Evoking stable and precise tactile sensations via multi-electrode intracortical microstimulation of the somatosensory cortex.

Tactile feedback from brain-controlled bionic hands can be partially restored via intracortical microstimulation (ICMS) of the primary somatosensory cortex. In ICMS, the location of percepts depends on the electrode's location and the percept intensity depends on the stimulation frequency and amplitude. Sensors on a bionic hand can thus be linked to somatotopically appropriate electrodes, and the contact force of each sensor can be used to determine the amplitude of a stimulus.

Somatosensory cortex and body representation: Updating the motor system during a visuo-proprioceptive cue conflict.

The brain's representation of hand position is critical for voluntary movement. Representation is multisensory, relying on both visual and proprioceptive cues. When these cues conflict, the brain recalibrates its unimodal estimates, shifting them closer together to compensate.

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark.

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neural data are often nonstationary, which can lead to decoder failure if not accounted for. To maintain performance, users must frequently recalibrate decoders, which requires the arduous collection of new neural and behavioral data.

Unsupervised, piecewise linear decoding enables an accurate prediction of muscle activity in a multi-task brain computer interface.

Objective: Creating an intracortical brain-computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI decoder. We aimed to develop a method that differs from a globally optimized decoder to address this issue.

Motor Cortex Latent Dynamics Encode Spatial and Temporal Arm Movement Parameters Independently.

The fluid movement of an arm requires multiple spatiotemporal parameters to be set independently. Recent studies have argued that arm movements are generated by the collective dynamics of neurons in motor cortex. An untested prediction of this hypothesis is that independent parameters of movement must map to independent components of the neural dynamics.

Less is more: selection from a small set of options improves BCI velocity control.

We designed the discrete direction selection (DDS) decoder for intracortical brain computer interface (iBCI) cursor control and showed that it outperformed currently used decoders in a human-operated real-time iBCI simulator and in monkey iBCI use. Unlike virtually all existing decoders that map between neural activity and continuous velocity commands, DDS uses neural activity to select among a small menu of preset cursor velocities. We compared closed-loop cursor control across four visits by each of 48 naïve, able-bodied human subjects using either DDS or one of three common continuous velocity decoders: direct regression with assist (an affine map from neural activity to cursor velocity), ReFIT, and the velocity Kalman Filter.

Topology of surface electromyogram signals: hand gesture decoding on Riemannian manifolds.

. Decoding gestures from the upper limb using noninvasive surface electromyogram (sEMG) signals is of keen interest for the rehabilitation of amputees, artificial supernumerary limb augmentation, gestural control of computers, and virtual/augmented realities. We show that sEMG signals recorded across an array of sensor electrodes in multiple spatial locations around the forearm evince a rich geometric pattern of global motor unit (MU) activity that can be leveraged to distinguish different hand gestures.

6-Mercaptopurine-associated Sinusoidal Obstructive Syndrome During Interim Maintenance I: A Case Report.

Thiopurine-methyltransferase (TPMT) and nudix-hydrolase-15 (NUDT15) are enzymes relevant to the metabolism of thiopurine medications, used to treat immunologic disorders and malignancies. Standard dosing administered in the setting of TPMT/NUDT15 dysfunction can cause excessive cytotoxic metabolites and life-threatening complications. We describe an adolescent with high-risk B-cell acute lymphoblastic leukemia (ALL) whose TPMT/NUDT15 status was unknown due to lack of insurance approval for genetic testing.

Injectable bioactive poly(propylene fumarate) and polycaprolactone based click chemistry bone cement for spinal fusion in rabbits.

Degenerative spinal pathology is a widespread medical issue, and spine fusion surgeries are frequently performed. In this study, we fabricated an injectable bioactive click chemistry polymer cement for use in spinal fusion and bone regrowth. Taking advantages of the bioorthogonal click reaction, this cement can be crosslinked by itself eliminating the addition of a toxic initiator or catalyst, nor any external energy sources like UV light or heat.

BRAND: a platform for closed-loop experiments with deep network models.

Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g.

Task-driven neural network models predict neural dynamics of proprioception.

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1).

Electrophysiological study of visual processing in children with cochlear implants.

Electrophysiological studies of congenitally deaf children and adults have reported atypical visual evoked potentials (VEPs) which have been associated with both behavioral enhancements of visual attention as well as poorer performance and outcomes in tests of spoken language speech processing. This pattern has often been interpreted as a maladaptive consequence of early auditory deprivation, whereby a remapping of auditory cortex by the visual system ultimately reduces resources necessary for optimal rehabilitative outcomes of spoken language acquisition and use. Making use of a novel electrophysiological paradigm, we compare VEPs in children with severe to profound congenital deafness who received a cochlear implant(s) prior to 31 months (n = 28) and typically developing age matched controls (n = 28).

Spinal fusion of biodegradable poly(propylene fumarate) and poly(propylene fumarate-co-caprolactone) copolymers in rabbits.

Background: Autologous bone grafts are currently the standard in orthopedic surgery despite limited donor sources and the prevalence of donor site morbidity. Other alternatives such as allografts are more readily available than autografts but have lower rates of graft incorporation.

Methods: Here, we propose a novel graft alternative consisting of an injectable poly(propylene fumarate) (PPF) and poly(propylene fumarate-co-caprolactone) P(PF--CL) copolymer with a recombinant human bone morphogenetic protein-2 (rhBMP-2)/vascular epithelial growth factor (VEGF) release system accompanied by hydroxyapatite (HA).

Fully implanted battery-free high power platform for chronic spinal and muscular functional electrical stimulation.

Electrical stimulation of the neuromuscular system holds promise for both scientific and therapeutic biomedical applications. Supplying and maintaining the power necessary to drive stimulation chronically is a fundamental challenge in these applications, especially when high voltages or currents are required. Wireless systems, in which energy is supplied through near field power transfer, could eliminate complications caused by battery packs or external connections, but currently do not provide the harvested power and voltages required for applications such as muscle stimulation.

Microstimulation of human somatosensory cortex evokes task-dependent, spatially patterned responses in motor cortex.

The primary motor (M1) and somatosensory (S1) cortices play critical roles in motor control but the signaling between these structures is poorly understood. To fill this gap, we recorded - in three participants in an ongoing human clinical trial (NCT01894802) for people with paralyzed hands - the responses evoked in the hand and arm representations of M1 during intracortical microstimulation (ICMS) in the hand representation of S1. We found that ICMS of S1 activated some M1 neurons at short, fixed latencies consistent with monosynaptic activation.

Preserved neural dynamics across animals performing similar behaviour.

Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual.

From monkeys to humans: observation-basedEMGbrain-computer interface decoders for humans with paralysis.

. Intracortical brain-computer interfaces (iBCIs) aim to enable individuals with paralysis to control the movement of virtual limbs and robotic arms. Because patients' paralysis prevents training a direct neural activity to limb movement decoder, most iBCIs rely on 'observation-based' decoding in which the patient watches a moving cursor while mentally envisioning making the movement.

Using adversarial networks to extend brain computer interface decoding accuracy over time.

Existing intracortical brain computer interfaces (iBCIs) transform neural activity into control signals capable of restoring movement to persons with paralysis. However, the accuracy of the 'decoder' at the heart of the iBCI typically degrades over time due to turnover of recorded neurons. To compensate, decoders can be recalibrated, but this requires the user to spend extra time and effort to provide the necessary data, then learn the new dynamics.