March 2024

Two PhD students from the Team will be presenting onging work at the first Representation Alignment workshop at ICLR this year! Niklas Mueller will show how enrichting convolutional neural networks with filters inspired by human pre-cortical visual processing affect alignment with human EEG data, while Clemens Bartnik will look at the alignment of deep networks with human navigational affordance perception using various XAI methods. Looking forward to the meeting and to discussing our work with other representational alignment-enthusiasts in Vienna in May!

January 2024

Amber Brands' paper just got accepted to Cosyne 2024! She will presenting her latest study in which we study effects of contrast gain and temporal adaptation on object recognition of objects embedded in noise, showing that CNNs endowed with delayed divisive normalization predict human behavior and EEG responses better than additive suppression or recurrent models. Congratulations Amber! 

January 2024

I'm looking forward to visiting Grenoble next month to give a keynote lecture on understanding scene perception in the human brain using computational models! Very excited to be invited and to hear about all the research at this annual meeting of vision researchers in France.  

January 2024

The new year is off to a good start with the publication of a new paper that is the result of a collaboration with Tessa Dekkers's Child Vision Lab at UCL! We studied the development of top-down influences on visual perception using the well-known Mooney paradigm. We confirm earlier indications that the top-down effects on perception of two-tone images Mooney images emerges late in development and moreover, that CNNs trained on object recognition fail to recognize such images, resembling young children's perception more than adult perception.

December 2023

A symposium proposed by Lina Teichmann from Chris Baker's lab at NIH was accepted at VSS 2024! I will be one of the speakers discussing temporal dynamics of visual processing. Looking forward to it!

November 2023

Our review on scene perception in the human brain is just out in the Oxford Research Encyclopedia or Neuroscience! We discuss object-, space- and affordance-centered representations of scenes, and summarize behavioral, fMRI and M/EEG evidence for their presence in the human brain, whilst also discussing how computational modeling and deep learning can help elucidate scene representation.

October 2023 

I have another PhD opening as part of our new lab focusing on human-aligned video AI that is funded by the Data Science Center Lighthouse grant! We are looking for an ambitious and motivated MSc with a background in AI and strong interest in cognitive (neuro-)science who is interested in studying the overlap between human and machine visual cognition in the video domain. The job description and application details are here; application deadline is Dec. 22nd!  

Sept 2023

In this new ECoG study done in collaboration with New York University and led by PhD student Amber Brands, we measured and modeled temporal dynamics of adaptation to naturalistic images at millisecond resolution in human cortex. We show that a simple augmentation to our delayed normalization (DN) model allows it to capture multiple adaptation patterns to different image classes. We show that higher visual areas show slower temporal integration and recovery from adaptation, which we attribute to slower normalization dynamics. 

September 2023 

I'm looking forward to give a talk in the Representational Alignment session at this year's edition of Neuromonster, the International Symposium on the Mathematics of Neuroscience!

August 2023 

The study showing that alpha oscillations in visual cortex are tuned to specific spatial locations as evidenced by population receptive field (pRF) modeling , led by Ken Yuasa from NYU, is now accepted at ELife!

July 2023 

I have a PhD opening that is funded through the ELLIS Unit Amsterdam! We are looking for an enthusiastic MSc with a background in machine learning/ AI interested in studying the overlap between human and machine representations. The job description and application details are here; application deadline is Aug. 26th!  

July 2023 

Together with a number of PIs from other UvA institutes, we have obtained funding from the UvA Data Science Center to start a new lab focusing on human-aligned video AI! The lab will fund 7 PhD positions, one of will be jointly supervised by me and Pascal Mettes. We'll start recruiting PhD students later this year, stay tuned!

June 2023 

I will be closing off a workshop on Brain-Inspired Computing taking place at TU Eindhoven on June 5th with the talk 'From the brain to the neural network and back' reviewing how contemporary deep learning is inspired by neuroscience, to what extent it can be said to be a good model of brain processing, and how state-of-the-art DL is used for brain decoding and image and speech reconstruction. 

May 2023 

Three papers submitted by the PhD students in my Team were all accepted to be presented at the Conference on Cognitive Computational Neuroscience (CCN 2023) in Oxford later this year! We're excited and looking forward to the meeting. 

February 2023 

Our ECoG paper on temporal dynamics in human visual cortex was selected to be part of the journals Spotlight section, which "highlights articles that our reviewers gave the highest marks for both methodological merit and significance".  I'm honored by the distinction and proud of this achievement! Later this year the paper and its will also be highlighted in the  journal's NeuroCurrent podcast (preparations underway).

