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Srinivas Chivukula, Matiar Jafari, Tyson Aflalo, Nicholas Au Yong, Nader Pouratian
Millions of people worldwide are afflicted with paralysis from a disruption of neural pathways between the brain and the muscles. Because their cortical architecture is often preserved, these patients are able to plan movements despite an inability to execute them. In such people, brain machine interfaces have great potential to restore lost function through neuroprosthetic devices, circumventing dysfunctional corticospinal circuitry. These devices have typically derived control signals from the motor cortex (M1) which provides information highly correlated with desired movement trajectories...
2019: Frontiers in Neuroscience
Hyeonseok Kim, Natsue Yoshimura, Yasuharu Koike
Many previous studies on brain-machine interfaces (BMIs) have focused on electroencephalography (EEG) signals elicited during motor-command execution to generate device commands. However, exploiting pre-execution brain activity related to movement intention could improve the practical applicability of BMIs. Therefore, in this study we investigated whether EEG signals occurring before movement execution could be used to classify movement intention. Six subjects performed reaching tasks that required them to move a cursor to one of four targets distributed horizontally and vertically from the center...
2019: Frontiers in Human Neuroscience
Sofia Sakellaridi, Vassilios N Christopoulos, Tyson Aflalo, Kelsie W Pejsa, Emily R Rosario, Debra Ouellette, Nader Pouratian, Richard A Andersen
Although animal studies provided significant insights in understanding the neural basis of learning and adaptation, they often cannot dissociate between different learning mechanisms due to the lack of verbal communication. To overcome this limitation, we examined the mechanisms of learning and its limits in a human intracortical brain-machine interface (BMI) paradigm. A tetraplegic participant controlled a 2D computer cursor by modulating single-neuron activity in the anterior intraparietal area (AIP). By perturbing the neuron-to-movement mapping, the participant learned to modulate the activity of the recorded neurons to solve the perturbations by adopting a target re-aiming strategy...
March 1, 2019: Neuron
Ludovico Minati, Natsue Yoshimura, Mattia Frasca, Stanisław Drożdż, Yasuharu Koike
The entrainment between weakly coupled nonlinear oscillators, as well as between complex signals such as those representing physiological activity, is frequently assessed in terms of whether a stable relationship is detectable between the instantaneous phases extracted from the measured or simulated time-series via the analytic signal. Here, we demonstrate that adding a possibly complex constant value to this normally null-mean signal has a non-trivial warping effect. Among other consequences, this introduces a level of sensitivity to the amplitude fluctuations and average relative phase...
February 2019: Chaos
Jun Dai, Peng Zhang, Hongji Sun, Xin Qiao, Yuwei Zhao, Jinxu Ma, Shaohua Li, Jin Zhou, Changyong Wang
OBJECTIVE: For intracortical neurophysiological studies, spike sorting is an important procedure to isolate single units for analyzing specific functions. However, whether spike sorting is necessary or not for neural decoding applications is controversial. Several studies showed that using threshold crossings (TC) instead of spike sorting could also achieve a similar satisfactory performance. However, such studies were limited in similar behavioral tasks, and the neural signal source mainly focused on the motor-related cortical regions...
March 1, 2019: Journal of Neural Engineering
Xiao Yang, Tao Zhou, Theodore J Zwang, Guosong Hong, Yunlong Zhao, Robert D Viveros, Tian-Ming Fu, Teng Gao, Charles M Lieber
As an important application of functional biomaterials, neural probes have contributed substantially to studying the brain. Bioinspired and biomimetic strategies have begun to be applied to the development of neural probes, although these and previous generations of probes have had structural and mechanical dissimilarities from their neuron targets that lead to neuronal loss, neuroinflammatory responses and measurement instabilities. Here, we present a bioinspired design for neural probes-neuron-like electronics (NeuE)-where the key building blocks mimic the subcellular structural features and mechanical properties of neurons...
February 25, 2019: Nature Materials
Nir Even-Chen, Blue Sheffer, Saurabh Vyas, Stephen I Ryu, Krishna V Shenoy
Voluntary movements are widely considered to be planned before they are executed. Recent studies have hypothesized that neural activity in motor cortex during preparation acts as an 'initial condition' which seeds the proceeding neural dynamics. Here, we studied these initial conditions in detail by investigating 1) the organization of neural states for different reaches and 2) the variance of these neural states from trial to trial. We examined population-level responses in macaque premotor cortex (PMd) during the preparatory stage of an instructed-delay center-out reaching task with dense target configurations...
