Vision & Sight Recovery


Presentation of research activities

What makes us perceive and interact with our visual environment the way we do?

This seemingly simple question is, in fact, far from trivial. The simple act of viewing an image can sometimes yield vastly different perceptual interpretations among individuals, even within the same person across different moments in time. The nature of this variability has puzzled researchers and scholars for centuries and remains one of the key problems of vision and cognitive science. In our research, we focus on multiple factors that might contribute to this variability. These include an individual’s prior experiences, the influence of temporal and spatial context, and the intrinsic dynamics of neural activity patterns. These factors may interact in ways that are highly specific to each individual, much like fingerprints, and can vary drastically, particularly in clinical conditions. Our goal is to understand how these factors interact in shaping our moment-to-moment visual abilities, beyond what meets the eye.

To this aim, our research follows two main axes:

  1. Understanding the role of spatial and temporal context in visual perception.
  2. Characterizing the relationship between inter- and intra-individual variability in visual performance and temporal dynamics of neural activity patterns.

Within these frameworks, we use a multidisciplinary approach, integrating studies of human behavior (psychophysics), neural activity (EEG, fMRI, brain connectivity), and computational/brain network modeling. Our research encompasses various topics, from visual perception, attention, and memory, to spatial and temporal processing, brain rhythms, and networks. Our overarching focus is on explaining variability in perceptual performance within and across individuals, including clinical populations.

David Pascucci

David Pascucci studied Experimental Psychology at the University of Florence (Italy) and obtained his Master’s degree in 2009, with a thesis about the integration of auditory and visual signals. In 2014, he earned his Ph.D. in Cognitive Science at the Center for Mind/Brain Sciences (CIMeC, Rovereto, Trento) under the supervision of Prof. Turatto. During his Ph.D., he focused on the mechanisms underlying plasticity and learning in human attention and visual perception, using psychophysics and functional magnetic resonance imaging (fMRI).

He did his first post-doc in 2014-2015 at the Department of Movement and Neurological Sciences, in the lab of Prof. Chelazzi (Emergent Attention Lab, University of Verona), where he investigated the role of temporal context in human vision. From 2015 to 2019, he was a senior post-doctoral fellow in the Perceptual Network Group of Prof. Plomp (University of Fribourg, Switzerland), where he focused on dynamic network approaches to the study of human vision, combining electroencephalography (EEG), MRI, and Granger-causal modeling. During these years, he was also a member of the SNSF Sinergia consortium “Brain Communication Pathways.”

In 2019, he was awarded an SNSF Ambizione grant, which allowed him to join the Brain Mind Institute (EPFL, hosted by the lab of Prof. Herzog) as Principal Investigator, and at the same time, he was a co-PI at the University of Iceland (RANNIS grant, in collaboration with Prof. Árni Kristjánsson).

Starting in 2024, he is an Assistant Professor (SNSF Starting Grant) at the University Hospital of Lausanne (CHUV), the University of Lausanne (UNIL), and The Sense Innovation and Research Center.

Av. de Provence 82
1007 Lausanne


Key publications


Laws of concatenated perception: Vision goes for novelty, decisions for perseverance

Pascucci, D. et al. Laws of concatenated perception: Vision goes for novelty, decisions for perseverance. PLOS Biology 17, e3000144 (2019).

Tuning perception and decisions to temporal context

Blondé, P., Kristjánsson, Á. & Pascucci, D. Tuning perception and decisions to temporal context. iScience 108008 (2023) doi:10.1016/j.isci.2023.108008

Unlocking crowding by ensemble statistics

Tiurina, N. A., Markov, Y., Choung, O.-H., Herzog, M. H. & Pascucci, D. Unlocking crowding by ensemble statistics. Current Biology 32, 4975-4981.e3 (2022).

Alpha peak frequency affects visual performance beyond temporal resolution

Menétrey, M. Q., Roinishvili, M., Chkonia, E., Herzog, M. H. & Pascucci, D. Alpha peak frequency affects visual performance beyond temporal resolution. Imaging Neuroscience 2, 1–12 (2024).

Modeling time-varying brain networks with a self-tuning optimized Kalman filter

Pascucci, D., Rubega, M. & Plomp, G. Modeling time-varying brain networks with a self-tuning optimized Kalman filter. PLOS Computational Biology 16, e1007566 (2020).