News
Speaker at Brain-inspired Computing Workshop
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.
Three papers accepted for CCN 2023
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.
ECoG paper highlighted as JNeurosci Spotlight
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).
New preprint online
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.
New paper in JNeurosci
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.
Speaker at NeurIPS 2022 SVRHM workshop
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!
Tutorial talk at ECVP
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!
PhD opening
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!
New paper in TICS
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.
Data Science grant
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!
New paper in Brain Structure and Function
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.
New preprint online
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.
Two posters at ECVP 2021
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.
New preprint online
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.
TMS-fMRI study published
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.
Presenting at CoSyne
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.
Neuromatch talk online
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!
New preprint: TMS-fMRI in lateral occipital cortex
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.
New ECoG paper in Brain Topography
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!
New paper on scene complexity and decision-making
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!
V-VSS 2020 presentation video
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!
2 PhD positions available
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.
MacGillavry Fellow
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.
Veni grant from NWO
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.
NeuroImage paper out
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!
NYU FAS Travel Award
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.
Talk in Japan
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.
Preview for Neuron
Jan 2019
Chris Baker, and I wrote a Neuron Preview for this recent paper published by Lescroart and Gallant on modeling scene representations.
New paper in PLoS Comp Biol
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.
New paper in eLife!
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.