February 22, 2019: PLoS Computational Biology
Vincenzo Catrambone, Alberto Greco, Giuseppe Averta, Matteo Bianchi, Gaetano Valenza, Enzo Pasquale Scilingo
Recent functional magnetic resonance imaging (fMRI) studies have identified specific neural patterns related to three different categories of movements: intransitive (i.e., meaningful gestures that do not include the use of objects), transitive (i.e., actions involving an object), and tool-mediated (i.e., actions involving a tool to interact with an object). However, fMRI intrinsically limits the exploitation of these results in a real scenario, such as a brain-machine interface (BMI). In this study, we propose a new approach to automatically predict intransitive, transitive, or tool-mediated movements of the upper limb using electroencephalography (EEG) spectra estimated during a motor planning phase...
February 11, 2019: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Filipe O Barroso, Bryan Yoder, David Tentler, Josephine Wallner, Amina Kinkhabwala, Maria K Jantz, Robert D Flint, Pablo Tostado, Evonne Pei, Ambika Satish, Sarah Brodnick, Aaron Suminski, Justin C Williams, Lee E Miller, Matthew Tresch
OBJECTIVE: Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery...
February 12, 2019: Journal of Neural Engineering
Yoon Jae Kim, Hyung Seok Nam, Woo Hyung Lee, Han Gil Seo, Ja-Ho Leigh, Byung-Mo Oh, Moon Suk Bang, Sungwan Kim
BACKGROUND: While spontaneous robotic arm control using motor imagery has been reported, most previous successful cases have used invasive approaches with advantages in spatial resolution. However, still many researchers continue to investigate methods for robotic arm control with noninvasive neural signal. Most of noninvasive control of robotic arm utilizes P300, steady state visually evoked potential, N2pc, and mental tasks differentiation. Even though these approaches demonstrated successful accuracy, they are limited in time efficiency and user intuition, and mostly require visual stimulation...
February 11, 2019: Biomedical Engineering Online
Ander Ramos-Murguialday, Marco R Curado, Doris Broetz, Özge Yilmaz, Fabricio L Brasil, Giulia Liberati, Eliana Garcia-Cossio, Woosang Cho, Andrea Caria, Leonardo G Cohen, Niels Birbaumer
BACKGROUND: Brain-machine interfaces (BMIs) have been recently proposed as a new tool to induce functional recovery in stroke patients. OBJECTIVE: Here we evaluated long-term effects of BMI training and physiotherapy in motor function of severely paralyzed chronic stroke patients 6 months after intervention. METHODS: A total of 30 chronic stroke patients with severe hand paresis from our previous study were invited, and 28 underwent follow-up assessments...
February 5, 2019: Neurorehabilitation and Neural Repair
Shaomin Zhang, Sheng Yuan, Lipeng Huang, Xiaoxiang Zheng, Zhaohui Wu, Kedi Xu, Gang Pan
Brain-machine interfaces (BMIs) provide a promising information channel between the biological brain and external devices and are applied in building brain-to-device control. Prior studies have explored the feasibility of establishing a brain-brain interface (BBI) across various brains via the combination of BMIs. However, using BBI to realize the efficient multidegree control of a living creature, such as a rat, to complete a navigation task in a complex environment has yet to be shown. In this study, we developed a BBI from the human brain to a rat implanted with microelectrodes (i...
February 4, 2019: Scientific Reports
Samuel A Budoff, Kim M Yano, Fernanda C de Mesquita, Jhulimar G Doerl, Maxwell B de Santana, Manuela S L Nascimento, Ana Carolina B Kunicki, Mariana F P de Araújo
Microelectrode implants are an important tool in neuroscience research and in developing brain⁻machine interfaces. Data from rodents have consistently shown that astrocytes are recruited to the area surrounding implants, forming a glial scar that increases electrode impedance and reduces chronic utility. However, studies in non-human primates are scarce, with none to date in marmosets. We used glial fibrillary acidic protein (GFAP) immunostaining to characterize the acute and chronic response of the marmoset brain to microelectrodes...
