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Journal of Neural Engineering

Aline F Renz, Andreas M Reichmuth, Flurin Stauffer, Greta Thompson-Steckel, Janos Vörös
Implantable electronics address therapeutical needs of patients with electrical signaling dysfunctions such as heart problems, neurological disorders or hearing impairments. While standard electronics are rigid, planar and made of hard materials, their surrounding biological tissues are soft, wet and constantly in motion. These intrinsic differences in mechanical and chemical properties cause physiological responses that constitute a fundamental challenge to create functional long-term interfaces. Using soft and stretchable materials for electronic implants decreases the mechanical mismatch between implant and biological tissues...
October 16, 2018: Journal of Neural Engineering
L Bashford, J Wu, D Sarma, K Collins, R P N Rao, J G Ojemann, C Mehring
OBJECTIVE: A primary control signal in brain-computer interfaces (BCIs) have been cortical signals related to movement. However, in cases where natural motor function remains, BCI control signals may interfere with other possibly simultaneous activity for useful ongoing movement. We sought to determine if the brain could learn to control both a BCI and concurrent overt movement execution in such cases. APPROACH: We designed experiments where BCI and overt movements must be used concurrently and in coordination to achieve a 2D centre out control...
October 10, 2018: Journal of Neural Engineering
Nicholas Waytowich, Vernon J Lawhern, Javier O Garcia, Jennifer Cummings, Josef Faller, Paul Sajda, Jean M Vettel
OBJECTIVE: Steady-state visual evoked potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram (EEG) and are commonly used in brain-computer interfaces (BCIs). However, methods for high-accuracy decoding of SSVEPs usually require hand-crafted approaches that leverage domain-specific knowledge of the stimulus signals, such as specific temporal frequencies in the visual stimuli and their relative spatial arrangement...
October 3, 2018: Journal of Neural Engineering
Vaclav Kremen, Benjamin Henry Brinkmann, Jamie J Van Gompel, Squire Matt M Stead, Erik K St Louis, Gregory A Worrell
OBJECTIVE: Automated behavioral state classification in intracranial EEG (iEEG) recordings may be beneficial for iEEG interpretation and quantifying sleep patterns to enable behavioral state dependent neuromodulation therapy in next generation implantable brain stimulation devices. Here, we introduce a fully automated unsupervised framework to differentiate between awake (AW), sleep (N2), and slow wave sleep (N3) using intracranial EEG (iEEG) only and validated with expert scored polysomnography...
October 2, 2018: Journal of Neural Engineering
Neethu Robinson, Kavitha P Thomas, A P Vinod
Neural engineering research is actively engaged in optimizing the robustness of sensorimotor rhythms (SMR)-brain-computer interface (BCI) to boost its potential real-world use. OBJECTIVE: This paper investigates two vital factors in efficient and robust SMR-BCI design-algorithms that address subject-variability of optimal features and neurophysiological factors that correlate with BCI performance. Existing SMR-BCI research using electroencephalogram (EEG) to classify bilateral motor imagery (MI) focus on identifying subject-specific frequency bands with most discriminative motor patterns localized to sensorimotor region...
October 2, 2018: Journal of Neural Engineering
Daria Nesterovich Anderson, Gordon Duffley, Johannes Vorwerk, Alan Chuck Dorval, Christopher R Butson
 During deep brain stimulation (DBS), it is well understood that extracellular cathodic stimulation can cause activation of passing axons. Activation can be predicted from the second derivative of the electric potential along an axon, which depends on axonal orientation with respect to the stimulation source. We hypothesize that fiber orientation influences activation thresholds and that fiber orientations can be selectively targeted with DBS waveforms.
 Approach: We used bioelectric field and multicompartment NEURON models to explore preferential activation based on fiber orientation during monopolar or bipolar stimulation...
October 2, 2018: Journal of Neural Engineering
Mads Jochumsen, Muhammad Shafique, Ali Hassan, Imran Khan Niazi
OBJECTIVE: As for stroke rehabilitation, brain-computer interfaces could potentially be used for inducing neural plasticity in patients with cerebral palsy by pairing movement intentions with relevant somatosensory feedback. Therefore, the aim of this study was to investigate if movement intentions from children with cerebral palsy can be detected from single-trial EEG. Moreover, different feature types and electrode setups were evaluated. APPROACH: Eight adolescents with cerebral palsy performed self-paced dorsiflexions of the ankle while nine channels of EEG were recorded...
