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Susan Ajith

@suzibot.bsky.social
199 followers 220 following 21 posts

🌱 PhD with @dkaiserlab.bsky.social | studying high-level vision and individual priors | prev IIT-GN, IN

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Susan Ajith @suzibot.bsky.social · 12/10/2026
Congrats, Dr Tim!! 🥳🚀
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Susan Ajith @suzibot.bsky.social · 17/09/2026
Congratss 🥳
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Rico Stecher @ricostecher.bsky.social · 03/09/2026
The final preprint of my PhD is out! We present a neuro-computational approach that can approximate mental images and allows us to assess their qualities without introspection. We evaluated this approach on a large-scale EEG data set (43,200 trials). (1/n) www.biorxiv.org/content/10.6...
biorxiv.org
A neuro-computational approximation of the qualities of mental images
Mental images are challenging to study, given that our conscious experience is notoriously hard to access. The currently prevalent introspective methods are inherently subjective and can thus only pro...
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Susan Ajith @suzibot.bsky.social · 29/08/2026
5/5 Critically, shared representations emerge between the Ball-only and Occluder conditions. Earlier time points in the Occluder condition predicted the ball's future position in the Ball-only condition: "ahead of time" neural coding under occlusion!
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Susan Ajith @suzibot.bsky.social · 29/08/2026
4/5 Using MVPA, we find alpha-band activity carries direction-specific motion information, both within and across conditions.
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Susan Ajith @suzibot.bsky.social · 29/08/2026
3/5 Behavioral and EEG results converge! Participants reported the ball's position ahead of its true path, especially during occlusion. Errors weren't random: they followed the direction of ongoing motion!
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Susan Ajith @suzibot.bsky.social · 29/08/2026
2/5 Participants viewed a ball falling through differently curved pipes (pipe condition). We compared this to 2 conditions: only the ball trajectory visible (Ball-only), or the pipe completely hidden (Occluder). On probe trials, the video paused and participants marked the ball's last position.
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Susan Ajith @suzibot.bsky.social · 29/08/2026
How does the brain track an object even when it is occluded and in constrained, non-linear motion? 👁️🧠 In a new preprint, we use EEG+behavior to study how we mentally track motion (w/ @dkaiserlab.bsky.social, @luchunyeh.bsky.social, @kathadobs.bsky.social,...) www.biorxiv.org/content/10.6... 1/5 🧵
biorxiv.org
Cortical alpha rhythms predictively track occluded motion trajectories
Objects in the real world frequently move along complex, non-linear trajectories shaped by their environment. As they do, they often pass temporarily out of sight, occluded by the surrounding environm...
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Susan Ajith @suzibot.bsky.social · 05/06/2026
Persepolis made a huge impact growing up! RIP
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Katharina Dobs @kathadobs.bsky.social · 15/05/2026
It's #VSS2026 time! We're super excited to be back and presenting some exciting, ongoing projects in the lab. Come by and say hi! 🤗
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Sander van Bree @sandervanbree.bsky.social · 14/05/2026
Are you attending #VSS2026? Come check out my talk on cross-species alignment for finding shared and distinct representational geometries in primate IT. Saturday, May 16, 2026, 3.30pm, Talk Room 1
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Susan Ajith @suzibot.bsky.social · 14/05/2026
Come to my talk for some fun experiments combining drawings, DNNs and visual search! 👀🧠⛱️
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Maëlle Lerebourg @maellelerebourg.bsky.social · 04/05/2026
What do we look for when searching for objects in our daily-life environments? Very happy that I can now share this review, together with @suryagayet.bsky.social , @predictivebrain.bsky.social and @peelen.bsky.social🥳 A brief thread below!
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Lenny van Dyck @levandyck.bsky.social · 24/02/2026
How segregated vs. integrated are face and body representations in human visual cortex? In this new preprint with @kathadobs.bsky.social, we use DNNs and fMRI to find out. www.biorxiv.org/content/10.6... #neuroskyence 🧵 1/n
biorxiv.org
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Mustafa Alperen Ekinci @alpekinci.bsky.social · 12/02/2026
New preprint! Why do people disagree about what looks beautiful, even when viewing the same stimulus? We show that shared aesthetic experience is linked to shared gaze during naturalistic viewing: www.biorxiv.org/content/10.6... 1/4
biorxiv.org
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Kaiser Lab @dkaiserlab.bsky.social · 10/02/2026
📢 Workshop announcement. We are super excited to announce the workshop Perceptual Inferences, from philosophy to neuroscience, organized by Alexander Schütz and Daniel Kaiser. 📍 Rauischholzhausen Castle, near Marburg, Germany 🗓️ June 8 to 10, 2026. 1/4
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Lu-Chun Yeh @luchunyeh.bsky.social · 09/02/2026
Check out our new preprint! 🎉 We demonstrate that real-world object search is shaped by both objects’ inherent variability and searchers’ individual priors, using a new approach that combines human drawings with DNN representational similarity analysis. ✍️🖥️👀
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Susan Ajith @suzibot.bsky.social · 09/02/2026
8/8 To sum it up, real world search depends on both what you’re looking for and who is looking. Inherent object variability and individual experience with that variability shapes how efficiently we find things in the real world.
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Susan Ajith @suzibot.bsky.social · 09/02/2026
7/8 Finally, do individuals guide attention using their own unique object templates? If so, individual differences should be strongest for the most prioritised template (i.e., first drawing). Indeed, targets more similar to a participant’s own first drawing predict their search the most! 🚶‍♂️👁️
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Susan Ajith @suzibot.bsky.social · 09/02/2026