January 23, 2019: Brain Sciences
Taiki Yasui, Shota Yamagiwa, Hirohito Sawahata, Shinnosuke Idogawa, Yoshihiro Kubota, Yuto Kita, Koji Yamashita, Rika Numano, Kowa Koida, Takeshi Kawano
Microelectrode devices, which enable the detection of neuronal signals in brain tissues, have made significant contributions in the field of neuroscience and the brain-machine interfaces. To further develop such microelectrode devices, the following requirements must be met: i) a fine needle's diameter (<30 µm) to reduce damage to tissues; ii) a long needle (e.g., ≈1 mm for rodents and ≈2 mm for macaques); and iii) multiple electrodes to achieve high spatial recording (<100 µm in pitch). In order to meet these requirements, this study herein reports an assembly technique for high-aspect-ratio microneedles, which employs a magnet...
January 15, 2019: Advanced Healthcare Materials
Jong-Ryul Choi, Seong-Min Kim, Rae-Hyung Ryu, Sung-Phil Kim, Jeong-Woo Sohn
A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings...
December 2018: Experimental Neurobiology
Tessy M Thomas, Daniel N Candrea, Matthew S Fifer, David P McMullen, William S Anderson, Nitish V Thakor, Nathan E Crone
Brain-machine interface (BMI) researchers have traditionally focused on modeling endpoint reaching tasks to provide control of neurally-driven prosthetic arms. Most previous research has focused on achieving endpoint control through a Cartesian-coordinate-centered approach. However, a joint-centered approach could potentially be used to intuitively control a wide range of limb movements. We systematically investigated the feasibility of discriminating between flexion and extension of different upper limb joints using electrocorticography (ECoG) recordings from sensorimotor cortex...
January 7, 2019: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Raquel Carvalho, Nuno Dias, João José Cerqueira
BACKGROUND: Technologies such as brain-computer interfaces are able to guide mental practice, in particular motor imagery performance, to promote recovery in stroke patients, as a combined approach to conventional therapy. OBJECTIVE: The aim of this systematic review was to provide a status report regarding advances in brain-computer interface, focusing in particular in upper limb motor recovery. METHODS: The databases PubMed, Scopus, and PEDro were systematically searched for articles published between January 2010 and December 2017...
January 4, 2019: Physiotherapy Research International: the Journal for Researchers and Clinicians in Physical Therapy
Chandramouli Chandrasekaran, Iliana E Bray, Krishna V Shenoy
Neural activity in the premotor and motor cortices shows prominent structure in the beta frequency range (13-30 Hz). Currently, the behavioral relevance of this beta band activity (BBA) is debated. The underlying source of motor BBA and how it changes as a function of cortical depth is also not completely understood. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex (PMd) of two male rhesus macaques performing a visual reaction time (RT) reach discrimination task...
January 3, 2019: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Juan A Barios, Santiago Ezquerro, Arturo Bertomeu-Motos, Marius Nann, Fco Javier Badesa, Eduardo Fernandez, Surjo R Soekadar, Nicolas Garcia-Aracil
Modulation of sensorimotor rhythm (SMR) power, a rhythmic brain oscillation physiologically linked to motor imagery, is a popular Brain-Machine Interface (BMI) paradigm, but its interplay with slower cortical rhythms, also involved in movement preparation and cognitive processing, is not entirely understood. In this study, we evaluated the changes in phase and power of slow cortical activity in delta and theta bands, during a motor imagery task controlled by an SMR-based BMI system. In Experiment I, EEG of 20 right-handed healthy volunteers was recorded performing a motor-imagery task using an SMR-based BMI controlling a visual animation, and during task-free intervals...
October 24, 2018: International Journal of Neural Systems
Hongbo Liang, Chi Zhu, Yu Iwata, Shota Maedono, Mika Mochita, Chang Liu, Naoya Ueda, Peirang Li, Haoyong Yu, Yuling Yan, Feng Duan
Brain-Machine Interface (BMI) has been considered as an effective way to help and support both the disabled rehabilitation and healthy individuals' daily lives to use their brain activity information instead of their bodies. In order to reduce costs and control exoskeleton robots better, we aim to estimate the necessary torque information for a subject from his/her electroencephalography (EEG) signals when using an exoskeleton robot to perform the power assistance of the upper limb without using external torque sensors nor electromyography (EMG) sensors...
December 24, 2018: Bioengineering
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