Ozan Vardal's Avatar

Ozan Vardal

@ozvardal.bsky.social

Neuroscience postdoc | ISTBI, Fudan University #shanghai | Studying learning & naturalistic decision-making | video games + neuroimaging + computational modeling

56 Followers  |  161 Following  |  4 Posts  |  Joined: 29.05.2025  |  1.4428

Latest posts by ozvardal.bsky.social on Bluesky

Post image

Check out our new work on the relationship between glioma and system-level functional networks! We identify that nearly all gliomas localize within a common brain functional network, Action-Mode Network (AMN) .

biorxiv.org/content/10.64898/2026.01.05.697608v1

06.01.2026 07:25 โ€” ๐Ÿ‘ 20    ๐Ÿ” 9    ๐Ÿ’ฌ 8    ๐Ÿ“Œ 4
Preview
The 1,000 neuron challenge A competition to design small, efficient neural models may provide new insight into real brainsโ€”and perhaps unite disparate modeling efforts.

Read my new piece in the @thetransmitter on @rougier's 1000 neuron challenge

https://www.thetransmitter.org/computational-neuroscience/the-1000-neuron-challenge/

models, brains, and the value of scientific competitions as sites of integration!

#Neuroscience #CompNeuro

05.01.2026 08:33 โ€” ๐Ÿ‘ 4    ๐Ÿ” 5    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0
Post image

Just finished Natural Neuroscience โ€“ a book I think will become an instant classic. This book can do for neuroscience what Schrodingerโ€™s โ€˜What is Lifeโ€™ did to usher in the golden age of molecular biology. Nachum Ulanovsky has given us a compelling call to arms to truly understand the brain.

16.05.2025 10:01 โ€” ๐Ÿ‘ 73    ๐Ÿ” 9    ๐Ÿ’ฌ 3    ๐Ÿ“Œ 2
Post image

๐Ÿง  New paper alert (the 1st one from our new lab)!
Led by 1st author & VR wizard @jaquent.bsky.social

@natcomms.nature.com

How do our brains distinguish novel from familiar places as we explore our environments, e.g., a new city?

๐Ÿ”— doi.org/10.1038/s414...

๐Ÿงต Thread below with key findings โฌ‡๏ธ

09.12.2025 09:49 โ€” ๐Ÿ‘ 26    ๐Ÿ” 12    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 2
Post image

๐—ช๐—ต๐—ฎ๐˜'๐˜€ ๐—ฐ๐—ผ๐—ด๐—ป๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐—ถ๐˜€ ๐—ถ๐˜ ๐—ฒ๐—บ๐—ฒ๐—ฟ๐—ด๐—ฒ๐—ป๐˜?
Don't miss the Neuroscience and Philosophy Salon.
Earl Miller and team will discuss recent paper and we'll have plenty of discussion. Open to all.
Sept 12, noon EST-US
umd.zoom.us/meeting/regi...
#neuroskyence
@earlkmiller.bsky.social

24.08.2025 16:06 โ€” ๐Ÿ‘ 74    ๐Ÿ” 24    ๐Ÿ’ฌ 5    ๐Ÿ“Œ 3
Task design and experimental set-up. Top left: underlying structure of the 8 ร— 8 grid, unseen by participants. Every state is represented by an image of an object, and these objects and their positions change on every trial. Top right: schematic diagram of the โ€˜map readingโ€™ phase of each trial. Participants see a topโ€“down view of the grid with objects obscured and successively click on blue squares to reveal โ€˜landmarkโ€™ objects at the location. After 16 clicks have been completed, a yellow square appears. Clicking on the yellow square reveals the โ€˜goalโ€™ object for the trial. Bottom: schematic diagram of the navigation phase of each trial. Participants start in a random, previously unobserved location and are tasked with navigating to the โ€˜goalโ€™ object they had just learnt about (displayed at the top). They can navigate in two ways. First, they could choose a direction to travel in by clicking on the corresponding arrow (highlighted yellow). This is analogous to using a โ€˜vector-basedโ€™ strategy. Alternatively, they could choose an adjacent state to travel to by clicking on one of the associated images (displayed in a random order; highlighted blue). This corresponds to using a โ€˜transition-basedโ€™ navigation strategy.

