@leechbrain
 London, England
github.com/ActiveNeuroImaging/Blender/blob/main/README.md
Joined May 2015
  • Tweets3.6K
  • Following835
  • Followers1.1K
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Using machine learning, this study shows that self-reported experience of task states maps onto 'brain space', i.e., features of different task states identified in fMRI. @the_mindwanders @leechbrain @IanGoodallH @BronteMckeown nature.com/articles/s44271-0…

Self-reports map the landscape of task states derived from brain imaging

Communications Psychology - Using machine learning, this study shows that self-reported experience of task states maps onto ‘brain space’, i.e., features of different task states...

nature.com
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We are incredibly excited to announce a new psychedelic research collaboration with King’s College London, investigating neurobiological changes that underly the ‘mystical experience’ using high-resolution 7 Tesla fMRI scanning. We look forward to seeing this research commence!
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The good news is that we can optimise task contexts to maximise their sensitivity to specific relationships, reducing the cost of future BWAS. See work by @leechbrain @romy_lorenz to see how this could work sciencedirect.com/science/ar…
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So the take home is that BWAS studies that use only 1 situation (often rest) require large sample sizes because any single situation may not be suited to detect brain-trait associations for all trait dimensions. See this nice review by @GrattonCaterina pubmed.ncbi.nlm.nih.gov/3941…

Using precision approaches to improve brain-behavior prediction - PubMed

Predicting individual behavioral traits from brain idiosyncrasies has broad practical implications, yet predictions vary widely. This constraint may be driven by a combination of signal and noise in...

pubmed.ncbi.nlm.nih.gov
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Importantly we looked at how many people you would need to show the relations in the best tasks for capturing a specific trait. Our estimates suggest hundreds (not thousands) of people would be needed to show the brain-trait relationship seen in the whole sample.
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These relations were clear for #gradients 3 (task positive-task negative) and 2 (vision-motor). Tasks with a strong response for one trait were different to those for other traits. This suggests there is likely no -one-size-fits-all situation for all brain-trait associations
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We examined if location of any of the tasks in the state-space varied with traits using Linear Mixed Models in R. We found little evidence that traits uniformly impact on brain activity in all tasks. Instead brain-trait association were often stronger in some tasks than others 👇
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To this end we took the task data from the Human Connectome Project and examined how brain activity in each situation vary with the Big-5 Personality traits. We built a 3d state-space using the first three #gradients from the work by @margulies and projected task data into it 👇
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Remember back in 2022, when we didn't need to worry about a 2nd Trump Presidency, but were concerned about how many participants it would take to map links between personality & brain activity? (cf work by @smarek0502 & @ndosenbach) We have good news 👇 nature.com/articles/s42003-0…
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Our review/perspective on tracking non-stationarity of an unknown process is now published in Chaos 🦋 Congratulations @kieran_s_owens ! Stay tuned for some follow-up work coming soon 👀 pubs.aip.org/aip/cha/article…

Parameter inference from a non-stationary unknown process

Non-stationary systems are found throughout the world, from climate patterns under the influence of variation in carbon dioxide concentration to brain dynamics

pubs.aip.org
Ben Fulcher@bendfulcher15 Jul 2024
Latest preprint: "Parameter Inference from a Non-stationary Unknown Process" (PINUP) We're really interested in the problem of inferring sources of non-stationary variation directly from measured time-series data. arxiv.org/abs/2407.08987v1 Quick summary 👇
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Rob Leech retweeted
David Soto@d_soto_b25 Oct 2024
Join our lab for an exciting PhD position to investigate perceptual awareness using psychophysics, fMRI and decoded neurofeedback. How to Apply: shorturl.at/vDtQH Application Deadline: December 1, 2024 Please retweet! @theASSC
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Well said, @LukeOShea1. hsj.co.uk/technology-and-inn…
More fundamentally, we sometimes fail to question the underlying processes and digitise them anyway. Long prose notes and letters have survived almost unscathed in the transition away from paper; instead, maybe, consultants could be told they don't need to write a clinic letter after every single appointment. Maybe GPs could access clinic notes, discharge summaries, and results directly in their systems, and patients via the NHS App. Maybe, just maybe, we don't need letters at all? I have seen many poor processes digitised when the big productivity gains come from asking basic questions about the process itself. So yes, we absolutely need investment in Al, but the unpopular truth is that we will also need the management capacity to transform our inefficient processes as well.

