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

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ( ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

Chattez avec Graph Search

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

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

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

Probing the latent hierarchical structure of data via diffusion models

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

Learning to Assemble with Alternative Plans

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

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

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

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

Text-to-Microstructure Generation Using Generative Deep Learning

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

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

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

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

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

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

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

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

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