Flexible neural probes are attractive emerging technologies for brain recording because they can effectively record signals with minimal risk of brain damage. Reducing the electrode impedance of the probe before recording is a common practice of many researchers. However, studies investigating the impact of low impedance levels on high-quality recordings using flexible neural probes are lacking. In this study, we electrodeposited Pt onto a commercial flexible polyimide neural probe and investigated the relationship between the impedance level and the recording quality. The probe was inserted into the brains of anesthetized mice. The electrical signals of neurons in the brain, specifically the ventral posteromedial nucleus of the thalamus, were recorded at impedance levels of 50, 250, 500 and 1000 kΩ at 1 kHz. The study results demonstrated that as the impedance decreased, the quality of the signal recordings did not consistently improve. This suggests that extreme lowering of the impedance may not always be advantageous in the context of flexible neural probes.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11014004 | PMC |
| http://dx.doi.org/10.3390/s24072300 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
BA-ATEMNet: Bayesian Learning and Multi-Head Self-Attention for Theoretical Denoising of Airborne Transient Electromagnetic Signals.
Sensors (Basel)
December 2024
Information Network Center, Chengdu University, Chengdu 610106, China.
Airborne transient electromagnetic (ATEM) surveys provide a fast, flexible approach for identifying conductive metal deposits across a variety of intricate terrains. Nonetheless, the secondary electromagnetic response signals captured by ATEM systems frequently suffer from numerous noise interferences, which impede effective data processing and interpretation. Traditional denoising methods often fall short in addressing these complex noise backgrounds, leading to less-than-optimal signal extraction.
View Article and Find Full Text PDFRSVP Keyboard with Inquiry Preview: mixed performance and user experience with an adaptive, multimodal typing interface combining EEG and switch input.
J Neural Eng
January 2025
Department of Pediatrics, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, Oregon, 97239-3098, UNITED STATES.
Objective: The RSVP Keyboard is a non-implantable, event-related potential-based brain-computer interface (BCI) system designed to support communication access for people with severe speech and physical impairments. Here we introduce Inquiry Preview, a new RSVP Keyboard interface incorporating switch input for users with some voluntary motor function, and describe its effects on typing performance and other outcomes.
Approach: Four individuals with disabilities participated in the collaborative design of possible switch input applications for the RSVP Keyboard, leading to the development of Inquiry Preview and a method of fusing switch input with language model and electroencephalography (EEG) evidence for typing.
tinyHLS: a novel open source high level synthesis tool targeting hardware accelerators for artificial neural network inference.
Physiol Meas
January 2025
University of Duisburg-Essen, Bismarckstr. 81 (BB), Duisburg, 47057, GERMANY.
Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.
Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed
to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.
A Self-Supporting Flexible Electrode for Tracking and Reversible Quantification of Mg2+ and Ca2+ in the Brains of Freely Behaving Animal.
Angew Chem Int Ed Engl
January 2025
East China Normal University, Dept. of Chemistry, Dongchuan Road 500, 200062, Shanghai, CHINA.
Monitoring dynamic neurochemical signals in the brain of free-moving animals remains great challenging in biocompatibility and direct implantation capability of current electrodes. Here we created a self-supporting polymer-based flexible microelectrode (rGPF) with sufficient bending stiffness for direct brain implantation without extra devices, but demonstrating low Young's modulus with remarkable biocompatibility and minimal position shifts. Meanwhile, screening by density functional theory (DFT) calculation, we designed and synthesized specific ligands targeting Mg2+ and Ca2+, and constructed Mg-E and Ca-E sensors with high selectivity, good reversibility, and fast response time, successfully monitoring Mg2+ and Ca2+ in vivo up to 90 days.
View Article and Find Full Text PDFThe impact of preschool children's physical fitness evaluation under self organizing maps neural network.
Sci Rep
January 2025
Faculty of Education, Universiti Kebangsaan Malaysia, Bangi, Selangor, 43600, Malaysia.
To improve the scientific accuracy and precision of children's physical fitness evaluations, this study proposes a model that combines self-organizing maps (SOM) neural networks with cluster analysis. Existing evaluation methods often rely on traditional, single statistical analyses, which struggle to handle the complexity of high-dimensional, nonlinear data, resulting in a lack of precision and personalization. This study uses the SOM neural network to reduce the dimensionality of high-dimensional health data.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!