Unraveling brain interactions in vision: the example of crowding

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In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainability. The ...

Goal: Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs of nodes. Here we explicitly model the entire set of voxels within a brai ...

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 ...

Understanding the structure of real data is paramount in advancing modern deep-learning methodologies. Natural data such as images are believed to be composed of features organized in a hierarchical and combinatorial manner, which neural networks capture d ...

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 ...

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contex-tual sta ...

The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeability is no ...

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

Although classically Rapid-Eye Movement (REM) sleep was thought to generate desynchronized activity similar to wakefulness, it was found that some brain regions could express Slow Wave activity (SWA), a pattern which was normally typical of slow-wave sleep ...

Technological progress in materials science and microengineering along with new discoveries in neuroscience have contributed to restore lost or impaired sensory functions by closely interfacing with the nervous system. Electronic devices have begun to be i ...

Federated learning (FL) is a machine learning approach where nodes collaboratively train a global model. As more nodes participate in a round of FL, the effectiveness of individual model updates by nodes also diminishes. In this study, we increase the effe ...

Unmanned vehicles have become indispensable tools in various fields such as agriculture, environmental monitoring, and disaster response. A crucial component of these platforms is sensor fusion. As measurements are inherently noisy, certain variables canno ...

Introduction Recent work has shown an association between cognitive and visual impairments and two main theories were advanced, namely the sensory deprivation and the common cause theories. Most studies considered only basic visual functions such as visual ...

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease ...

Optic nerve stimulation holds great potential for visual prostheses. Its effectiveness depends on the stimulation protocol, which can be optimized to achieve cortical activation similar to that evoked in response to visual stimuli. To identify a target cor ...

The epileptic brain is the result of a sequence of events transforming normal neuronal populations into hyperexcitable networks supporting recurrent seizure generation. These modifications are known to induce fundamental alterations of circuit function and ...

Remote sensing visual question answering (RQA) was recently proposed with the aim of interfacing natural language and vision to ease the access of information contained in Earth Observation data for a wide audience, which is granted by simple questions in ...

Unraveling brain interactions in vision: the example of crowding

Chattez avec Graph Search

Towards Visual Saliency Explanations of Face Verification

Voxel-Wise Brain Graphs From Diffusion MRI: Intrinsic Eigenspace Dimensionality and Application to Functional MRI

The full-body illusion changes visual depth perception

A phase transition in diffusion models reveals the hierarchical nature of data

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

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Experimental and computational analysis of REM sleep distributed cortical activity in mice

Fabrication and validation of an intraneural interface tailored for optic nerve stimulation

Harnessing Increased Client Participation with Cohort-Parallel Federated Learning

Factor-graph Optimisation with Vehicle Dynamic Models for Mapping & Sensing Applications

No Common Factor Underlying Decline of Visual Abilities in Mild Cognitive Impairment

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

Predicting visual stimuli from cortical response recorded with widefield imaging in a mouse

Disruption of layer-specific visual processing in a model of focal neocortical epilepsy

Prompt–RSVQA: Prompting visual context to a language model for Remote Sensing Visual Question Answering