February 2023 

As part of the Brain Initiative project that funded my post-doc at NYU, we collected a lot of rich and interesting ECoG data. In this paper, led by Ken Yuasa (another post-doc in the Winawerlab), we show that is possible to estimate population receptive field from alpha power changes in visual cortex, indicating that alpha oscillations can be spatially tuned. 

Oct 2022

The ECoG paper on temporal dynamics in visual cortex that I started during my post-doc at NYU is now out in Journal of Neuroscience! We characterized how the time course of visual responses measured inside many areas of visual cortex changes when the dynamics of the input change, and show we can predict these changes using a simple computational model of delayed divisive normalization. Here's a Twitter thread summarizing the main findings.

September 2022

I will be giving an invited talk in the NeurIps 2022 workshop Shared Visual Representations in Humans and Machine Intelligence that will take place in December (https://www.svrhm.com). Excited to be among an excellent set of speakers at this interdisciplinary workshop!

August 2022

I'll be giving a tutorial talk on Using temporal encoding models to model ECoG data at the European Conference on Visual Perception (https://2022.ecvp.eu/tutorials/) later this month. Looking forward to what promises to be an excellent session and conference!

February 2022

Steven Scholte and I are now accepting applications for a new PhD position funded by the UvA's Data Science Center's Interdisciplinary PhD Programme! You can find details on the position and how to apply on the UvA's vacancy website and on academic transfer. Feel free to email me with inquiries on the position. Looking forward to hearing from you!

January 2022

This new review paper in Trends in Cognitive Sciences is the result of a really fun collaboration with Tomas Knapen (VU), Tessa Dekker (UCL) and Edward Silson (U Edinburgh)! We review evidence for visuospatial coding throughout the brain and discuss the role that visuospatial coding plays in higher-order perception, cognitive development and action-perception integration. We propose that visuospatial coding (our window onto the world) is not thrown away by the brain but rather is retained to facilitate the exchange of visual information with other functional systems to the benefit of cognition. 

November 2021

Pleased to announce that together with Steven Scholte from the Dept. of Psychology, I was awarded a grant from the UvA's Data Science Center (DSC) to hire a PhD student to work on integrating precortical processing models of vision with deep learning. The recruitement ad will be posted soon!

October 2021 

The preprint we posted last May was just accepted for publication in a special issue in Brain Structure and Function. You can find the pdf and online version here. 

October 2021

I was accepted as a member representing the University of Amsterdam in the Europe-wide collaborative AI network ELLIS (European Lab for Learning and Intelligent Systems). Looking forward to setting up new collaborations through this platform!

August 2021 

In this ECoG study done in collaboration with New York University and University Medical Center Utrecht, we measured and modeled temporal dynamics of visual responses at millisecond resolution in human cortex. We show that a simple computational model predicts a wide variety of complex neural response shapes that we induced experimentally by manipulating the duration, repetition and contrast of visual stimuli.  By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the human brain processes dynamic sensory information.   

July 2021

Amber and Clemens will be attending ECVP 2021  and presenting work from their PhDs for the first time! Check out the program here: Amber will presenting "Adaptation of neural responses to naturalistic visual categories in low- and high-level visual cortex" on Monday Aug 23rd, 11:00am CEST and Clemens will be presenting "Human Perception of Navigational Affordances in Real-world Scenes" on Wednesday Aug 25th, 11:00 am CEST. 

May 2021

In this fMRI study, we performed a direct comparison of the relative visual field position of stimuli (contra- vs ipsilateral) and category (face or scene) to determine which of these two drives fMRI responses more strongly throughout visual cortex. Our results suggest that ventral-temporal visual regions are less position-sensitive than lateral-occipital regions, and that the 'transition' between category vs. position-dominance does not map cleanly onto known boundaries of retinotopic or category-selective cortex. 

February 2021

Our study on the effect of theta-burst TMS on fMRI responses in category-selective brain regions in visual cortex is now out in NeuroImage! See this twitter thread for a short summary of the findings plus some extra information on our publication process for this paper, for which the data were collected during my first post-doc at NIH. 

January 2021

I'll be presenting our work on temporal dynamics again at Cosyne next month. Happy our abstract was accepted given that only about 60% of submissions could be accepted! I'll be presenting in Poster session 1 on Wednesday Nov 24th. 