September 27, 2018: Journal of Neural Engineering
Janak Gaire, Heui Chang Lee, Nicholas Hilborn, Ray Ward, Mary Regan, Kevin J Otto
Neuroinflammation has long been associated with the performance decline of intracortical microelectrodes (IMEs). Consequently, several strategies, including the use of anti-inflammatories, have been employed to mitigate the inflammation surrounding IMEs. However, these strategies have had limited success towards achieving a chronically viable cortical neural interface, questioning the efficacy of anti-inflammatory approach. Herein, we conducted a systematic study in rats implanted with functional devices by modulating inflammation via systemic injection of lipopolysaccharide (LPS), dexamethasone (DEX), a combination of both, or none to assess the degree of inflammation on device functionality...
September 27, 2018: Journal of Neural Engineering
Alborz Rezazadeh Sereshkeh, Rozhin Yousefi, Andrew T Wong, Tom Chau
Most brain-computer interfaces (BCIs) based on functional near-infrared spectroscopy (fNIRS) require that users perform mental tasks such as motor imagery, mental arithmetic, or music imagery to convey a message or to answer simple yes or no questions. These cognitive tasks usually have no direct association with the communicative intent, which makes them difficult for users to perform. In this paper, a 3-class intuitive BCI is presented which enables users to directly answer yes or no questions by covertly rehearsing the word "yes" or "no" for 15 s...
September 27, 2018: Journal of Neural Engineering
D L Rathbun, N Ghorbani, H Shabani, E Zrenner, Z Hosseinzadeh
Bionic retinal implants are gaining acceptance in the treatment of blindness from degenerative diseases including retinitis pigmentosa and macular degeneration. OBJECTIVE: A current obstacle to the improved performance of such implants is the difficulty of comparing the results of disparate experiments. Another obstacle is the current difficulty in selectively activating the many different retinal ganglion cell types that are used as separate pathways for visual information to the brain...
September 27, 2018: Journal of Neural Engineering
Leon Li, Serban Negoita
Advances in electrophysiological methods such as electrocorticography (ECoG) have enabled researchers to decode phonemes, syllables, and words from brain activity. The ultimate aspiration underlying these efforts is the development of a brain-machine interface (BMI) that will enable speakers to produce real-time, naturalistic speech. In the effort to create such a device, researchers have typically followed a bottom-up approach whereby low-level units of language (e.g., phonemes, syllables, or letters) are decoded from articulation areas (e...
September 26, 2018: Journal of Neural Engineering
Virginia Woods, Michael Trumpis, Brinnae Bent, Kay Palopoli-Trojani, Chia-Han Chiang, Charles Wang, Chunxiu Yu, Michele Insanally, Robert C Froemke, Jonathan Viventi
OBJECTIVE: The clinical use of microsignals recorded over broad cortical regions is largely limited by the chronic reliability of the implanted interfaces. APPROACH: We evaluated the chronic reliability of novel 61-channel micro-electrocorticographic (µECoG) arrays in rats chronically implanted for over one year and using accelerated aging. Devices were encapsulated with polyimide (PI) or liquid crystal polymer (LCP), and fabricated using commercial manufacturing processes...
September 24, 2018: Journal of Neural Engineering
Elizaveta V Okorokova, Qinpu He, Sliman J Bensmaia
OBJECTIVE: Hand function can be restored in upper-limb amputees by equipping them with anthropomorphic prostheses controlled with signals from residual muscles. The dexterity of these bionic hands is severely limited in large part by the absence of tactile feedback about interactions with objects. We propose that, to the extent that artificial touch mimics its natural counterpart, these sensory signals will be more easily integrated into the motor plan for object manipulation. APPROACH: We describe an approach to convey tactile feedback through electrical stimulation of the residual somatosensory nerves that mimics the aggregate activity of tactile fibers that would be produced in the nerve of a native hand during object interactions...
