Kaiser Lab

Kaiser Lab

@dkaiserlab.bsky.social

Studying natural vision at JLU Giessen using psychophysics, neuroimaging, and computational models, PI: Daniel Kaiser. danielkaiser.net

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Kaiser Lab
@dkaiserlab.bsky.social

Hello Bluesky! This is the Kaiser Lab. We are cognitive neuroscientists studying the neural computations that support real-world vision using fMRI, EEG, and TMS. Our main research areas include individual differences, categorization, and aesthetics. For more information: danielkaiser.net

Kaiser Lab
@dkaiserlab.bsky.social

🚨New paper alert: "Visual features explain dynamic aesthetic experiences across distinct movie content" 👀🧠

Mustafa Alperen Ekinci@alpekinci.bsky.social

The first paper of my PhD work! We show that our aesthetic experiences while watching movies can be partly explained by shared perceptual mechanisms: a combination of image-based visual features predicts our moment-to-moment aesthetic experiences, even across different movies.

Kaiser Lab
@dkaiserlab.bsky.social

🚨 Preprint alert! 🚨 Check out @ricostecher.bsky.social's new preprint: "A neuro-computational approximation of the qualities of mental images."

Rico Stecher@ricostecher.bsky.social

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.orgA neuro-computational approximation of the qualities of mental imagesMental 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...
Kaiser Lab
@dkaiserlab.bsky.social

🚨 New paper alert! "Cortical alpha rhythms predictively track occluded motion trajectories" 👁️🧠 by @suzibot.bsky.social.

Susan Ajith@suzibot.bsky.social

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.orgCortical alpha rhythms predictively track occluded motion trajectoriesObjects 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...
Kaiser Lab
@dkaiserlab.bsky.social

🚨New paper alert: "Spatiotemporal Representations of Contextual Associations for Real-World Objects" 👀🧠

Lu-Chun Yeh@luchunyeh.bsky.social

🚨Out now in J Neurosci! 🧠 Using fMRI and EEG, we mapped where and when contextual knowledge of real-world objects emerges within the visual system - even when those objects are viewed in isolation. @dkaiserlab.bsky.social @peelen.bsky.social www.jneurosci.org/content/46/1...

jneurosci.orgSpatiotemporal Representations of Contextual Associations for Real-World ObjectsIn the real world, objects always appear in context. Many objects are reliably associated with a certain scene context (e.g., pots appear in kitchens) and other objects that appear in the same context...
Kaiser Lab
@dkaiserlab.bsky.social

New paper alert 🚨👀 Check out @ilkrdymz.bsky.social's paper: "Abrupt scene onsets and gradually emerging scene information produce distinct EEG decoding dynamics".

Ilker Duymaz@ilkrdymz.bsky.social

New paper! We compared EEG decoding for scenes that appeared abruptly versus scenes emerging gradually during continuous visual input. Takeaway: Presentation context matters when interpreting EEG decoding time courses. With @michaengesee.bsky.social and Daniel Kaiser. doi.org/10.1152/jn.0...