November 2020

The talk I gave last month at Neuromatch 3.0 on the temporal dynamics of ECoG responses in visual cortex was recorded and can be freely watched online! It can be found here on Neuromatch's YouTube channel starting at 1.32.05 hrs in.  The talk is about 12 minutes + a few minutes of questions. A cut-out recording of each talk separately should be made available soon!

August 2020

Happy to share this preprint on a labor intensive experiment (4 fMRI sessions per subject!). Our findings suggest that the effect of TMS on fMRI responses to visual stimuli is not as specific as we might have expected from behavioral TMS findings, raising questions about the separability of cortical visual information processing networks with theta-burst fMRI.

July 2020

In collaboration with colleagues from Utrecht University and Lausanne we found evidence that neural responses to visual and tactile stimuli co-localize in visual cortex. I contributed only a small part (to the computational modeling of the visual responses), but the results provide an interesting case study of how sensory information processing can be input modality independent. Plus it's my first contribution to an ECoG paper! 

July 2020

I co-authored a paper by Noor Seijdel and colleagues at the University of Amsterdam on the influence of scene statistics on perception. We found that image complexity as reflected in image statistics affects model parameters such as drift rate (rate of evidence accumulation) and boundary in drift diffusion decision-making models fitted to reaction time data when human observers perform a rapid object categorization task.  The image statistics themselves were task-irrelevant, but they still had a strong influence on behavior. This suggests that in naturalistic settings (i.e. when viewing real-world images), very basic, low-level properties of our natural visual environment influence perceptual decision-making!

June 2020

The annual Vision Sciences Society meeting went online this year. I presented a poster along with a walkthrough on my ongoing work  at NYU. The full presentation can be found on YouTube! 

June 2020 

The advertisements are up! I am looking for two motivated candidates to study visual representations in the human brain with deep neural networks. Please follow either one of these links for more information and to apply: academic transfer and UvA vacancy.

November 2019

I am pleased to announce that next year I will be starting as an assistant-professor at the Faculty of Science of the University of Amsterdam sponsored by a MacGillavry Fellowship! I'm very excited about entering a new phase and starting my own research group in 2020.

July 2019

I was awarded a Veni grant from the Netherlands Organisation for Scientific Research to study natural scene representation in the human brain! The grant will officially kick off in 2020.

May 2019

In this paper, we tested how well human groupings of naturalistic images was reflected in patterns of fMRI activity in visual cortex. Contrary to what is commonly assumed, there was not a clear-cut mapping of the brain responses in ventral-temporal cortex to behavior, and comparisons with deep network models suggested that activity in these regions reflected lower level processing than what guided behavior. This suggests there's still a lot we don't understand about the representations in higher-order visual regions, especially not for naturalistic images! Note that the stimuli and data are freely available so others can test more models of visual representation against these behavioral and fMRI data!

March 2019

I received the NYU Faculty of Arts and Sciences Postdoctoral Travel Award to sponsor my attendance at OHBM this year! I will be presenting our ECoG and fMRI work on temporal dynamics in visual cortex, in both a poster and a (selected) talk session. 

March 2019

I received a FoVea Travel and Networking Award to sponsor my attendance at VSS this year! FoVea aims to promote women in vision science and increase their visibility. I am very honored and grateful that they chose to support my career in this way. Thanks Fovea!

Jan 2019

On February 21st 2019, I will be giving an invited talk at the 5th CiNet Conference themed ‘Computation and Representation in Brains and Machines’, Center for Information and Neural Networks (CiNet) in Osaka, Japan. 

I'm very excited to be among this line-up of esteemed speakers! It promises to be a very interesting meeting.

Jan 2019

Chris Baker, and I wrote a Neuron Preview for this recent paper published by Lescroart and Gallant on modeling scene representations. 

Dec 2018

It took a while, but I finally published the last chapter of my PhD thesis! The wonderful Sara Jahfari and I  led this project together, looking at the influence of scene complexity (as determined by low-level image statistics) on detection of animal in natural scenes.  It turns out that scene complexity affects the degree of evidence accumulation (as formalized in a drift diffusion) which for highly complex scenes appears to be driven by feedback activity.

March 2018 

I'm excited to announce that our collaboration with scene perception experts Michelle Greene, Chris Baldassano, Diane Beck and Fei-Fei Li resulted in a publication in eLife! 

In this paper, we tested how well scene categorization behavior and patterns of fMRI activity in scene-selective cortex could be explained by three different models of scene information, quantifying the unique contributions of each. We found that the relative contributions of each model differ depending on whether you're looking at behavior or the brain - suggesting we have more work to do in terms of developing computational models that can explain both behavior and neural responses in the human brain.