Realizing the neurological information processing by analyzing the complex data transferring behavior of populations and individual neurons is one of the fast-growing fields of neuroscience and bioelectronic technologies. This field is anticipated to...
Neural electrodes are essential for nerve signal recording, neurostimulation, neuroprosthetics and neuroregeneration, which are critical for the advancement of brain science and the establishment of the next-generation brain–electronic interface, cen...
We report on a new approach toward a laser-assisted modification of biocompatible polydimethylsiloxane (PDMS) elastomers relevant to the fabrication of stretchable multielectrode arrays (MEAs) devices for neural interfacing technologies. These applic...
Neural interfaces are crucial conduits between neural tissues and external devices, enabling the recording and modulation of neural activity. However, with increasing demand, simple neural interfaces are no longer adequate to meet the requirements fo...
This review outlines the technological principles of neural–computer interface (NCI) construction, classifying them according to: (1) the degree of intervention (invasive, semi-invasive, and non-invasive); (2) the direction of signal communicat...
Neural interfaces are a fundamental tool to interact with neurons and to study neural networks by transducing cellular signals into electronics signals and vice versa. State-of-the-art technologies allow both in vivo and in vitro recording of neural...
Achieving a stable, long-term connection with millions of neurons within living organisms remains one of the dreams of neuroscience. Silicon shank based probes lead the field in terms of pure channel count. On the other hand, polymer neural probes of...
Brain‒machine interface (BMI) is a promising technology that looks set to contribute to the development of artificial limbs and new input devices by integrating various recent technological advances, including neural electrodes, wireless communicatio...
Neural interfaces, which enable the recording and stimulation of living neurons, have emerged as valuable tools in understanding the brain in health and disease, as well as serving as neural prostheses. While neural interfaces are typically based on...
With the rapid development of Micro-electro-mechanical Systems (MEMS) fabrication technologies, many microelectrodes with various structures and functions have been designed and fabricated for applications in biomedical research, diagnosis and treatm...
It is a great challenge to solve nonhomogeneous elliptic interface problems, because the interface divides the computational domain into two disjoint parts, and the solution may change dramatically across the interface. A soft constraint physics-info...
Background: Restoration of sensory feedback has become one of the major goals of modern bidirectional neuroprosthetic rehabilitation, enabling the transition from conventional prosthetic replacement toward bidirectional neuroprosthetic systems capabl...
Neural interfaces, such as microarrays and probes, consist of many electrodes for stimulating and recording purposes simultaneously. The multi-functional neural interface can suffer from many types of artefacts and noise, such as long-term use, envir...
Recently, methods for the treatment of chronic diseases and disorders through the modulation of peripheral and autonomic nerves have been proposed. To investigate various treatment methods and results, experiments are being conducted on animals such...
Functional hydrogels are increasingly used in neural interfaces. As hydrophilic polymer networks that combine tissue-like softness with tunable conductivity and adhesion, they relieve two fundamental limitations of rigid conventional electrodes withi...
The promise of intracortical neural interfaces—to restore lost sensory and motor function and probe the brain’s activity—has long been constrained by device instability over chronic implantation. Conventional silicon-based probes, c...
Long-term implantable neural electrodes underpin brain–machine interfaces, deep brain stimulation, epilepsy monitoring, and closed-loop neuromodulation. Following chronic implantation, however, the foreign body response (FBR) at the electrode&n...
A new high-order hybrid method integrating neural networks and corrected finite differences is developed for solving elliptic equations with irregular interfaces and discontinuous solutions. Standard fourth-order finite difference discretization beco...
This paper proposed and verified the use of polymer-based packaging to implement the chronic implantation of neural interfaces using a combination of a commercial thermal epoxy and a thin parylene film. The packaging’s characteristics and the p...
Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a lo...
Protein–protein interactions (PPIs) are fundamental processes governing cellular functions, crucial for understanding biological systems at the molecular level. Compared to experimental methods for PPI prediction and site identification, comput...
This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrat...
Chronic implantation of an epidural Electrocorticography (ECoG) electrode produces thickening of the dura mater and proliferation of the fibrosis around the interface sites, which is a significant concern for chronic neural ECoG recording application...
The process of changing the neuronal activity of the brain to acquire rewards in a broad sense is essential for utilizing brain-machine interfaces (BMIs), which is essentially operant conditioning of neuronal activity. Currently, this is also known a...
High-order implicit-explicit (IMEX) schemes are effective for stiff parabolic partial differential equations when temporal regularity is compatible with the active multistep stencil. In moving-interface problems, a fixed Eulerian node may undergo a r...
Intracortical brain–computer interfaces (iBCIs) translate neural activity into control commands, thereby allowing paralyzed persons to control devices via their brain signals. Recurrent neural networks (RNNs) are widely used as neural decoders becaus...
