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https://www.readbyqxmd.com/read/28637207/the-use-of-semitranslucent-rubber-pledgets-during-microsurgical-dissection-of-cerebellopontine-angle-tumors-technical-note
#1
Marcus D Mazur, Richard Gurgel, Joel D MacDonald
BACKGROUND AND IMPORTANCE: Dissection of cerebellopontine angle (CPA) tumors that abut or adhere to the brainstem or cranial nerves can be a challenging surgical endeavor. We describe the use of semitranslucent latex rubber pledgets in the tumor-brain interface as a method to improve visualization and protection of vital tissue during microsurgical dissection of CPA masses. The rubber pledgets are fashioned by cutting circular discs out of the cuff portion of talc-free, partially opaque latex gloves...
June 20, 2017: Operative Neurosurgery (Hagerstown, Md.)
https://www.readbyqxmd.com/read/28630937/high-precision-neural-decoding-of-complex-movement-trajectories-using-recursive-bayesian-estimation-with-dynamic-movement-primitives
#2
Guy Hotson, Ryan J Smith, Adam G Rouse, Marc H Schieber, Nitish V Thakor, Brock A Wester
Brain-machine interfaces (BMIs) are a rapidly progressing technology with the potential to restore function to victims of severe paralysis via neural control of robotic systems. Great strides have been made in directly mapping a user's cortical activity to control of the individual degrees of freedom of robotic end-effectors. While BMIs have yet to achieve the level of reliability desired for widespread clinical use, environmental sensors (e.g. RGB-D cameras for object detection) and prior knowledge of common movement trajectories hold great potential for improving system performance...
July 2016: IEEE Robotics and Automation Letters
https://www.readbyqxmd.com/read/28630894/next-generation-probes-particles-and-proteins-for-neural-interfacing
#3
REVIEW
Jonathan Rivnay, Huiliang Wang, Lief Fenno, Karl Deisseroth, George G Malliaras
Bidirectional interfacing with the nervous system enables neuroscience research, diagnosis, and therapy. This two-way communication allows us to monitor the state of the brain and its composite networks and cells as well as to influence them to treat disease or repair/restore sensory or motor function. To provide the most stable and effective interface, the tools of the trade must bridge the soft, ion-rich, and evolving nature of neural tissue with the largely rigid, static realm of microelectronics and medical instruments that allow for readout, analysis, and/or control...
June 2017: Science Advances
https://www.readbyqxmd.com/read/28628030/a-novel-flexible-cuff-like-microelectrode-for-dual-purpose-acute-and-chronic-electrical-interfacing-with-the-mouse-cervical-vagus-nerve
#4
April Shawn Caravaca, Téa Tsaava, Laura Goldman, Harold Silverman, Gary Riggott, Sangeeta Chavan, Chad Bouton, Kevin J Tracey, Robert Desimone, Ed Boyden, Harbaljit Singh Sohal, Peder S Olofsson
OBJECTIVE: Neural reflexes establish homeostasis and regulate the immune system. Advances in bioelectronic medicine indicate that electrical stimulation of the vagus nerve can be used to treat inflammatory disease, yet the understanding of neural signals that regulate inflammation is incomplete. Current interfaces with the vagus nerve do not permit effective chronic stimulation or recording in mouse models, which is vital to studying the molecular and neurophysiological mechanisms that control inflammation homeostasis in health and disease...
June 19, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28628004/visual-field-map-clusters-in-human-frontoparietal-cortex
#5
Wayne E Mackey, Jonathan Winawer, Clayton E Curtis
The visual neurosciences have made enormous progress in recent decades, in part because of the ability to drive visual areas by their sensory inputs, allowing researchers to reliably define visual areas across individuals and across species. Similar strategies for parcellating higher-order cortex have proven elusive. Here, using a novel experimental task and nonlinear population receptive field modeling we map and characterize the topographic organization of several regions in human frontoparietal cortex. We discover representations of both polar angle and eccentricity that are organized into clusters, similar to visual cortex, where multiple gradients of polar angle of the contralateral visual field share a confluent fovea...
