Towards a Robust BCI: Error Potentials and Online Learning

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Robots have to adjust their motor behavior to changing environments and variable task requirements to successfully operate in the real world and physically interact with humans. Thus, robotics strives to enable a broad spectrum of adjustable motor behavior ...

Neural quantum state (NQS) ans & auml;tze have shown promise in variational Monte Carlo algorithms by their theoretical capability of representing any quantum state. However, the reason behind the practical improvement in their performance with an increase ...

Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...

Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to ...

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 ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

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 ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

We present a new algorithm for imitation learning in infinite horizon linear MDPs dubbed ILARL which greatly improves the bound on the number of trajectories that the learner needs to sample from the environment. In particular, we re- move exploration assu ...

Recent research shows prominent effects of pregnancy and the parenthood transition on structural brain characteristics in humans. Here, we present a comprehensive study of how parental status and number of children born/fathered links to markers of brain a ...

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 ...

Objective. Selective neuromodulation of deep brain regions has for a long time only been possible through invasive approaches, because of the steep depth-focality trade-off of conventional non-invasive brain stimulation (NIBS) techniques. Approach. An appr ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

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 ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Energy dispersive X-ray (EDX) spectroscopy in the transmission electron microscope is a key tool for nanomaterials analysis, providing a direct link between spatial and chemical information. However, using it for precisely determining chemical compositions ...

BackgroundImpaired cerebrospinal fluid (CSF) dynamics is involved in the pathophysiology of neurodegenerative diseases of the central nervous system and the optic nerve (ON), including Alzheimer's and Parkinson's disease, as well as frontotemporal dementia ...

Self-supervised learning through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) image representation learning, and thus embodies a significant potential for content-based image retrieval (CBIR) from ever-growing R ...

Towards a Robust BCI: Error Potentials and Online Learning

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A neuromechanics solution for adjustable robot compliance and accuracy

Efficiency of neural quantum states in light of the quantum geometric tensor

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System

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

Driving and suppressing the human language network using large language models

Augmenting locomotor perception by remapping tactile foot sensation to the back

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

White adipose tissue distribution and amount are associated with increased white matter connectivity

Imitation Learning in Discounted Linear MDPs without exploration assumptions

Parental status and markers of brain and cellular age: A 3D convolutional network and classification study

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

Safety, tolerability and blinding efficiency of non-invasive deep transcranial temporal interference stimulation: first experience from more than 250 sessions

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Small-scale robotic devices for medical interventions in the brain

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Leveraging Machine Learning for Advanced Nanoscale X-ray Analysis: Unmixing Multicomponent Signals and Enhancing Chemical Quantification

Large-scale in-silico analysis of CSF dynamics within the subarachnoid space of the optic nerve

Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing