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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
Alessandro Marco De Nunzio, Meike Annika Schweisfurth, Nan Ge, Deborah Falla, Janne Mathias Hahne, Kim Gödecke, Frank Petzke, Mathias Siebertz, Peter Dechent, Thomas Weiss, Herta Flor, Bernhard Graimann, Oskar Aszmann, Dario Farina
 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. 
 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, Jorg 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
Tong Wu, Wenfeng Zhao, Edward Keefer, Zhi Yang
Understanding the coordinated activity underlying brain computations requires large-scale, simultaneous recordings from distributed neuronal structures at a cellular-level resolution. One major hurdle to design high-bandwidth, high-precision, large-scale neural interfaces lies in the formidable data streams (tens to hundreds of Gbps) that are generated by the recorder chip and need to be online transferred to a remote computer. The data rates can require hundreds to thousands of I/O pads on the recorder chip and power consumption on the order of Watts for data streaming alone...
September 14, 2018: Journal of Neural Engineering
Gary Garcia Molina, Tsvetomira Kirova Tsoneva, Jeff Jasko, Brenda Steele, Antonio Aquino, Keith Baehr, Sander Pastoor, Stefan Pfundtner, Lynn Ostrowski, Barbara Miller, Noah Papas, Brady Riedner, Giulio Tononi, David P White
Recent evidence reports cognitive, metabolic, and sleep restoration benefits resulting from the enhancement of sleep slow-waves using auditory stimulation. To make this concept practical for a consumer user, we have developed an integrated wearable closed-loop electroencephalogram (EEG) based system to deliver auditory stimulation during sleep. The stimulation is in the form of 50-millisecond-long tones separated by a constant one-second inter-tone interval at a volume that is dynamically modulated such that louder tones are delivered when sleep is deeper...
September 14, 2018: Journal of Neural Engineering
Edgar Peña, Simeng Zhang, Remi Patriat, Joshua E Aman, Jerrold L Vitek, Noam Harel, Matthew D Johnson
The effectiveness of deep brain stimulation (DBS) therapy strongly depends on precise surgical targeting of intracranial leads and on clinical optimization of stimulation settings. Recent advances in surgical targeting, multi-electrode designs, and multi-channel independent current-controlled stimulation are poised to enable finer control in modulating pathways within the brain. However, the large stimulation parameter space enabled by these technologies also poses significant challenges for efficiently identifying the most therapeutic DBS setting for a given patient...
September 13, 2018: Journal of Neural Engineering
Akshay Arora, Jui-Jui Lin, Alec Gasperian, Joel Stein, Joseph Maldjian, Michael J Kahana, Bradley Lega
We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordings obtained from human stereo EEG subjects. We also sought to test the impact of applying t-distributed stochastic neighbor embedding (tSNE) for unsupervised dimensionality reduction, as well as testing the effect of reducing input features to a core set of memory relevant brain areas...
September 13, 2018: Journal of Neural Engineering
Ishita Basu, Britni Crocker, Kara Farnes, Madeline Robertson, Angelique C Paulk, Deborah Vallejo, Darin D Dougherty, Sydney S Cash, Emad N Eskandar, Mark Kramer, Alik S Widge
Deep brain stimulation (DBS) is a valuable tool for ameliorating drug resistant pathologies such as movement disorders and epilepsy. DBS is also being considered for complex neuro-psychiatric disorders, which are characterized by high variability in symptoms and slow responses that hinder DBS setting optimization. The objective of this work was to develop an in-silico platform to examine the effects of electrical stimulation in regions neighboring a stimulated brain region. 
 Approach: We used the Jansen-Rit neural mass model of single and coupled nodes to simulate the response to a train of electrical current pulses at different frequencies (10-160 Hz) of the local field potential recorded in the amygdala and cortical structures in human subjects and a non-human primate...
September 13, 2018: Journal of Neural Engineering
Parastoo Khoshakhlagh, Ashwin Sivakumar, Lauren Pace, Daniel Sazer, Michael J Moore
OBJECTIVE: The cost and low success rates of the neurological drug development pipeline have diverted the pharmaceutical industry to 'nerve-on-a-chip' systems as preclinical models to streamline drug development. We present a novel micro-engineered 3D hydrogel platform for the culture of myelinated embryonic peripheral neural tissue to serve as an effective in vitro model for electrophysiological and histological analysis that could be adopted for preclinical testing. APPROACH: Dorsal root ganglions (DRG) from 15-day old embryonic rats were cultured in 3D hydrogel platforms...
