Reverse engineering the motor control system

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

Animals, including humans, exhibit a remarkable variety of complex behaviours. How the nervous system controls all these behaviours ranging from simple, stereotyped movements to flexible, adaptive actions is a central questions of neuroscience. One of the ...

In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely positioned and displaying notable inter-object correlations. This can creat ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

The decline of motor ability is a hallmark feature of aging and is accompanied by degeneration of motor synaptic terminals. Consistent with this, Drosophila motor synapses undergo characteristic age -dependent structural fragmentation co -incident with dim ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

The hands, our silent performers in daily life, face overwhelming challenges when neurological impairments disrupt the simple tasks that compose our daily symphony. This thesis unveils a comprehensive framework for the objective monitoring of upper-limb re ...

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

Background :Sensory reafferents are crucial to correct our posture and movements, both reflexively and in a cognitively driven manner. They are also integral to developing and maintaining a sense of agency for our actions. In cases of compromised reafferen ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Reverse engineering the motor control system

Chat with Graph Search

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Uncovering interactions between Descending Neurons as a functional principle of behavioural control

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Topics in statistical physics of high-dimensional machine learning

Trio preserves motor synapses and prolongs motor ability during aging

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Small-scale robotic devices for medical interventions in the brain

Context-Aware Monitoring of Hand Motor Primitives in Daily Life Activities: A Pathway to Objectively Assess Rehabilitation of Patients with Upper-Limb Neurological Impairment

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Random matrix methods for high-dimensional machine learning models

Machine Learning for Modeling Stock Returns

Augmenting locomotor perception by remapping tactile foot sensation to the back

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging