Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely spaced recording sites, and electrodes with thousands of sites are under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons from the raw data captured from the probes. Here we present a set of tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus and thalamus of rat, mouse, macaque and marmoset, demonstrating error rates as low as 5%.
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http://dx.doi.org/10.1038/nn.4268 | DOI Listing |
Sci Rep
December 2024
State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China.
Microelectrode arrays (MEAs) have been widely used in studies on the electrophysiological features of neuronal networks. In classic MEA experiments, spike or burst rates and spike waveforms are the primary characteristics used to evaluate the neuronal network excitability. Here, we introduced a new method to assess the excitability using the voltage threshold of electrical stimulation.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Chemical Engineering, Electrochemical Innovation Lab, University College London, London, UK.
High-temperature proton exchange membrane fuel cells (HT-PEMFCs) offer solutions to challenges intrinsic to low-temperature PEMFCs, such as complex water management, fuel inflexibility, and thermal integration. However, they are hindered by phosphoric acid (PA) leaching and catalyst migration, which destabilize the critical three-phase interface within the membrane electrode assembly (MEA). This study presents an innovative approach to enhance HT-PEMFC performance through membrane modification using picosecond laser scribing, which optimises the three-phase interface by forming a graphene-like structure that mitigates PA leaching.
View Article and Find Full Text PDFBiosensors (Basel)
November 2024
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
In this paper, we present a microfluidic flow cytometer for simultaneous imaging and dielectric characterization of individual biological cells within a flow. Utilizing a combination of dielectrophoresis (DEP) and high-speed imaging, this system offers a dual-modality approach to analyze both cell morphology and dielectric properties, enhancing the ability to analyze, characterize, and discriminate cells in a heterogeneous population. A high-speed camera is used to capture images of and track multiple cells in real-time as they flow through a microfluidic channel.
View Article and Find Full Text PDFBiosensors (Basel)
November 2024
Nanobioengineering Group, Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), 12 Baldiri Reixac 15-21, 08028 Barcelona, Spain.
There are many examples in nature in which the ability to detect is combined with decision-making, such as the basic survival instinct of plants and animals to search for food. We can technically translate this innate function via the use of robotics with integrated sensors and artificial intelligence. However, the integration of sensing capabilities into robotics has traditionally been neglected due to the significant associated technical challenges.
View Article and Find Full Text PDFAm J Physiol Cell Physiol
December 2024
Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Norway.
Amyotrophic lateral sclerosis (ALS) is characterized by dysfunction and loss of upper and lower motor neurons. Several studies have identified structural and functional alterations in the motor neurons before the manifestation of symptoms, yet the underlying cause of such alterations and how they contribute to the progressive degeneration of affected motor neuron networks remain unclear. Importantly, the short and long-term spatiotemporal dynamics of neuronal network activity make it challenging to discern how ALS-related network reconfigurations emerge and evolve.
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