CAP Lab

Surya is Assistant Professor in Experimental Psychology at Utrecht University, and the head of the CAP-Lab. He uses behavioral, computational, and neuroimaging methods to investigate human (visual) perception, consciousness, working memory, and attention.

Sam is Assistant Professor in Experimental Psychology and Artificial Intelligence at Utrecht University, and co-PI of the CAP-Lab, where he supervises PhD students Kabir Arora, Dan Wang, and Xiaohua Bao together with Surya. He combines EEG with machine learning techniques and frequency tagging to investigate visual perception, attention, and working memory.

Andre is a PhD candidate, supervised by Stefan van der Stigchel, Chris Paffen, and Surya Gayet. He uses online and lab-based behavioral methods and pupillometry to research naturalistic use of visual working memory.

Luzi is a PhD candidate supervised by Stefan van der Stigchel, Chris Paffen, and Surya Gayet. She uses online and lab-based behavioral methods to investigate how statistical learning influences conscious access, attentional selection, and working memory encoding.

Yichen is a PhD candidate supervised by Nathan van der Stoep and Surya Gayet. He uses psychophysical and neuroimaging (EEG, 7T fMRI) methods to investigate working memory maintenance of multimodal (e.g., audio-visual) stimuli.

​

​

Liangyou is a PhD candidate supervised by Ben Harvey, Serge Dumoulin, and Surya Gayet. He uses 7T fMRI and population receptive field modeling to investigate the influence of attention on the processing of visual quantity (e.g., numerosity) in the human brain.

​

​

Kabir is a PhD candidate supervised by Samson Chota, Stefan van der Stigchel, Leon Kenemans and Surya Gayet. He uses rapid invisible frequency tagging (RIFT) and EEG to investigate the attentional shifts within visual working memory, and between visual working memory and perception.

​

Dan Wang is a PhD candidate supervised by Samson Chota, Stefan van der Stigchel, and Surya Gayet. She uses behavioral methods and EEG to investigate how the influence of visual working memory on perception depends on the (attentional and representational) state of the memorized content.

​

Lasse Dietz is a PhD candidate supervised by Samson Chota, Christoph Strauch, Stefan van der Stigchel, and Surya Gayet. He will combine invisible frequency tagging (RIFT) of EEG data with machine learning to investigate how visual working memory representations change over time, as a function of internal (e.g., strategy) and external (e.g., interference) factors.

Xiaohua is a PhD candidate at Tianjin Normal University, supervised by Yong Lyu, and visiting the lab for a year under the supervision of Surya Gayet and Samson Chota. She investigates the influence of visual working memory of real-world objects on conscious access, using behavioral methods and EEG.

​

After completing her Neuroscience & Cognition research master at Utrecht University, Femke joined the lab as a research assistant supervised by Surya Gayet. She uses 7T fMRI and machine learning techniques to investigate visual working memory storage in the human brain, as a function of the attentional state of the memory content. 

Marleen is working as a research assistant and as an intern in the lab, supervised by Surya Gayet. She uses 7T fMRI and machine learning techniques to investigate the distributed nature of visual working memory storage in the human brain; and she uses behavioral methods to study the role of attention in feature binding during visual working memory maintenance.