Home

Publication

Closed-Loop Control of Epidural Electrical Stimulation in Patients with Spinal Cord Injury and Parkinson's Disease

About
Privacy
Disclaimer

Graph Chatbot

Related publications (56)

Page 2 of 3

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Zeki Doruk Erden

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

EPFL2025

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus

Emanuela De Falco

Neurons in the human amygdala and hippocampus are classically thought to encode a person’s identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortical areas is translated into such a semanti ...

2025

Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex

Sylvain Jean-François Harquel

The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, dep ...

Mit Press2024

Probing the latent hierarchical structure of data via diffusion models

Alessandro Favero, Antonio Sclocchi, Noam Itzhak Levi

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

2025

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Outman Akouissi

This thesis presents an extensive exploration of neuroelectronic interfaces, focusing on microfabrication, in silico modeling, and their applications in designing and fabricating devices for neural interfacing. The research encompasses both peripheral nerv ...

EPFL2024

Learning to Assemble with Alternative Plans

Gabriel Rémi Vallat, Ziqi Wang, Jingwen Wang, Maryam Kamgarpour, Stefana Parascho

We present a reinforcement learning framework for constructing assemblies composed of rigid parts, which are commonly seen in many historical masonry buildings and bridges. Traditional construction methods for such structures often depend on dense scaffold ...

Association for Computing Machinery (ACM)2025

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Mohammad Javad Karimi

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

EPFL2024

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

Volkan Cevher, Zhenyu Zhu, Fanghui Liu

This paper investigates the fundamental regression task of learning k neurons (a.k.a. teachers) from Gaussian input, using two-layer ReLU neural networks with width m (a.k.a. students) and m, k = O(1), trained via gradient descent under proper initializati ...

2025

Synergetic Support of Cartilage Homeostasis via Coupled Thermal-Hydrostatic Pressure Stimuli

Yanheng Guo

Cartilage homeostasis, crucial for musculoskeletal function, is orchestrated by interconnected biophysical cues. In healthy cartilage, repetitive compressive loading not only elicits a range of mechanical stimuli but also induces a gradual transient temper ...

EPFL2024

Idiopathic normal pressure hydrocephalus: A sulcal morphometry approach to brain phenotype and clinical response

Dimitri Nestor Alice Van De Ville, Alessandra Griffa

Idiopathic normal pressure hydrocephalus (iNPH), the leading cause of reversible dementia in older adults, is characterized by urinary incontinence, gait impairment, cognitive decline, and ventriculomegaly. Neuroradiological features rely on visual assessm ...

Elsevier BV2025

Text-to-Microstructure Generation Using Generative Deep Learning

Jamie Paik, Xiaoyang Zheng

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

Wiley-V C H Verlag Gmbh2024

Improving the accuracy and interpretability of neural networks for wind power forecasting

Jiannong Fang, Fernando Porté Agel, Wenlong Liao

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

2025

Neuromodulation/neurostimulation system for mitigating locomotor deficits of parkinson's disease, spinal cord injury (sci), stroke and/or other neurological disorders

Tomislav Milekovic, Léonie Asboth, Grégoire Courtine, Eduardo Martin Moraud, Robin Jonathan Demesmaeker, Newton Cho, Jocelyne Bloch, Jordan Squair

The present invention relates to a combined neuromodulation and/or neurostimulation system (10) for mitigating locomotor deficits of/or neuronal disorders, especially Parkinson's disease, said system (10) comprising: - at least one Deep Brain Stimulation ( ...

2023

Walking naturally after spinal cord injury using a brain-spine interface

Léonie Asboth, Salif Axel Komi, Grégoire Courtine, Robin Jonathan Demesmaeker, Jocelyne Bloch, Sergio Daniel Hernandez, Henri Charles Alexandre Lorach, Edeny Baaklini, Jimmy James Ravier, Carmina Andrea Galvez Solano, Cathal John Harte, Grégory Didier Dumont, Thibault Jean Etienne Collin, Icare Sakr, Nadine Intering

A spinal cord injury interrupts the communication between the brain and the region of the spinal cord that produces walking, leading to paralysis(1,2). Here, we restored this communication with a digital bridge between the brain and spinal cord that enable ...

NATURE PORTFOLIO2023

Lessons Learned Executing the Non-disruptive Compass Scan Method at Jet Towards Error Field Identification Experiments in Iter

Olivier Sauter, Alessandro Pau

In preparation for error field (EF) identification experiments in ITER, a series of experiments have been conducted at JET to test the portability of the non-disruptive compass scan, a method originally designed and tested in DIII-D (Paz-Soldan et al 2022 ...

IOP Publishing Ltd2025

Quantitative analysis of the correlation between body posture quality assessment scores and handwriting quality measures

Pierre Dillenbourg, Chenyang Wang, Barbara Bruno, Daniel Carnieto Tozadore

Various technological applications for body posture correction have been proposed in order to improve handwriting or facilitate its learning for children, under the assumption that a better posture promotes better handwriting. However, very little research ...

Springer Science and Business Media LLC2025

Targeted regeneration of spinal cord neurons across a complete injury restores walking

Marco Milano

Spinal cord injury (SCI) interrupts axonal connections between the brain and the spinal cord, and is characterized by a spectrum of sensorimotor and autonomic impairments. While spontaneous recovery is limited, recent studies have shown that functional imp ...

EPFL2023

A Closer Look at Benchmarking Self-supervised Pre-training with Image Classification

Fernando Perez Cruz

Self-supervised learning (SSL) is a machine learning approach where the data itself provides supervision, eliminating the need for external labels. The model is forced to learn about the data's inherent structure or context by solving a pretext task. With ...

SPRINGER2025

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

Gian Luca Barbruni

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 ...

EPFL2023

Integrating Physics and Topology in Neural Networks for Learning Rigid Body Dynamics

Amaury Pierre Jiezhi Wei, Olga Fink

Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable learnin ...

NATURE PORTFOLIO2025