A 16-channel 220 µW neural recording IC with embedded delta compression

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Recent advances in the development of intra-cortical neural interfacing devices show the bright horizon of having access to brain-implantable microsystems with extremely high channel counts in the not-so-distant future. With the fabrication of high-density ...

Depth sensing is essential for intelligent computer vision applications, but it often suffers from low range precision and spatial resolution. To address this problem, we propose a novel framework that combines non-uniform sampling and reconstruction based ...

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 ...

A modular multiple frequency coils inductive link system to wirelessly provide power for at least a medical implant at an output of a receiving coil, whereby the receiving coil is configured to be implanted in an organism. The modular multiple frequency co ...

This article proposes a new two-wired amplifying active electrode (AE), presenting a high input impedance and a high common-mode rejection ratio (CMRR). In the proposed structure, the input impedance and the CMRR of the system are considerably increased by ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins t ...

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 ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Solid-state transformers with input-series outputparallel structures are being considered for a variety of applications requiring MVAC to LVDC conversion. Due to the singlephase AC/DC conversion at the input side, all floating cells of the solid-state tran ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

We study the hitting probabilities of the solution to a system of d stochastic heat equations with additive noise subject to Dirichlet boundary conditions. We show that for any bounded Borel set with positive (d-6)\documentclass[12pt]{minimal} \usepackage{ ...

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 ...

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 ...

The research presented in this article draws inspiration from previous efforts aimed at replicating the functions of various solid-state memristors using a variety of materials. The memristor circuit emulator serves as a cost-effective tool for circuit des ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

In the development of implantable bioelectronics, the establishment of efficient wireless RF links between implants and external nodes is crucial, providing substantial contributions to the advancement of medical diagnosis, therapies, and basic science. Im ...

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

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 ...

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 ...

A 16-channel 220 µW neural recording IC with embedded delta compression

Chattez avec Graph Search

Real-time, Neural Signal Processing for High-density Brain-implantable Devices

High-Quality Reconstruction of Depth Maps From Graph-Based Non-Uniform Sampling

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

A modular multiple frequency inductive link to wirelessly power multiple miniaturized implants

A Two-Wired High Input Impedance and High CMRR Active Electrode Insensitive to Component Mismatch

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Recording physiological history of cells with chemical labeling

Random matrix methods for high-dimensional machine learning models

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Active Power Decoupling for Single-Phase Input-Series-Output-Parallel Solid-State Transformers

Live-cell imaging powered by computation

Hitting with Probability One for Stochastic Heat Equations with Additive Noise

Small-scale robotic devices for medical interventions in the brain

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

Emulating Multimemristive Behavior of Silicon Nanowire-Based Biosensors by Using CMOS-Based Implementations

Exploiting the Signal-Leak Bias in Diffusion Models

Electromagnetic Radiation of Implantable Antennas

Fast adaptation to rule switching using neuronal surprise

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

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis