13 papers · ranked by Valyu relevance
Jonas Oberste-Frielinghaus, Aitor Morales-Gregorio, Simon Essink, Alexander Kleinjohann + 4 more
Current electrophysiology experiments often involve massively parallel recordings of neuronal activity using multi-electrode arrays. While researchers have been aware of artifacts arising from electric cross-talk between channels in setups for such recordings, systematic and quantitative assessment of the effects of…
Chongxi Lai, Dohoung Kim, Brian Lustig, Shinsuke Tanaka + 6 more
Real-time neural signal processing is essential for brain-machine interfaces and closed-loop neuronal perturbations. However, most existing applications sacrifice cell-specific identity and temporal spiking information for speed. We developed a hybrid hardware-software system that utilizes a Field Programmable Gate…
Jonas Oberste-Frielinghaus, Aitor Morales-Gregorio, Simon Essink, Alexander Kleinjohann + 7 more
Contemporary electrophysiology experiments often involve massively parallel recordings of neuronal activity using multi-electrode arrays. While researchers have been aware of artifacts arising from electric cross-talk between channels in setups for such recordings, systematic and quantitative assessment of the effects…
Kaan Kesgin, Henrik Jörntell
Time-frequency decomposition is a well-established method to unmix signals generated by multiple sources with unique characteristics. However, there are cases of high signal complexity where existing time-frequency decomposition tools are insufficient for localizing and representing short-bursting signals. One example…
Lukas Hecker, Amita Giri, Dimitrios Pantazis, Amir Adler
Magnetoencephalography (MEG) and electroencephalography (EEG) are widely employed techniques for the in-vivo measurement of neural activity with exceptional temporal resolution. Modeling the neural sources underlying these signals is of high interest for both neuroscience research and pathology. The method of…
Richard Yang, Heather D. Orser, Kip A. Ludwig, Brandon S. Coventry
Digital implementations of discrete Fourier transforms (DFT) are a mainstay in feature assessment of recorded biopotentials, particularly in the quantification of biomarkers of neurological disease state for adaptive deep brain stimulation. Fast Fourier transform (FFT) algorithms and architectures present a substantial…
Fan Zhang, Luxi Zhang, Jie Xia, Wanpeng Zhao + 5 more
Active electrocorticogram (ECoG) electrodes can amplify the weak electrophysiological signals and improve the anti-interference ability, but the traditional active electrodes are so opaque that cannot realize photoelectric collaborative observation. Here an active and fully-transparent ECoG array based on zinc…
Dmitrii Zendrikov, Sergio Solinas, Giacomo Indiveri
Neuromorphic processing systems implementing spiking neural networks with mixed signal analog/digital electronic circuits and/or memristive devices represent a promising technology for edge computing applications that require low power, low latency, and that cannot connect to the cloud for off-line processing, either…
A.R. Mamleev, D.S. Suchkov, E.I. Malyshev, A.A. Vorobyov + 8 more
Flexible and biocompatible neurointerfaces are crucial elements for intraoperative monitoring and chronic neural recordings. However, existing fabrication methods often involve complex cleanroom processes, limiting rapid prototyping and customization. In this study, we present a fast, low-cost method for manufacturing…
Alain de Cheveigné
To understand the brain, we need to observe both the nature and dynamics of its activity (the “what”), and the location or distribution of its sources (the “where”). This paper proposes a new approach based on standard data-driven linear analysis, in which these two elements are derived in parallel from separate…
Safwan Mohammed, Neeraj J. Gandhi, Clara Bourelly, Ahmed Dallal
Neural signals encode information through oscillatory and transient components. The transient component captures rapid, non-rhythmic changes in response to internal or external events, while the oscillatory component reflects rhythmic patterns critical for processing sensation, action, and cognition. Current spectral…
Ambra Ferrari, Luca Filippin, Marco Buiatti, Eugenio Parise
Electroencephalography (EEG) is an established method for investigating neurocognitive functions during human development. In cognitive neuroscience, time-frequency analysis of the EEG is a widely used analytical approach. This paper introduces WTools, a new MATLAB-based toolbox capable of performing time-frequency…
I. Baglaeva, B. Iaparov, I. Zahradník, A. Zahradníková
Dynamic systems such as cells or tissues generate, either spontaneously or in response to stimuli, transient signals that carry information about the system. Characterization of recorded transients is often hampered by a low signal-to-noise ratio (SNR). Reduction of the noise by filtering has limited use due to partial…