Publications related to The effects of visual distractors on serial dependence

Temporal aspects of feature integration in vision

To fully comprehend visual perception, we need to necessarily understand its temporal dimension. Our visual environment is highly dynamic, requiring the processing and integration of temporal signals in order to make sense of it. Many processes, such as th ...

EPFL2024

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

Andrea Rinaldo, Lorenzo Mari, Marino Gatto, Cristiano Trevisin

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to th ...

2024

Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study

Lijing Xin, Kim Do

This study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism ...

Springernature2024

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Fabio Nobile, Tommaso Vanzan

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

2024

Tuning perception and decisions to temporal context

David Pascucci

Recent work suggests that serial dependence, where perceptual decisions are biased toward previous stimuli, arises from the prior that sensory input is temporally correlated. However, existing studies have mostly used random stimulus sequences that do not ...

Cell Press2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Kynthia Chamilothori, Bahar Aydemir, Caroline Karmann, Seungryong Kim

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

OrthoPlanes: A Novel Representation for Better 3D-Awareness of GANs

Siyuan Li, Zhuoqian Yang

We present a new method for generating realistic and view-consistent images with fine geometry from 2D image collections. Our method proposes a hybrid explicitimplicit representation called OrthoPlanes, which encodes fine-grained 3D information in feature ...

Ieee Computer Soc2023

The Cerebellum and Cognitive Function: Anatomical Evidence from a Transdiagnostic Sample

Charles Laidi, Farnaz Delavari

Multiple lines of evidence across human functional, lesion, and animal data point to a cerebellar role, in particular of crus I, crus II, and lobule VIIB, in cognitive function. However, a mapping of distinct facets of cognitive function to cerebellar stru ...

Springer2023

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Henry Markram, Felix Schürmann, James Gonzalo King, Srikanth Ramaswamy, Juan Bautista Hernando Vieites, Alexis Arnaudon, Eilif Benjamin Muller, Michael Reimann, Huanxiang Lu, Ying Shi, Marwan Muhammad Ahmed Abdellah, Vishal Sood, Jean-Denis Georges Emile Courcol, Werner Alfons Hilda Van Geit, Lida Kanari, Juan Luis Riquelme Roman, Michael Emiel Gevaert, Pramod Shivaji Kumbhar, Liesbeth Maria L Vanherpe, Armando Romani, Cyrille Pierre Henri Favreau, Michele Migliore, Mohameth François Sy, Szabolcs Kali, Judit Planas Carbonell, Genrich Ivaska, Sàra Sàray, Carmen Alina Lupascu, Rosanna Migliore, Audrey Mercer, András Ecker, Alberto Antonietti, Cristina Colangelo, Anna-Kristin Kaufmann, Julian Martin Budd, Elisabetta Giacalone, Thomas Brice Delemontex, Davide Bella, Fabien Petitjean, , , , ,

Stronger serial dependence in the depth plane than the fronto-parallel plane between realistic objects: Evidence from virtual reality

David Pascucci

Visual estimates of stimulus features are systematically biased toward the features of previously encountered stimuli. Such serial dependencies have often been linked to how the brain maintains perceptual continuity. However, serial dependence has mostly b ...

2023

Linear Complexity Self-Attention With 3rd Order Polynomials

Filippos Kokkinos, Grigorios Chrysos

Self-attention mechanisms and non-local blocks have become crucial building blocks for state-of-the-art neural architectures thanks to their unparalleled ability in capturing long-range dependencies in the input. However their cost is quadratic with the nu ...

Ieee Computer Soc2023

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

Aesthetic experience enhances first-person spatial representation

Marie Chatel, Mariana Babo Rebelo

Episodic autobiographical memories are characterized by a spatial context and an affective component. But how do affective and spatial aspects interact? Does affect modulate the way we encode the spatial context of events? We investigated how one element o ...

National Academy of Sciences2022

The SparSpec algorithm and the application to the detection of spatial periodicities in tokamaks: from a 1D to a 2D analysis

Duccio Testa

A well-known, previously only 1D, algorithm using the Sparse Representation of Signals and an iterative Block Coordinate Descent method (the SparSpec-1D algorithm) has been further developed and tested in a 2D spatial domain to obtain the toroidal and polo ...

2022

STATNet: Spatial-temporal attention in the traffic prediction

Alexandre Massoud Alahi, Amin Gheibi, Seyed Mohamad Moghadas

Recent traffic flow prediction methods are lacking abilities to determine predictive features. Thus, they will propagate the error in the next timestamps. In this paper, first, we assess the role of spatial and temporal features on the traffic speed predic ...

2022

Selective attention involves a feature-specific sequential release from inhibitory gating

Gijs Plomp, David Pascucci

Selective attention is a fundamental cognitive mechanism that allows our brain to preferentially process relevant sensory information, while filtering out distracting information. Attention is thought to flexibly gate the communication of irrelevant inform ...

2022

Geographic clusters of objectively measured physical activity and the characteristics of their built environment in a Swiss urban area

Stéphane Joost, Cédric Gubelmann, Marco André Vieira Ruas, Idris Guessous

Introduction ...

PUBLIC LIBRARY SCIENCE2022

Sense of self impacts spatial navigation and hexadirectional coding in human entorhinal cortex

Olaf Blanke, Nathan Quentin Faivre, Hyeongdong Park, Hyukjun Moon, Baptiste Gauthier

Grid cells in entorhinal cortex (EC) encode an individual’s location in space and rely on environmental cues and self-motion cues derived from the individual’s body. Body-derived signals are also primary signals for the sense of self and based on integrate ...

2022

(from) the repertoire : an architectural theory of operations. Oral and embodied knowledge in architectural and spatial practices

Julien Lafontaine Carboni

How can one construct spatial histories and architectural theories from gestures, words and voices, bodies and minor threads? This research delves into oral and embodied architectural and spatial knowledge as modes of producing buildings, spaces and spati ...

EPFL2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022