ALT More fundamentally, we sometimes fail to question the underlying processes and digitise them anyway. Long prose notes and letters have survived almost unscathed in the transition away from paper; instead, maybe, consultants could be told they don't need to write a clinic letter after every single appointment. Maybe GPs could access clinic notes, discharge summaries, and results directly in their systems, and patients via the NHS App. Maybe, just maybe, we don't need letters at all? I have seen many poor processes digitised when the big productivity gains come from asking basic questions about the process itself. So yes, we absolutely need investment in Al, but the unpopular truth is that we will also need the management capacity to transform our inefficient processes as well.

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Happy to share our Opinion piece @TrendsCognSci "Large-scale interactions in predictive processing: oscillatory versus transient dynamics" with @martin_a_vinck, @uran_cem, Jarrod Dowdall & Brian Rummell. Check our thread below 🧵👇
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Shining a light on subcortical organization 🧠💡! Using @yetianmed's Melbourne Subcortex Atlas, here’s my latest dive into glass brain visualizations—aiming for practical and insightful anatomical renders! 🎥👇
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For those in Chicago for @SfNtweets, welcome! Come check out our poster (Wed 1-5pm; I'm there at 4!). We recorded iEEG during a mental imagery task, with rsfc-MRI networks in the same patients. Come learn about changes in temporal dynamics across different functional networks!
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We started this journey together at the @BcBlab, and I’m so glad to see the “cognition morphospace” finally published in @NatureComms, joining the “disconnectome morphospace” in our morphospace family! Congratulations @valepacella 👏
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Had to try mixing Python & Blender after seeing @leechbrain's mesmerizing brain animations. 🧠✨ Spent the weekend tinkering, and honestly, happy with the result! Now wondering if it'd be useful in presentations/research or just a cool tool. 🤔 #Thumping_Thoughts😅
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Replying to @the_mindwanders
@the_mindwanders @leechbrain
Why you should have a cat
@ShouldHaveCat21 Sep 2024
Kitten seeing birds for the first time🥹
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🚨Attn fellow scientists! If you’ve reviewed for or published in these journals you can be part of this @LucinaUddin taking her natural knack for leadership to the legal realm 💪🏽 xitter.cf/laurenatlas/status/183…
Mushtaq Bilal, PhD
@MushtaqBilalPhD15 Sep 2024
Major academic publishers are getting sued for unlawfully appropriating billions of dollars. Prof. Lucina Qazi Uddin, a neuroscientist at UCLA, has sued these six academic publishers Elsevier, Wolters Kluwer, Wiley, Taylor & Francis, Sage, and Springer Nature. The lawsuit claims that these publishers violate antitrust laws on the following three grouds: 1. The publishers have colluded to fix the price of peer review at zero. 2. These publishers agree to not compete with each by making it obligatory for researchers to submit their work to only one journal at a time. 3. These publishers prohibit scholars from sharing scientific advancements while they are under peer review, which can take up to a year. Here's a comparison of the publishers' revenue and what they pay authors and reviewers Elsevier: $3.9 billion Springer Nature: $2 billion Wolters Kluwer: $1.6 billion Wiley: $1.8 billion Taylor & Francis: $800 million Sage: $500 million They pay: Authors: $0 Peer reviewers: $0
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Rob Leech retweeted
Rob Leech@leechbrain6 Sep 2024
Day 31: #nobrains #geometrynodes #blender "It's called the Academic Dream because you have to be asleep to believe in it"
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