6/8 Do individuals prioritise specific object forms in their templates? If drawing order reflects prioritisation, earlier drawings should predict faster search with higher target-template match. By relating target-template similarity to search time, we find first drawing predicts search the most!
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Susan Ajith @suzibot.bsky.social · 09/02/2026
5/8 But could variability be individual-specific? When searching for a shoe, I might prioritise a sneaker, while someone else looks for a boot. To test this, we look at drawings of each individual. Here, participants make 4 drawings of each object (1-4), followed by a visual search task.
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Susan Ajith @suzibot.bsky.social · 09/02/2026
4/8 To test this, we run a visual search task for 200 real-world objects on an independent set of participants. Voila! As predicted, when an object category is more variable, search takes longer and when it’s less variable, search is faster.
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Susan Ajith @suzibot.bsky.social · 09/02/2026
3/8 We use drawings as a window into object variability. By looking at human object drawings and measuring similarity between drawings with a DNN, we capture variability across object categories. This gives us an index of object variability. Our key question: does variability influence search?
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Susan Ajith @suzibot.bsky.social · 09/02/2026
2/8 If so, objects with little variability (balls) should activate narrow templates that enable efficient search. In contrast, highly variable categories (shoes) should activate broader templates, making search less efficient. But how do we measure variability in templates of real-world objects?
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Susan Ajith @suzibot.bsky.social · 09/02/2026
Real-world objects vary a lot in how they look. Some categories like balls or rackets are relatively consistent, while others like shoes or bags come in many forms (stilettos, boots, sneakers). Could this inherent variability affect the precision of target templates as we search for them?
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Susan Ajith @suzibot.bsky.social · 09/02/2026
🧨 Preprint alert Is it easier to find a ball than a shoe? The answer lies in how variable we think these objects are in the real-world. www.biorxiv.org/content/10.6... w/ the amazing @dkaiserlab.bsky.social & @luchunyeh.bsky.social 🦄 🧵1/8
biorxiv.org
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Davide Cortinovis @davidecortinovis.bsky.social · 21/12/2025
Now in press at Nature Communications! www.nature.com/articles/s41... Check it out if you are interested in category selectivity, the organization of visual cortex, and topographic models!
nature.com
Investigating action topography in visual cortex and deep artificial neural networks - Nature Communications
This study shows that interaction with objects is an important dimension that shapes the way object categories such as hands and tools are organized in visual cortex and shows that artificial neural n...
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Lu-Chun Yeh @luchunyeh.bsky.social · 16/12/2025
🚨 New preprints out!🚨 Excited to share two new preprints from my #MSCA project. With Daniel @dkaiserlab.bsky.social , Marius @peelen.bsky.social , and Belma Seferovic, we show how contextual associations shape real-world object representations and guide everyday visual task performance. 👇👇👇 1/n
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Micha Engeser @michaengesee.bsky.social · 04/12/2025
I’m excited to share the first preprint from my PhD project! Together with Daniel Kaiser (@dkaiserlab.bsky.social), we investigated how internal models shape inter-individual differences in the perception and neural processing of natural scenes. Preprint: osf.io/preprints/ps... 1/n
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Sander van Bree @sandervanbree.bsky.social · 02/12/2025
New Correspondence with @davidpoeppel.bsky.social in Nat Rev Neurosci. www.nature.com/articles/s41... Here, we critique a recent paper by Rosas et al. We argue that "Bottom-up" and "Top-down" neuroscience have various meanings in the literature. PDF: rdcu.be/eSKYI
nature.com
Top-down and bottom-up neuroscience as collections of practices - Nature Reviews Neuroscience
Nature Reviews Neuroscience - Top-down and bottom-up neuroscience as collections of practices
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Fernanda Ribeiro @felenitaribeiro.bsky.social · 01/12/2025
Investigating individual-specific topographic organization has traditionally been a resource-intensive and time-consuming process. But what if we could map visual cortex organization in thousands of brains? Here we offer the community with a toolbox that can do just that! tinyurl.com/deepretinotopy
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Sam Gershman @gershbrain.bsky.social · 14/10/2025
Really interesting work by Bakhurin and colleagues challenging the reward prediction error hypothesis of dopamine: www.nature.com/articles/s41... I love this figure which both echoes and undermines the famous figure from Schultz et al. (1997).
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Susan Ajith @suzibot.bsky.social · 08/10/2025
How can we characterize the contents of our internal models of the world? We highlight participant-driven approaches, from drawings to descriptions, to study how we expect scenes to look! 🤩
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Susan Ajith @suzibot.bsky.social · 26/06/2025
Go Lu! 💃💜
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Lenny van Dyck @levandyck.bsky.social · 18/06/2025
How is high-level visual cortex organized? In a new preprint with @martinhebart.bsky.social & @kathadobs.bsky.social, we show that category-selective areas encode a rich, multidimensional feature space 🌈 www.biorxiv.org/content/10.1... #neuroskyence 🧵 1/n
biorxiv.org
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Kaiser Lab @dkaiserlab.bsky.social · 22/05/2025
#VSS2025 was a blast - great science, fun people, beach vibes. We‘ll be back! @vssmtg.bsky.social
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Susan Ajith @suzibot.bsky.social · 03/03/2025
It's very little we understand! There's the data gap but also very little done about the known and existing gaps
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