Neurosurgical focus最新文献

Objective: The long-term goal of this work is to develop a sensorimotor brain-machine interface (BMI) in which intended movements are decoded from the motor cortex and proprioceptive feedback is delivered via intracortical microstimulation of Brodmann's area 3a. A vital step toward this goal is to demonstrate in rhesus macaques a novel surgical approach for the precise and safe implantation of custom-length microelectrode arrays into area 3a at the bottom of the central sulcus.

Methods: Preoperative planning combined high-resolution 7-T MR and CT imaging to generate 3D models of the cortices of 2 subjects. These models were used to fabricate 3D-printed skull replicas and to define a stereotactic trajectory that provided the shortest perpendicular path to the base of the central sulcus, where Brodmann's area 3a resides. Custom variable-length microwire electrode arrays were designed to span this target region. The flexibility of the microwires precluded the standard impact-insertion approach used with stiffer electrodes. Therefore, a custom vacuum-powered microdrive holder that moved with the pulsating brain was developed to maintain electrode orientation and to allow slow, controlled insertion along the planned trajectory. After implantation, the craniotomy was closed, and a skull-mounted recording chamber was secured. Postoperative verification of array placement was performed using CT imaging and neural recordings.

Results: In both animals, imaging revealed that the base of the central sulcus was positioned anterior to its dorsal opening, making a precentral implant trajectory the shortest and most direct path to the bottom of the central sulcus. The integrated imaging and 3D modeling approach enabled accurate stereotactic placement of custom microelectrode arrays using the novel vacuum-assisted microdrive, as confirmed by postoperative CT imaging. Both surgical procedures were completed without complication, and isolatable neuronal spikes were recorded from multiple channels in each subject. In both animals, neural activity was modulated by passive movements of the arm.

Conclusions: Intracortical microelectrode implants for BMI applications have traditionally been limited to short (1.5-mm) electrodes targeting cortical sites exposed on the brain surface. The surgical methodology described here enables safe and accurate implantation of custom-length arrays into deep sulcal targets such as Brodmann's area 3a. By expanding access to previously inaccessible cortical regions, this approach broadens the potential neural information available for future BMI applications.

Objective: The aim of this study was to evaluate the feasibility of using the Layer 7 Cortical Interface, a high-density micro-electrocorticography (μECoG) array, for intraoperative neural recordings and real-time brain-computer interface (BCI) applications, including speech decoding and cursor control.

Methods: Four patients (age range 23-43 years) who underwent awake craniotomy for tumor resection near the eloquent cortex were enrolled. The Layer 7 µECoG device (1024 channels, approximately 1.5-cm2 coverage) was placed on the motor cortex following standard cortical mapping. Intraoperative tasks included a joystick-controlled center-out movement paradigm (n = 3) and an auditory-cued speech repetition task (n = 1). Neural data were recorded at 20 kHz, preprocessed, and used to train decoders intraoperatively. A transformer-based model was applied for real-time speech synthesis and a convolutional neural network was trained for speech classification, while a convolutional recurrent neural network was trained to classify 2D cursor direction.

Results: All 4 patients tolerated the procedure without device-related adverse events. The mean electrode impedances across 6 arrays (6144 channels) ranged from 1.21 to 1.99 MΩ, with 954-990 channels per array retained for analysis. In the speech task, a 4-word classification model achieved 77.5% accuracy, and a real-time synthesis model was able to distinguish speech and silence during approximately 20 minutes of data recording in the operating room. In the motor task, a 4-direction classification model achieved 78%-84% accuracy. Recordings remained stable during tumor resection.

Conclusions: The Layer 7 Cortical Interface device enabled high-resolution nonpenetrating cortical recordings that supported real-time speech classification and cursor control within the limited timeframe of an intraoperative session. These findings highlight the potential clinical applications of high-density µECoG for functional mapping, diagnostic assessment, and future chronic BCI systems for patients with motor and communication impairments.