September 13, 2018: Journal of Neural Engineering
Zhenhu Liang, Yasuyo Minagawa, Ho-Ching Yang, Hao Tian, Lei Cheng, Takeshi Arimitsu, Takao Takahashi, Yunjie Tong

 Objective: Assessing infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS...
September 12, 2018: Journal of Neural Engineering
Neetha Das, Alexander Bertrand, Tom Francart
<i>Objective</i>. A listener's neural responses can be decoded to identify the speaker the person is attending to in a cocktail party environment. Such auditory attention detection methods have the potential to provide noise suppression algorithms in hearing devices with information about the listener's attention. A challenge is the effect of noise and other acoustic conditions that can reduce the attention detection accuracy. Specifically, noise can impact the ability of the person to segregate the sound sources and perform selective attention, as well as the external signal processing necessary to decode the attention effectively...
September 12, 2018: Journal of Neural Engineering
Stefan Ehrlich, Gordon Cheng
Error-related potentials (ErrP) have been proposed as an intuitive feedback signal decoded from the ongoing electroencephalogram (EEG) of a human observer for improving human-robot interaction (HRI). While recent demonstrations of this approach have successfully studied the use of ErrPs as a teaching signal for robot skill learning, so far, no efforts have been made towards HRI scenarios where mutual adaptations between human and robot are expected or required. These are collaborative or social interactive scenarios without predefined dominancy of the human partner and robots being perceived as intentional agents...
September 11, 2018: Journal of Neural Engineering
Albertine Dubois, Chih-Chieh Chiang, François Smekens, Sebastien Jan, Vesna Cuplov, Stephane Palfi, Keh-Shih Chuang, Suhan Senova, Frederic Pain
The use of optogenetics or photobiomodulation in non-human primate (NHP) requires the ability to noninvasively stimulate large and deep cortical brain tissues volumes. In this context, the optical and geometrical parameters of optodes are critical. We propose the design of an optode for safe and efficient optical stimulation of a large volume of NHP cortex, down to 3-5 mm depths without inserting fibers into the cortex. Monte Carlo simulations of optical and thermal transport have been carried out using the Geant4 Application for Tomographic Emission (GATE) platform...
September 7, 2018: Journal of Neural Engineering
Tushar Chouhan, Neethu Robinson, Vinod A Prasad, Kai Keng Ang, Cuntai Guan
&lt;i&gt;Objective&lt;/i&gt;. Brain signals can be used to extract relevant features to decode various limb movement parameters such as direction of upper limb movements. Amplitude based feature extraction techniques have been used to study such motor activity of upper limbs whereas phase synchrony, used to estimate functional relationship between signals, has rarely been used to study single hand movements in different directions. &lt;i&gt;Approach&lt;/i&gt;. In this paper, a novel phase-locking-based feature extraction method, called Wavelet Phase-Locking Value (W-PLV) is proposed to analyse synchronous EEG channel-pairs and classify hand movement directions...
September 5, 2018: Journal of Neural Engineering
Ancor Sanz-Garcia, Miriam Perez-Romero, Jesus Pastor, Rafael G Sola, Lorena Vega-Zelaya, Fernando Monasterio, Carmen Torrecilla, Gema Vega, Paloma Pulido, Guillermo J Ortega
To exploring and assessing the relationship between the electroencephalography (EEG) activity with the intracranial pressure (ICP) in patients suffering from Traumatic Brain Injury (TBI) and Subarachnoid Hemorrhage (SAH) during their stay at the Intensive Care Unit (ICU)&#13; Methods: We performed an observational prospective cohort study of adult patients suffered from TBI or SAH. Continuous EEG-ECG was performed during ICP monitoring. In every patient, derived variables from the EEG were calculated and the Granger Causality (GC) methodology was employed to assess whether, and in which direction, any relationship between EEG and ICP exists...
September 5, 2018: Journal of Neural Engineering
Wendy Yen Xian Peh, Marlena Natalia Raczkowska, Yuni Teh, Monzurul Alam, Nitish Thakor, Shih-Cheng Yen
&lt;i&gt;Objective&lt;/i&gt; Neural stimulation to restore bladder function has traditionally relied on open-loop approaches that used pre-set parameters, which do not adapt to suboptimal outcomes. The goal of this study was to examine the effectiveness of a novel closed-loop stimulation paradigm for improving micturition or bladder voiding. &lt;i&gt;Approach&lt;/i&gt; We compared the voiding efficiency obtained with this closed-loop framework against open-loop stimulation paradigms in anesthetized rats...
September 5, 2018: Journal of Neural Engineering
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