June 19, 2017: ELife
https://www.readbyqxmd.com/read/28626362/nanoporous-gold-biointerfaces-modifying-nanostructure-to-control-neural-cell-coverage-and-enhance-electrophysiological-recording-performance
#6
Christopher A R Chapman, Ling Wang, Hao Chen, Joshua Garrison, Pamela J Lein, Erkin Seker
Nanostructured neural interface coatings have significantly enhanced recording fidelity in both implantable and in vitro devices. As such, nano-porous gold (np-Au) has shown promise as a multifunctional neural interface coating due, in part, to its ability to promote nanostructure-mediated reduction in astrocytic surface coverage while not affecting neuronal coverage. The goal of this study is to provide insight into the mechanisms by which the np-Au nanostructure drives the differential response of neurons versus astrocytes in an in vitro model...
January 19, 2017: Advanced Functional Materials
https://www.readbyqxmd.com/read/28625485/motor-cortical-visuomotor-feedback-activity-is-initially-isolated-from-downstream-targets-in-output-null-neural-state-space-dimensions
#7
Sergey D Stavisky, Jonathan C Kao, Stephen I Ryu, Krishna V Shenoy
Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent...
June 6, 2017: Neuron
https://www.readbyqxmd.com/read/28620273/state-dependent-decoding-algorithms-improve-the-performance-of-a-bidirectional-bmi-in-anesthetized-rats
#8
Vito De Feo, Fabio Boi, Houman Safaai, Arno Onken, Stefano Panzeri, Alessandro Vato
Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28615329/physiological-properties-of-brain-machine-interface-input-signals
#9
Marc W Slutzky, Robert D Flint
Brain machine interfaces (BMIs), also called brain computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically-viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably the first of these is the selection of brain signals used to control BMIs. Here, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date...
June 14, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28612758/recording-nerve-signals-in-canine-sciatic-nerves-with-a-flexible-penetrating-microelectrode-array
#10
Donghak Byun, Sung-Joon Cho, Byeong Han Lee, Joongkee Min, Jong-Hyun Lee, Sohee Kim
OBJECTIVE: Previously, we presented the fabrication and characterization of a flexible penetrating microelectrode array (FPMA) as a neural interface device. In the present study, we aim to prove the feasibility of the developed FPMA as a chronic intrafascicular recording tool for peripheral applications. APPROACH: For recording from the peripheral nerves of medium-sized animals, the FPMA was integrated with an interconnection cable and other parts that were designed to fit canine sciatic nerves...
June 14, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28611621/whole-body-awareness-for-controlling-a-robotic-transfemoral-prosthesis
#11
Andrea Parri, Elena Martini, Joost Geeroms, Louis Flynn, Guido Pasquini, Simona Crea, Raffaele Molino Lova, Dirk Lefeber, Roman Kamnik, Marko Munih, Nicola Vitiello
Restoring locomotion functionality of transfemoral amputees is essential for early rehabilitation treatment and for preserving mobility and independence in daily life. Research in wearable robotics fostered the development of innovative active mechatronic lower-limb prostheses designed with the goal to reduce the cognitive and physical effort of lower-limb amputees in rehabilitation and daily life activities. To ensure benefits to the users, active mechatronic prostheses are expected to be aware of the user intention and properly interact in a closed human-in-the-loop paradigm...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28611611/a-synchronous-motor-imagery-based-neural-physiological-paradigm-for-brain-computer-interface-speller
#12
Lei Cao, Bin Xia, Oladazimi Maysam, Jie Li, Hong Xie, Niels Birbaumer
Brain Computer Interface (BCI) speller is a typical BCI-based application to help paralyzed patients express their thoughts. This paper proposed a novel motor imagery based BCI speller with Oct-o-spell paradigm for word input. Furthermore, an intelligent input method was used for improving the performance of the BCI speller. For the English word spelling experiment, we compared synchronous control with previous asynchronous control under the same experimental condition. There were no significant differences between these two control methods in the classification accuracy, information transmission rate (ITR) or letters per minute (LPM)...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28611579/stacked-autoencoders-for-the-p300-component-detection
#13
Lukáš Vařeka, Pavel Mautner
