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Publications associées (31)

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The full-body illusion changes visual depth perception

Olaf Blanke, Bruno Herbelin, Sophie Jacqueline Andrée Betka

Knowing where objects are relative to us implies knowing where we are relative to the external world. Here, we investigated whether space perception can be influenced by an experimentally induced change in perceived self-location. To dissociate real and ap ...

Nature Research2023

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

Modeling Visual Impairments with Artificial Neural Networks: a Review

Martin Schrimpf

We present an approach to bridge the gap between the computational models of human vision and the clinical practice on visual impairments (VI). In a nutshell, we propose to connect advances in neuroscience and machine learning to study the impact of VI on ...

Ieee Computer Soc2023

Pathway and directional specificity of Hebbian plasticity in the cortical visual motion processing network

Friedhelm Christoph Hummel, Estelle Emeline Raffin, Michele Bevilacqua

Cortico-cortical paired associative stimulation (ccPAS), which repeatedly pairs single-pulse transcranial magnetic stimulation (TMS) over two distant brain regions, is thought to modulate synaptic plasticity. We explored its spatial selectivity (pathway an ...

2023

Glare analysis of an integral daylighting and lighting control strategy for offices

Stephen William Wasilewski

Complex Fenestration Systems (CFSs) can significantly impact both the visual and non-visual daylight effects on the occupants as well as the energy performance of buildings. To ensure that those impacts improve the overall situation, proper control algorit ...

IOP Publishing2023

Recognizing distant faces

Lukas Vogelsang

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Single fraction and hypofractionated radiosurgery for perioptic meningiomas-tumor control and visual outcomes: a systematic review and meta-analysis

Constantin Tuleasca

Perioptic meningiomas, defined as those that are less than 3 mm from the optic apparatus, are challenging to treat with stereotactic radiosurgery (SRS). Tumor control must be weighed against the risk of radiation-induced optic neuropathy (RION), as both tu ...

Springer2023

Evaluating contrast sensitivity in early and intermediate age-related Macular Degeneration with the Quick Contrast Sensitivity Function

Michael Herzog, Simona Adele Garobbio

Purpose: The purpose of this study was to describe, validate, and compare the contrast sensitivity functions (CSFs) acquired with the novel quick CSF (qCSF) method from patients with early and intermediate age-related macular degeneration (eAMD and iAMD) a ...

2023

Serial dependence in visual perception: A review

David Pascucci, Gizay Ceylan, Ayberk Ozkirli

How does the visual system represent continuity in the constantly changing visual input? A recent proposal is that vision is serially dependent: Stimuli seen a moment ago influence what we perceive in the present. In line with this, recent frameworks sugge ...

Association for Research in Vision and Ophthalmology (ARVO)2023

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Brain dynamics uncovered using a machine-learning algorithm

Mackenzie Mathis

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

NATURE PORTFOLIO2023