doi.orgAbrupt scene onsets and gradually emerging scene information produce distinct EEG decoding dynamics | Journal of Neurophysiology | American Physiological SocietyMultivariate analyses of magneto-/electroencephalography (M/EEG) data are typically performed on neural responses time-locked to discrete stimulus onsets. Such designs usually reveal high decoding performance during the initial transient response (0–500 ms), which subsequently drops to a lower, sustained level. Here, we examined time-resolved EEG decoding of natural scene processing when scenes gradually enter the visual field without a clear onset. We created video sequences in which one scene category (e.g., a beach) smoothly transitioned into another category (e.g., a forest) by blending two scenes into a single composite panorama and moving a square aperture across it. We compared EEG decoding for the first scenes within the transitions, which appeared with a sudden, artificial onset, to the second scenes, which emerged naturalistically as the videos progressed. For the first scenes, we observed robust category decoding from 60 ms after onset with a clear peak structure. For the second scene, category decoding was markedly weaker and showed no discernible peak structure. Realigning the appearance of category-diagnostic content for the second scene using deep neural networks did not enhance decoding or recover a peak structure. Furthermore, classifiers trained on the first scene generalized to the second, but with a broad, temporally diffuse pattern, instead of a diagonal pattern more consistent with a shared hierarchical processing timeline. Together, these findings demonstrate that time-resolved EEG decoding is sensitive to stimulus-presentation context. Accordingly, temporal decoding patterns obtained in conventional trial-based paradigms may not generalize unchanged to conditions involving gradual scene transitions and continuous visual input. NEW & NOTEWORTHY Using multivariate EEG decoding, we show that scene-category information follows different temporal profiles across two presentation regimes: abrupt scene appearance after a grayscale screen and gradual scene emergence during continuous visual input. Our findings demonstrate that time-resolved decoding is sensitive to stimulus-presentation context and should not be interpreted as an invariant signature of a fixed visual processing hierarchy.

Kaiser Lab reposted

Susan Ajith
@suzibot.bsky.social

Come to my talk for some fun experiments combining drawings, DNNs and visual search! 👀🧠⛱️

Kaiser Lab@dkaiserlab.bsky.social

Kaiser Lab is at @vssmtg.bsky.social with 6 posters and 3 talks! 👁️🏖️☀️ Come check out our works!

Kaiser Lab reposted

Micha Engeser
@michaengesee.bsky.social

If you're at #VSS2026 come check out our posters and talks! On Saturday 6:45 pm I'll present my talk on individual differences in scene perception.

Kaiser Lab@dkaiserlab.bsky.social

Kaiser Lab is at @vssmtg.bsky.social with 6 posters and 3 talks! 👁️🏖️☀️ Come check out our works!

Kaiser Lab
@dkaiserlab.bsky.social

📢 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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Kaiser Lab
@dkaiserlab.bsky.social

4/4 Participation fee is 240 €, covering accommodation and meals during the workshop. Travel to Rauischholzhausen is organized individually. Registration deadline is March 8, 2026.

Kaiser Lab
@dkaiserlab.bsky.social

📢 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

Kaiser Lab
@dkaiserlab.bsky.social

2/4 The workshop covers diverse aspects of perceptual inferences and how they shape our conception of the world. Talks by exciting international speakers span philosophy, behavioral and neuroimaging work, ranging from low level vision and social perception to unconscious processing.

Kaiser Lab
@dkaiserlab.bsky.social

🚨 Preprint alert! 🚨 Check out @suzibot.bsky.social's preprint: “Visual search is constrained by the variability of object-category templates.” Includes some neat findings on individual differences in search 👀

Susan Ajith@suzibot.bsky.social

🧨 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.orgbiorxiv.org
Kaiser Lab
@dkaiserlab.bsky.social

🚨 Preprint alert! 🚨

Lu-Chun Yeh@luchunyeh.bsky.social

🚨 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

Kaiser Lab
@dkaiserlab.bsky.social

Check out @michaengesee.bsky.social 's preprint on individual differences in expectations about natural scenes and how they shape how we perceive and neurally represent scenes. 👁️🧠👨‍🦱👩‍🦰👩‍🦳

Micha Engeser@michaengesee.bsky.social

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

Kaiser Lab reposted

Susan Ajith
@suzibot.bsky.social

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! 🤩

Kaiser Lab@dkaiserlab.bsky.social

From line drawings to scene perception — our new review argues for moving beyond experimenter-driven manipulations toward participant-driven approaches to reveal what’s in our internal models of the visual world. 👁️✍️🛋 royalsocietypublishing.org/doi/10.1098/...

royalsocietypublishing.orgCharacterizing internal models of the visual environment | Proceedings of the Royal Society B: Biological SciencesDespite the complexity of real-world environments, natural vision is seamlessly efficient. To explain this efficiency, researchers often use predictive processing frameworks, in which perceptual effic...