Novel neural network training methods (commonly referred to as deep learning) have emerged in recent years. Using a combination of unsupervised pre-training and subsequent fine-tuning, deep neural networks have become one of the most reliable classification methods. Since deep neural networks are especially powerful for high-dimensional and non-linear feature vectors, electroencephalography (EEG) and event-related potentials (ERPs) are one of the promising applications. Furthermore, to the authors' best knowledge, there are very few papers that study deep neural networks for EEG/ERP data...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28611575/ica-derived-eeg-correlates-to-mental-fatigue-effort-and-workload-in-a-realistically-simulated-air-traffic-control-task
#14
Deepika Dasari, Guofa Shou, Lei Ding
Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28602817/on-memories-neural-ensembles-and-mental-flexibility
#15
Dimitris A Pinotsis, Scott L Brincat, Earl K Miller
Memories are assumed to be represented by groups of co-activated neurons, called neural ensembles. Describing ensembles is a challenge: complexity of the underlying micro-circuitry is immense. Current approaches use a piecemeal fashion, focusing on single neurons and employing local measures like pairwise correlations. We introduce an alternative approach that identifies ensembles and describes the effective connectivity between them in a holistic fashion. It also links the oscillatory frequencies observed in ensembles with the spatial scales at which activity is expressed...
June 9, 2017: NeuroImage
https://www.readbyqxmd.com/read/28597847/mapping-the-fine-structure-of-cortical-activity-with-different-micro-ecog-electrode-array-geometries
#16
Xi Wang, Alexis Gkogkidis, Olga Iljina, Lukas Fiederer, Chiristian Henle, Irina Mader, Jan Kaminsky, Thomas Stieglitz, Mortimer Gierthmuehlen, Tonio Ball
OBJECTIVE: Innovations in micro-electrocorticography (µECoG) electrode array manufacturing now allow for intricate designs with smaller contact diameters and/or pitch (i.e., center-to-center contact distance) down to the sub-mm range. The aims of the present study were: (i) to investigate whether frequency ranges up to 400 Hz can be reproducibly observed in µECoG recordings and (ii) to examine how differences in topographical substructure between these frequency bands and electrode array geometries can be quantified...
June 9, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28596725/a-ternary-brain-computer-interface-based-on-single-trial-readiness-potentials-of-self-initiated-fine-movements-a-diversified-classification-scheme
#17
Elias Abou Zeid, Alborz Rezazadeh Sereshkeh, Benjamin Schultz, Tom Chau
In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have mainly attempted binary single-trial classification of RP. An RP-based BCI with three or more states would expand the options for functional control...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28578108/an-interpenetrating-microstructurable-and-covalently-attached-conducting-polymer-hydrogel-for-neural-interfaces
#18
Carolin Kleber, Michael Bruns, Karen Lienkamp, Jürgen Rühe, Maria Asplund
This study presents a new conducting polymer hydrogel (CPH) system, consisting of the synthetic hydrogel P(DMAA-co-5%MABP-co-2,5%SSNa) and the conducting polymer (CP) poly(3,4-ethylenedioxythiophene) (PEDOT), intended as coating material for neural interfaces. The composite material can be covalently attached to the surface electrode, can be patterned by a photolithographic process to influence selected electrode sites only and forms an interpenetrating network. The hybrid material was characterized using cyclic voltammetry (CV), impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS), which confirmed a homogeneous distribution of PEDOT throughout all CPH layers...
May 31, 2017: Acta Biomaterialia
https://www.readbyqxmd.com/read/28575181/deepsite-protein-binding-site-predictor-using-3d-convolutional-neural-networks
#19
J Jiménez, S Doerr, G Martínez-Rosell, A S Rose, G De Fabritiis
Motivation: An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years by clever exploitation of geometric, chemical and evolutionary features of the protein. Results: Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples...
May 31, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28573984/a-gaussian-mixture-model-based-adaptive-classifier-for-fnirs-brain-computer-interfaces-and-its-testing-via-simulation
#20
Zheng Li, Yi-Han Jiang, Lian Duan, Chao-Zhe Zhu
OBJECTIVE: Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC)...
June 2, 2017: Journal of Neural Engineering
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