Task design and experimental set-up. Top left: underlying structure of the 8 ร— 8 grid, unseen by participants. Every state is represented by an image of an object, and these objects and their positions change on every trial. Top right: schematic diagram of the โ€˜map readingโ€™ phase of each trial. Participants see a topโ€“down view of the grid with objects obscured and successively click on blue squares to reveal โ€˜landmarkโ€™ objects at the location. After 16 clicks have been completed, a yellow square appears. Clicking on the yellow square reveals the โ€˜goalโ€™ object for the trial. Bottom: schematic diagram of the navigation phase of each trial. Participants start in a random, previously unobserved location and are tasked with navigating to the โ€˜goalโ€™ object they had just learnt about (displayed at the top). They can navigate in two ways. First, they could choose a direction to travel in by clicking on the corresponding arrow (highlighted yellow). This is analogous to using a โ€˜vector-basedโ€™ strategy. Alternatively, they could choose an adjacent state to travel to by clicking on one of the associated images (displayed in a random order; highlighted blue). This corresponds to using a โ€˜transition-basedโ€™ navigation strategy.

How do humans navigate unfamiliar environments? @denislan.bsky.social @lhuntneuro.bsky.social @summerfieldlab.bsky.social show that humans & deep meta-learning networks combine โ€˜vector-basedโ€™ & โ€˜transition-basedโ€™ strategies for flexible navigation in similar ways @plosbiology.org ๐Ÿงช plos.io/45uSwNm

01.08.2025 08:27 โ€” ๐Ÿ‘ 9    ๐Ÿ” 2    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 1

Absolute thrill to be part of this team and to be able to piggy-back on this post

28.06.2025 07:48 โ€” ๐Ÿ‘ 3    ๐Ÿ” 0    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0

Hot off the press, by my brilliant colleague Ashley Zhou

26.06.2025 07:35 โ€” ๐Ÿ‘ 4    ๐Ÿ” 0    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0

Last chance to have a chat about naturalistic decision-making by my poster! #OHBM2025

26.06.2025 04:43 โ€” ๐Ÿ‘ 3    ๐Ÿ” 0    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0

Just arrived in Brisbane with the loveliest of teams. Can't wait to connect with fellow neuronerds at #OHBM2025!

23.06.2025 01:20 โ€” ๐Ÿ‘ 3    ๐Ÿ” 1    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0
Post image

Our work, out at Cell, shows that the brainโ€™s dopamine signals teach each individual a unique learning trajectory. Collaborative experiment-theory effort, led by Sam Liebana in the lab. The first experiment my lab started just shy of 6y ago & v excited to see it out: www.cell.com/cell/fulltex...

11.06.2025 15:17 โ€” ๐Ÿ‘ 211    ๐Ÿ” 71    ๐Ÿ’ฌ 7    ๐Ÿ“Œ 2
Preview
Neural dynamics of an extended frontal lobe network in goal-subgoal problem solving Complex behavior calls for hierarchical representation of current state, goal, and component moves. In the human brain, a network of โ€œmultiple-demandโ€ (MD) regions underpins cognitive control. We reco...

Now out ๐Ÿšจ ๐Ÿงช : our preprint describing dynamics of an extended frontal lobe network (4 cortical regions) in monkeys solving complex multi-step spatial problems! We observe distributed codes for goals, states, and planned moves across PFC!

www.biorxiv.org/content/10.1...
#neuroscience #compneuro

๐Ÿงต๐Ÿ‘‡

29.05.2025 09:55 โ€” ๐Ÿ‘ 43    ๐Ÿ” 11    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 0

@ozvardal is following 20 prominent accounts