The connectome spectrum as a canonical basis for a sparse representation of fast brain activity

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Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as ...

Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) poses significant challenges due to the substantial view discrepancies between oblique UAV images and overhead satellite images. Existing methods heavily rely on supervised learning with labe ...

A spinal cord injury (SCI) disrupts the neuronal projections from the brain to the region of the spinal cord that produces walking, leading to various degrees of paralysis. Here, we aimed to identify brain regions that steer the recovery of walking after i ...

This note describes a method to train a Neural Network so that it approximates a control Lyapunov function for a nonlinear system in affine form. The network is trained in a physics-informed fashion, as the training data are generated by enforcing the nega ...

Bending-active structures are composed of elastic elements that deform to achieve a desired target shape. To support effective design, inverse algorithms have been proposed that optimize the geometry of each element specifically for each design. This makes ...

In some areas of Antarctica, blue-colored bare ice is exposed at the surface. These blue ice areas (BIAs) can trap meteorites or old ice and are vital for understanding the climatic history. By combining multi-sensor remote sensing data (MODIS, RADARSAT-2, ...

The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the interpretation of clinical data. However, high-resolution and accurate multi-p ...

Constrained Spherical Deconvolution (CSD) is a state-of-the-art technique for unraveling complex fiber configurations of white matter from diffusion MRI data. Despite its ability to identify multiple fiber orientations, it faces difficulties in resolving f ...

The premotor (PM) and primary motor (M1) cortical areas broadcast voluntary motor commands through multiple neuronal pathways, including the corticorubral projection that reaches the red nucleus (RN). However, the respective contribution of M1 and PM to co ...

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

Goal-directed behaviors involve coordinated activity in many cortical areas, but whether the encoding of task variables is distributed across areas or is more specifically represented in distinct areas remains unclear. Here, we compared representations of ...

In this work, we study neural network architectures that will reduce the number of infractions made by autonomous-driving agents. These agents control vehicles by providing future waypoints directly from a forward-facing camera. Building on top of the teac ...

While aging is characterized by neurodegeneration, musical training is associated with experience-driven brain plasticity and protection against age-related cognitive decline. However, evidence for the positive effects of musical training mostly comes from ...

Current speech recognition architectures perform very well from the point of view of machine learning, hence user interaction. This suggests that they are emulating the human biological system well. We investigate whether the inference can be inverted to p ...

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques ...

The connectome spectrum as a canonical basis for a sparse representation of fast brain activity

Chattez avec Graph Search

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering

Hypothalamic deep brain stimulation augments walking after spinal cord injury

Stabilization of nonlinear systems by neural Lyapunov approximators and Sontag's formula

Computational Design of a Kit of Parts for Bending Active Structures

Where the White Continent Is Blue: Deep Learning Locates Bare Ice in Antarctica

Physics-informed neural network estimation of material properties in soft tissue nonlinear biomechanical models

Spatial Prior Informed Constrained Spherical Deconvolution in Super Resolution Variation

Loss of Motor Cortical Inputs to the Red Nucleus after CNS Disorders in Nonhuman Primates

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Distributed and specific encoding of sensory, motor, and decision information in the mouse neocortex during goal-directed behavior

Training Traffic Light Behavior with End-to-End Learning

Six Months of Piano Training in Healthy Elderly Stabilizes White Matter Microstructure in the Fornix, Compared to an Active Control Group

Low-Level Physiological Implications of End-to-End Learning of Speech Recognition

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios