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Light activation of neurons is a growing field with applications ranging from basic investigation of neuronal systems to the development of new therapeutic methods such as artificial retina. Many recent studies currently explore novel methods for optical stimulation with temporal and spatial precision. Novel materials in particular provide an opportunity to enhance contemporary approaches. Here we review recent advances towards light directed interfaces for neuronal stimulation, focusing on state-of-the-art nanoengineered devices. In particular, we highlight challenges and prospects towards improved retinal prostheses.

Reciprocal inhibition (RI) between leg muscles is crucial for smooth movement. Pedaling is a rhythmic movement that can increase RI in healthy individuals. Transcutaneous spinal cord stimulation (tSCS) stimulates spinal neural circuits by targeting the afferent fibers. Pedaling with simultaneous tSCS may modulate the plasticity of the spinal neural circuit and alter neural activity based on movement and muscle engagement. This study investigated the RI changes after pedaling and tSCS and determined the phase of pedaling in which tSCS should be applied for optimal RI modulation in healthy individuals. Eleven subjects underwent three interventions: pedaling combined with tSCS during the early phase of lower extension (phase 1), pedaling combined with tSCS during the late phase of lower flexion (phase 4) of the pedaling cycle, and pedaling combined with sham tSCS. The RI from the tibialis anterior to the soleus muscle was assessed before, immediately after, 15 min, and 30 min after the intervention. RI increased immediately after phase 4 and pedaling combined with sham tSCS, whereas no changes were observed after phase 1. These results demonstrate that tSCS modulates RI changes induced by pedaling in a stimulus phase-dependent manner in healthy individuals. However, the mechanism involved in this intervention needs to be explored to achieve higher efficacy.

Using functional MRI in a large multisite sample of more that 1,000 patients, four distinct neurophysiological biotypes of depression are defined. These biotypes are used to develop diagnostic classifiers that distinguish patients with depression from controls in separate multisite validation and replication cohorts, and can predict patient responsiveness to therapy. Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample ( n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes ('biotypes') defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82–93%) sensitivity and specificity for depression subtypes in multisite validation ( n = 711) and out-of-sample replication ( n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy ( n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.

This work proposes and computationally investigate the use of magnetic neural stimulation as an alternative to electrical stimulation to achieve selective activation of rat sciatic nerve. In particular, they assess the effectiveness of an array of small coils to obtain selective neural stimulation, as compared to a single coil. Specifically, an array of four mm-sized coils is used to stimulate rat sciatic nerve, targeting the regions of fascicles that are associated with different muscles of the leg. To evaluate the selectivity of activation, a three-dimensional heterogeneous multi-resolution nerve model is implemented using the impedance method for the computation of the magnetic and electric fields in the nerve. The performance metric ‘selectivity index’ is defined that measures the recruitment of the targeted region compared to other non-targeted regions of the nerve. The selectivity index takes values between −1 (least selective) and 1 (most selective). For each targeted region, a selectivity index of 0.75 or better is predicted for the proposed array configuration. The results suggest that an array of coils can provide superior spatial control of the electric field induced in the neural tissue compared to traditional extraneural electrode arrays, thus opening the possibility to applications where selective neurostimulation is of interest.

Brief-pulse stimulation at 50 Hz has been shown to terminate afterdischarges observed in epilepsy patients. However, the optimal pulse stimulation parameters for terminating cortical electrical stimulation-induced afterdischarges remain unclear. In the present study, we examined the effects of different brief-pulse stimulation frequencies（5, 50 and 100 Hz） on cortical electrical stimulation-induced afterdischarges in 10 patients with refractory epilepsy. Results demonstrated that brief-pulse stimulation could terminate cortical electrical stimulation-induced afterdischarges in refractory epilepsy patients. In conclusion,（1） a brief-pulse stimulation was more effective when the afterdischarge did not extend to the surrounding brain area.（2） A higher brief-pulse stimulation frequency（especially 100 Hz） was more likely to terminate an afterdischarge.（3） A low current intensity of brief-pulse stimulation was more likely to terminate an afterdischarge.

We present Augur, a method to prioritize the cell types most responsive to biological perturbations in single-cell data. Augur employs a machine-learning framework to quantify the separability of perturbed and unperturbed cells within a high-dimensional space. We validate our method on single-cell RNA sequencing, chromatin accessibility and imaging transcriptomics datasets, and show that Augur outperforms existing methods based on differential gene expression. Augur identified the neural circuits restoring locomotion in mice following spinal cord neurostimulation. The cell types affected by biological perturbations in complex tissues are uncovered by single-cell analysis.

Epidural electrical stimulation (EES) of the spinal cord restores locomotion in animal models of spinal cord injury but is less effective in humans. Here we hypothesized that this interspecies discrepancy is due to interference between EES and proprioceptive information in humans. Computational simulations and preclinical and clinical experiments reveal that EES blocks a significant amount of proprioceptive input in humans, but not in rats. This transient deafferentation prevents modulation of reciprocal inhibitory networks involved in locomotion and reduces or abolishes the conscious perception of leg position. Consequently, continuous EES can only facilitate locomotion within a narrow range of stimulation parameters and is unable to provide meaningful locomotor improvements in humans without rehabilitation. Simulations showed that burst stimulation and spatiotemporal stimulation profiles mitigate the cancellation of proprioceptive information, enabling robust control over motor neuron activity. This demonstrates the importance of stimulation protocols that preserve proprioceptive information to facilitate walking with EES.

Bioelectronics for modulating the nervous system have shown promise in treating neurological diseases 1 – 3 . However, their fixed dimensions cannot accommodate rapid tissue growth 4 , 5 and may impair development 6 . For infants, children and adolescents, once implanted devices are outgrown, additional surgeries are often needed for device replacement, leading to repeated interventions and complications 6 – 8 . Here, we address this limitation with morphing electronics, which adapt to in vivo nerve tissue growth with minimal mechanical constraint. We design and fabricate multilayered morphing electronics, consisting of viscoplastic electrodes and a strain sensor that eliminate the stress at the interface between the electronics and growing tissue. The ability of morphing electronics to self-heal during implantation surgery allows a reconfigurable and seamless neural interface. During the fastest growth period in rats, morphing electronics caused minimal damage to the rat nerve, which grows 2.4-fold in diameter, and allowed chronic electrical stimulation and monitoring for 2 months without disruption of functional behavior. Morphing electronics offers a path toward growth-adaptive pediatric electronic medicine. Viscoplastic electronic devices adapt as nerves enlarge in growing animals.

Spinal sensorimotor networks that are functionally disconnected from the brain because of spinal cord injury (SCI) can be facilitated via epidural electrical stimulation (EES) to restore robust, coordinated motor activity in humans with paralysis 1 – 3 . Previously, we reported a clinical case of complete sensorimotor paralysis of the lower extremities in which EES restored the ability to stand and the ability to control step-like activity while side-lying or suspended vertically in a body-weight support system (BWS) 4 . Since then, dynamic task-specific training in the presence of EES, termed multimodal rehabilitation (MMR), was performed for 43 weeks and resulted in bilateral stepping on a treadmill, independent from trainer assistance or BWS. Additionally, MMR enabled independent stepping over ground while using a front-wheeled walker with trainer assistance at the hips to maintain balance. Furthermore, MMR engaged sensorimotor networks to achieve dynamic performance of standing and stepping. To our knowledge, this is the first report of independent stepping enabled by task-specific training in the presence of EES by a human with complete loss of lower extremity sensorimotor function due to SCI. In a human subject with chronic paraplegia, a combination of epidural electrical stimulation and long-term rehabilitative training have culminated in the first report of unassisted, voluntary independent stepping in a paralyzed individual.