September 24, 2018: Journal of Neural Engineering
Efraïm Salari, Zachary V Freudenburg, Mariska J Vansteensel, Nick Ramsey
 In recent years, brain-computer interface (BCI) systems have been investigated for their potential as a communication device to assist people with severe paralysis. Decoding speech sensorimotor cortex activity is a promising avenue for the generation of BCI control signals, but is complicated by variability in neural patterns, leading to suboptimal decoding. We investigated whether neural pattern variability associated with sound pronunciation can be explained by prior pronunciations and determined to what extent prior speech affects BCI decoding accuracy...
September 21, 2018: Journal of Neural Engineering
A M De Nunzio, M A Schweisfurth, N Ge, D Falla, J Hahne, K Gödecke, F Petzke, M Siebertz, P Dechent, T Weiss, H Flor, B Graimann, O C Aszmann, D Farina
OBJECTIVE: The causes for the disabling condition of phantom limb pain (PLP), affecting 85% of amputees, are so far unknown, with few effective treatments available. Sensory feedback based strategies to normalize the motor commands to control the phantom limb offer important targets for new effective treatments as the correlation between phantom limb motor control and sensory feedback from the motor intention has been identified as a possible mechanism for PLP development. APPROACH: Ten upper-limb amputees, suffering from chronic PLP, underwent 16 days of intensive training on phantom-limb movement control...
September 19, 2018: Journal of Neural Engineering
Massimo Sartori, Guillaume Durandau, Strahinja Dosen, Dario Farina
OBJECTIVES: Robotic prosthetic limbs promise to replace mechanical function of lost biological extremities and restore amputees' capacity of moving and interacting with the environment. Despite recent advances in biocompatible electrodes, surgical procedures, and mechatronics, the impact of current solutions is hampered by the lack of intuitive and robust man-machine interfaces. APPROACH: Based on authors' developments, this work presents a biomimetic interface that synthetizes the musculoskeletal function of an individual's phantom limb as controlled by neural surrogates, i...
September 19, 2018: Journal of Neural Engineering
Xu Han, Ke Lin, Shangkai Gao, Xiaorong Gao
Human-robot coordination (HRC) aims to enable human and robot form a tightly coupled system to accomplish a task. One of its important application prospects is to improve the physical function of the disabled. However, the low level of the coordination between human and robot and the limited potential users still hampered the efficiency of such systems. 
 Methods: To deal with such challenges, a novel steady-state visual evoked potential (SSVEP) based human-robot coordinated BCI system was proposed to finish a target capturing task...
September 17, 2018: Journal of Neural Engineering
Yuxiao Yang, Allison T Connolly, Maryam M Shanechi
OBJECTIVE: Closed-loop electrical brain stimulation systems may enable a precisely-tailored treatment for neurological and neuropsychiatric disorders by controlling the stimulation based on neural activity feedback in real time. Developing model-based closed-loop systems requires a principled system identification framework to quantify the effect of input stimulation on output neural activity by learning an input-output (IO) dynamic model from data. Further, developing these systems needs a realistic clinical simulation testbed to design and validate the closed-loop controllers derived from the IO models before testing in human patients...
September 17, 2018: Journal of Neural Engineering
Zied Tayeb, Nicolai Waniek, Juri Fedjaev, Nejla Ghaboosi, Leonard Rychly, Christian Widderich, Christoph Richter, Jonas Braun, Matteo Saveriano, Gordon Cheng, Jörg Conradt
OBJECTIVE: The objective of this work is to present gumpy, a new free and open source Python toolbox designed for hybrid brain-computer interface (BCI). APPROACH: Gumpy provides state-of-the-art algorithms and includes a rich selection of signal processing methods that have been employed by the BCI community over the last 20 years. In addition, a wide range of classification methods that span from classical machine learning algorithms to deep neural network models are provided...
September 14, 2018: Journal of Neural Engineering
Marta Jole Ildelfonsa Airaghi Leccardi, Paola Vagni, Diego Ghezzi
OBJECTIVE: In many applications, multielectrode arrays employed as neural implants require a high density and a high number of electrodes to precisely record and stimulate the activity of the nervous system while preserving the overall size of the array as little as possible. APPROACH: Here we present a multilayer and three-dimensional (3D) electrode array, together with its manufacturing method, enabling a higher electrode density and a more efficient signal transduction with the biological tissue...
September 14, 2018: Journal of Neural Engineering
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