Sydney, Australia
Joined June 2019
- Tweets208
- Following219
- Followers317
- Likes445
Pinned Tweet
Do you work on surface MRI such as HCP data? Our paper is finally out in Imaging Neuroscience, showing biases in surface fMRI. The revised ms has many new insights!
TLDR: Vertices are much closer to each other in sulci, resulting in (fake) high spatial autocorrelation. (1/5)
Jayson Jeganathan retweeted
New paper in Imaging Neuroscience by Jayson Jeganathan, Michael Breakspear, et al:
Spurious correlations in surface-based functional brain imaging
doi.org/10.1162/imag_a_00478
This was a team effort! @KoussisNikitas @tremodian @Sina_Mansour_L @AndrewZalesky @DrBreaky @phogat_richa @jchrispang
I'm proud of this work, and I hope this paper helps you to avoid spurious conclusions in your work. Check out the full paper (tinyurl.com/gyral) for a detailed breakdown and for other downstream analyses that can be impacted (FC fingerprinting, hyperalignment, etc). (5/5)
The new Onavg template promises to even out variability in inter-vertex spacing across the cortex. We tested this. This template reduces variability by 90% in the common surface space, but only by about 20% in subject-specific surfaces :( (4/5)
We then explored the consequences. Adjacent sulcal vertices have highly correlated fMRI time series just because they're closer. This can trick functional parcellations into putting parcel boundaries on gyri instead. (3/5)
This new visual by @phogat_richa shows it all. In this single-subject flattened cortex, we see mesh vertices and triangles with gyri (red) and sulci (blue). The triangles are clearly smaller in sulci (blue). All fsaverage and fsLR surfaces look like this. (2/5)
Amazing paper !
1/12 How do animals build an internal map of the world? In our new paper, we tracked thousands of neurons in mouse CA1 over days/weeks as they learned a VR navigation task. @nspruston @HHMIJanelia, w/ co-1st author @JohanWinn
Video summary: youtube.com/watch?v=yw_4uVur…
Paper: nature.com/articles/s41586-0…
Jayson Jeganathan retweeted
In markets, there are price bubbles. In science, are there popularity bubbles? When promising research gets hyped up, it can lead to a burst of activity followed by a dramatic collapse, shows huge bibliometric study @Nature Magazine l.sslevine.com/Ex7z
Wow. Most recent openAI model o3 smashes the prev leaderboard for ARC-AGI reasoning challenge. It is also now the 175th best coder in the world (CodeForces challenge), and can solve 25% of hard-for-humans FrontierMath Qs (up from 2%). What does this all mean?
ARC-AGI scores for past five years of OpenAI models (updated w/ release dates)
ALT Matplotlib scatter plot of ARC-AGI score data from @mikeknoop’s quote-tweeted post ARC-AGI semi-private v1 scores: * GPT-2 (2019): 0% * GPT-3 (2020): 0% * GPT-4 (2023): 2% * GPT-4o (2024): 5% * o1-preview (2024): 21% * o1 high (2024): 32% * o1 Pro (2024): ~50% * o3 tuned low (2024): 76% * o3 tuned high (2024): 87%
Jayson Jeganathan retweeted
I've combined some of these together into a new #neuro #visualization "In the eye of a fly":
Using the @FlyWireNews visual system wiring diagram, #Brian2 spiking #neuron simulator, and #blender. Information flow through the chiasms, across a topographic map.
Wow
𝗛𝗼𝘄 𝘀𝗵𝗼𝘂𝗹𝗱 𝗼𝗻𝗲 𝗱𝗼 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗻𝗲𝘂𝗿𝗼𝘀𝗰𝗶𝗲𝗻𝗰𝗲??
This way! Every neuro program should just make this required reading and teach students how to do outstanding science like this.
doi.org/10.1038/s41586-024-0…