Because of rising traumatic accidents and diseases, the number of patients suffering from nerve injury is increasing. Without effective rehabilitation therapy, the patients will get motor or sensory function losses or even a lifelong disability. As f...
Limb amputation is a major cause of disability in our community, for which motorised prosthetic devices offer a return to function and independence. With the commercialisation and increasing availability of advanced motorised prosthetic technologies,...
Neural interfaces created using thin-film fabrication rely primarily on conductive metal traces for electrical interconnects. Here, we explore the use of tantalum (Ta) metal interconnects as a replacement for noble-metal interconnects such as Au, Pt...
Through the development of artificial intelligence, some capabilities of human beings have been replicated in computers. Among the developed models, convolutional neural networks stand out considerably because they make it possible for systems to hav...
Flexible microscale neural interfaces are advancing current strategies for recording and modulating electrical activity in the brain and spinal cord. The aim of this review is to colligate recent progress in thin-film micro-electrocorticography (μ...
The rapid advancement of flexible sensor technology has profoundly transformed neural interface research, enabling multimodal information acquisition, real-time neurochemical and electrophysiological signal monitoring, and adaptive closed-loop regula...
The stable generalized finite element method (SGFEM) is an improved version of generalized or extended FEM (GFEM/XFEM), which (i) uses simple and unfitted meshes, (ii) reaches optimal convergence orders, and (iii) is stable and robust in the sense th...
Implantable flexible neural interfaces (IfNIs) are capable of directly modulating signals of the central and peripheral nervous system by stimulating or recording the action potential. Despite outstanding results in acute experiments on animals and h...
Microelectrode arrays that consistently and reliably record and stimulate neural activity under conditions of chronic implantation have so far eluded the neural interface community due to failures attributed to both biotic and abiotic mechanisms. Arr...
Although neural devices have shown efficacy in the treatment of neurodegenerative diseases, their functionality is limited by the inflammatory state and glial scar formation associated with chronic implantation. The aim of this study was to investiga...
User satisfaction serves as a crucial reference for iteratively optimizing software interface designs. This paper introduces a comprehensive measurement model of user satisfaction, employing Notability and Goodnotes for case studies. The proposed mod...
Intracortical neural interfaces (INI) have made impressive progress in recent years but still display questionable long-term reliability. Here, we report on the development and characterization of highly resilient monolithic silicon carbide (SiC) neu...
Estimation of human emotions plays an important role in the development of modern brain-computer interface devices like the Emotiv EPOC+ headset. In this paper, we present an experiment to assess the classification accuracy of the emotional states pr...
One of the main issues with micron-sized intracortical neural interfaces (INIs) is their long-term reliability, with one major factor stemming from the material failure caused by the heterogeneous integration of multiple materials used to realize the...
The development of implantable neural interfaces is essential for enabling bidirectional communication between the nervous system and prosthetic devices, yet their evaluation still relies primarily on in vivo models which are costly, variable, and et...
The motor imagery-based brain-computer interface (BCI) using electroencephalography (EEG) has been receiving attention from neural engineering researchers and is being applied to various rehabilitation applications. However, the performance degradati...
Imagined speech decoding has attracted growing interest in brain–computer interface (BCI) research, as it may enable language-related information to be recovered from non-overt neural activity. Current studies in this area are often treated as...
Direct interaction with the neuronal cells is a prerequisite to deciphering useful information in understanding the underlying causes of diseases and functional abnormalities in the brain. Precisely fabricated nanoelectrodes provide the capability to...
Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has become one of the most influential materials in neural engineering, offering high electrical conductivity, mechanical softness, and stable processing in complex aqueous media. Be...
This paper advances real-time cursor control for individuals with motor impairments through a novel brain–computer interface (BCI) system based solely on motor imagery. We introduce an enhanced deep neural network (DNN) classifier integrated wi...
An essential method to investigate neuromodulation effects of an invasive neural interface (INI) is magnetic resonance imaging (MRI). Presently, MRI imaging of patients with neural implants is highly restricted in high field MRI (e.g., 3 T and higher...
Carbon containing materials, such as graphene, carbon-nanotubes (CNT), and graphene oxide, have gained prominence as possible electrodes in implantable neural interfaces due to their excellent conductive properties. While carbon is a promising electr...
Microservice workflow orchestration recommendation aims to streamline business process construction by suggesting relevant microservices, yet existing methods relying on functional similarity in dependency graphs prove inadequate. Traditional graphs...
Modern achievements accomplished in both cognitive neuroscience and human–machine interaction technologies have enhanced the ability to control devices with the human brain by using Brain–Computer Interface systems. Particularly, the deve...
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