Kaiser Lab reposted

Micha Engeser
@michaengesee.bsky.social

In this paper we present flexible methods for participants to express their expectations about natural scenes.

Kaiser Lab@dkaiserlab.bsky.social

From line drawings to scene perception — our new review argues for moving beyond experimenter-driven manipulations toward participant-driven approaches to reveal what’s in our internal models of the visual world. 👁️✍️🛋 royalsocietypublishing.org/doi/10.1098/...

royalsocietypublishing.orgCharacterizing internal models of the visual environment | Proceedings of the Royal Society B: Biological SciencesDespite the complexity of real-world environments, natural vision is seamlessly efficient. To explain this efficiency, researchers often use predictive processing frameworks, in which perceptual effic...
Kaiser Lab
@dkaiserlab.bsky.social

Go Lu!! Congratulations 💜

Lu-Chun Yeh@luchunyeh.bsky.social

Honored and thrilled to receive the GGN Early Career Award @jlugiessen.bsky.social 🏆 Huge thanks to my awesome supervisors Daniel @dkaiserlab.bsky.social & Marius @peelen.bsky.social , all my collaborators, and the amazing colleagues from both labs — couldn’t have done it without you! 💗

Kaiser Lab
@dkaiserlab.bsky.social

Kaiser Lab goes #Exzellenz! The excellence cluster „The Adaptive Mind“ got funding for the next 7 years! Proud to be part of this awesome team and looking forward to all the exciting research to come. 🎆✨🥂

Kaiser Lab reposted

Lu-Chun Yeh
@luchunyeh.bsky.social

How fast do we extract distance cues from scenes 🛤️🏞️🏜️ and integrate them with retinal size 🧸🐻 to infer real object size? Our new EEG study in Cortex has answers! w/ @dkaiserlab.bsky.social @suryagayet.bsky.social @peelen.bsky.social Check it out: www.sciencedirect.com/science/arti...

sciencedirect.comThe neural time course of size constancy in natural scenesAccurate real-world size perception relies on size constancy, a mechanism that integrates an object's retinal size with distance information. The neur…

Kaiser Lab reposted

Lu-Chun Yeh
@luchunyeh.bsky.social

Glad to share our EEG study now is out in JNP. 🎉 We showed that alpha rhythms automatically interpolate occluded motion based on the surrounding contextual cues! 🚶‍♂️🏞️ @dkaiserlab.bsky.social journals.physiology.org/doi/full/10....

journals.physiology.orgCortical alpha rhythms interpolate occluded motion from natural scene context | Journal of Neurophysiology | American Physiological SocietyTracking objects as they dynamically move in and out of sight is critical for parsing our everchanging real-world surroundings. Here, we explored how the interpolation of occluded object motion in nat...

Kaiser Lab reposted

Communications Biology
@commsbio.nature.com

Representational shifts from bottom-up gamma to top-down alpha dynamics drive visual integration, highlighting the crucial role of cortical feedback in the construction of seamless perceptual experiences. @lixiangchen.bsky.social @dkaiserlab.bsky.social doi.org/10.1038/s42003-025-08011-0

doi.orgRepresentational shifts from feedforward to feedback rhythms index phenomenological integration in naturalistic vision - Communications BiologyRepresentational shifts from bottom-up gamma to top-down alpha dynamics drive visual integration, highlighting the crucial role of cortical feedback in the construction of seamless perceptual experien...
Kaiser Lab
@dkaiserlab.bsky.social

Now out in @royalsocietypublishing.org Proceedings B! Check out Gongting Wang's EEG work on individual differences in scene perception: Scenes that are more typical for individual observers are represented in an enhanced yet more idiosyncratic way. Link: royalsocietypublishing.org/doi/10.1098/...

royalsocietypublishing.orgEnhanced and idiosyncratic neural representations of personally typical scenes | Proceedings of the Royal Society B: Biological SciencesPrevious research shows that the typicality of visual scenes (i.e. if they are good examples of a category) determines how easily they can be perceived and represented in the brain. However, the uniqu...