Greenville, TX, United States
Greenville, TX, United States

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Ware T.,University of Texas at Dallas | Simon D.,University of Texas at Dallas | Arreaga-Salas D.E.,University of Texas at Dallas | Reeder J.,University of Texas at Dallas | And 3 more authors.
Advanced Functional Materials | Year: 2012

A novel processing method is described using photolithography to pattern thin-film flexible electronics on shape memory polymer substrates with mechanical properties tailored to improve biocompatability and enhance adhesion between the polymer substrate and metal layers. Standard semiconductor wafer processing techniques are adapted to enable robust device design onto a variety of softening substrates with tunable moduli. The resulting devices are stiff enough (shear modulus of ≈700 MPa) to assist with device implantation and then soften in vivo (≈300 kPa) approaching the modulus of brain tissue (≈10 kPa) within 24 h. Acute in vivo studies demonstrate that these materials are capable of recording neural activity. Softening multi-electrode arrays offer a highly customizable interface, which can be optimized to improve biocompatibility, enabling the development of robust, reliable neural electrodes for neural engineering and neuroscience. 8-channel cortical probes are fabricated using the transfer-by-polymerization process with substrates that soften under physiological conditions. Single unit action potential recordings are shown from rat somatosensory cortex with a shape memory polymer (SMP)-gold electrode array during an acute experiment. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Rush A.D.,Illinois Institute of Technology | Rush A.D.,Plexon Inc. | Troyk P.R.,Illinois Institute of Technology | Troyk P.R.,Sigenics Inc.
IEEE Transactions on Biomedical Engineering | Year: 2012

A wireless cortical neural recording system with a miniature-implanted package is needed in a variety of neuroscience and biomedical applications. Toward that end, we have developed a transcutaneous two-way communication and power system for wireless neural recording. Wireless powering and forward data transmission (into the body) at 1.25 Mbps is achieved using a frequency-shift keying modulated class E converter. The reverse telemetry (out of the body) carrier frequency is generated using an integer-N phase-locked loop, providing the necessary wideband data link to support simultaneous reverse telemetry from multiple implanted devices on separate channels. Each channel is designed to support reverse telemetry with a data rate in excess of 3 Mbps, which is sufficient for our goal of streaming 16 channels of raw neural data. We plan to incorporate this implantable power and telemetry system in a 1-cm diameter single-site cortical neural recording implant. © 2012 IEEE.


Ghanbari Y.,Southern Methodist University | Papamichalis P.E.,Southern Methodist University | Spence L.,Plexon Inc.
IEEE Transactions on Biomedical Engineering | Year: 2011

Analysis of extracellular recordings of neural action potentials (known as spikes) is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering that is performed in the feature space. Principal components analysis (PCA) is the most commonly used feature extraction method employed for neural spike recordings. To improve upon PCAs feature extraction performance for neural spike sorting, we revisit the PCA procedure to analyze its weaknesses and describe an improved feature extraction method. This paper proposes a linear feature extraction technique that we call graph-Laplacian features, which simultaneously minimizes the graph Laplacian and maximizes variance. The algorithms performance is compared with PCA and a wavelet-coefficient-based feature extraction algorithm on simulated single-electrode neural data. A cluster-quality metric is proposed to quantitatively measure the algorithm performance. The results show that the proposed algorithm produces more compact and well-separated clusters compared to the other approaches. © 2006 IEEE.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers, video cameras, and digital input/output hardware for synchronization with other equipment, sold as a unit; computer software, namely, software for controlling video recording and video playback, tracking objects captured on video, recording and analyzing behavioral data, archiving behavioral video and data, and synchronizing behavioral video and data with other equipment.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers and video cameras, sold as a unit; computer software, namely, software for controlling video recording and video playback.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers and video cameras, sold as a unit; computer software, namely, software for controlling video recording and video playback, and tracking objects captured on video.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers and video cameras, sold as a unit; computer software, namely, software for controlling video recording and video playback, tracking objects captured on video, and recording and analyzing behavioral data.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers and video cameras, sold as a package; computer software, namely, software for controlling video recording and video playback, tracking objects captured on video, recording and analyzing behavioral data, and video playback.


Trademark
Plexon Inc. | Date: 2014-10-20

Electronic equipment, namely, computers and video cameras, sold as a unit; computer software, namely, software for controlling video recording and video playback, tracking objects captured on video, recording and analyzing behavioral data, and synchronizing behavioral video and data with other equipment.


Trademark
Plexon Inc. | Date: 2014-06-09

Software, firmware, and hardware for interfacing with living tissue, namely, stimulating, acquiring, recording, analyzing and using signals from the brain, nervous system and related structures.

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