulation type, pain location & participant sex https://buff.ly/2u3uc6e pic.twitter.com/HGpgoRooin
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Dissociated representations of reinforcement along hippocampal long axis: Posterior signals predict exploration anterior exploitation A->P gradient seems more behaviorally relevant than subfields (cf. https://buff.ly/2ReLWmS )
@AlexDombrovski1@bealuna55 https://buff.ly/36Lrz7o pic.twitter.com/HcQwEZyTKV
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Nice study
@NeuroMetrology: data from 6 wearable sensors during standard clinical tests may differentiate PD from PSP / controls. Small N, so I would not give to much about accuracies. Key message is the potential of quantitative clinical phenotyping ! https://buff.ly/2NnWb7h pic.twitter.com/vYsor35kOZ
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Interested in robust ROIs, functional networks and task-based connectivity maps? Check out the ANIMA database! View & download data from meta-analytic studies on the default-mode, premotor cortex, emotion regulation and action control and many more ! http://anima.fz-juelich.de pic.twitter.com/QufnXJojgQ
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Thanks for sharing out work! Here is a follow-up taking a more clinical perspective: https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24886 …pic.twitter.com/spttL5zVsy
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Good read by
@DaniSBassett on translational potential of data-driven neuroimaging analysis for psychiatric diagnosis & therapy The perspective is clear, tools are (increasingly) there, what is really missing is (shared) data. None of this works with N=40 https://buff.ly/2spXBag pic.twitter.com/Ao4p7pxeBA
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Reporting tractometry results [...] without a sufficient reproducibility score could make the analysis and interpretations more difficult. Massive work by
@FrancoisRheault,@maxdescoteaux & many more on the reproducibility of tractography dissections https://buff.ly/3a6opxa pic.twitter.com/9t4xivAFPN
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Interested in gradients of brain organization? Check out the BrainSpace toolbox! Amazing work with parallel
@MATLAB and#Python implementation Next stop: Understanding the relationship between brain areas, gradients and large-scale networks
https://www.biorxiv.org/content/10.1101/761460 …pic.twitter.com/AfF5PlHajI
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"Cerebral cortical folding, parcellation, and connectivity in humans, nonhuman primates, and mice" David van Essen & team covering a lot of ground in this comprehensive review, even though the "human" side is biased heavily towards their own atlas https://www.pnas.org/content/116/52/26173.short …pic.twitter.com/kOaEqOMhBf
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We are looking for a postdoc
Join us to develop & apply new approaches for #MachineLearning on neuroimaging and clinical datasets. Many exciting data-sets, world-class facilities@fzj_jsc, international network and a great team@fzj_inm7 Please RT for reach !!pic.twitter.com/vYeCJInISA
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What's your evidence? Here Bert Heinrichs, a philosopher, and I outline some thoughts on discursive practice, acceptance and responsibility in the context of
#MachineLearning for medical diagnosis & prediction https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24886 …@KordingLab@DrHughHarvey@NewMindMirrorpic.twitter.com/zwcQdl5jLb
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It's a joy when others are worse off than myself Social downward comparison robustly results in activation of the ventral striatum, a key brain region for reward processing https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.23854 …pic.twitter.com/ywCp3kuyFD
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