Acute and chronic CNS pathologies that result in tissue loss remain among the most intractable problems in neurosurgery, with current treatments focused on stabilization and neuroprotection rather than structural repair. Neural interfaces such as recording, stimulating, or replacing neural activity have demonstrated value in restoring function via prostheses and brain-computer interfaces, yet these approaches are constrained by electrode design, bandwidth, and limited biological integration. Engineered neuroglial organoids offer a complementary, biologically based interface strategy. Derived from pluripotent stem cells, neuroglial organoids arrive as 3D constructs containing neurons and glia in intrinsic architecture, capable of vascularization, synaptic connectivity, and integration with host tissue. Building on dissociated stem cell suspensions, organoids act not only as reservoirs of cells but also as living neural interfaces, receiving inputs from host circuits and generating functional outputs. Preclinical studies have demonstrated that transplanted organoids can couple to host sensory pathways, respond to stimulation, and support recovery of motor and cognitive functions. Moreover, emerging work coupling organoid grafts to brain-computer interfaces highlights the potential for closed-loop biological electronic systems, in which engineered devices provide precise recording and stimulation while organoids contribute adaptive, active biological circuits. This combination allows real-time bidirectional communication, allowing the graft to be both monitored and adapted to structurally and functionally integrate into host tissue. In this review, the authors examine neuroglial organoid transplantation through the lens of neural interfacing. They outline lessons from non-CNS organoid transplantation, summarize neurotrauma studies where grafts engage host circuits, and highlight opportunities to integrate organoids with electrodes, stimulation paradigms, and computational models. They also discuss challenges, namely vascularization, immune tolerance, surgical delivery, and manufacturing standards, that parallel those in neural device translation. For neurosurgeons, the appeal of neuroglial organoids lies not only in tissue replacement but in establishing a new class of biological neural interfaces, extending the reach of restorative neurosurgery. By merging living constructs with engineered devices, organoid-based strategies may enable hybrid restorative systems that restore function after neurological injury and disease.

Objective: Stroke is a leading cause of long-term disability, with conventional rehabilitation often failing to achieve substantial motor recovery, particularly in patients with severe paresis or in chronic stages. Brain-computer interfaces (BCIs) offer a novel rehabilitation approach by translating neural signals into real-time external feedback. The authors performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the efficacy and safety of noninvasive BCIs for poststroke motor rehabilitation.

Methods: A systematic literature review was performed based on the PRISMA guidelines using 3 databases. Eligible RCTs enrolled stroke patients receiving noninvasive BCI-assisted motor rehabilitation compared with conventional therapies. The primary outcome was the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) improvement. Secondary outcomes included the Action Research Arm Test (ARAT), Motor Activity Log (MAL), Modified Barthel Index (MBI), and Modified Ashworth Scale (MAS). Effect sizes were pooled using random-effects models and expressed as mean differences (MDs), standardized MDs (SMDs), or odds ratios, each with corresponding 95% confidence intervals (CIs).

Results: Thirty-two RCTs comprising 1187 patients were included with no heterogeneity or significant imbalances in baseline characteristics across groups. A BCI was significantly superior in FMA-UE score improvement compared with controls (MD 3.85, 95% CI 2.84-4.86; p < 0.01), with benefits sustained at follow-up. Within-group analyses revealed greater improvement in the BCI arm from follow-up to baseline (MD 8.18, 95% CI 5.77-10.60; p < 0.01). A BCI was also associated with higher ARAT (MD 7.18, 95% CI 2.4-12.0; p < 0.01) and MAL (SMD 0.59, 95% CI 0.34-0.85; p < 0.01) scores, although between-group differences for these endpoints were not statistically significant. For the MBI, a subgroup analysis did not demonstrate significant differences, but a sensitivity analysis revealed a significant improvement in the BCI group (p = 0.042). There were no significant differences in the within- and between-group analyses of the MAS. A subgroup analysis suggested a synergistic benefit with the BCI combined with neuromuscular electrical stimulation. Adverse events were infrequent and generally mild; 2 withdrawals in the BCI group were reported due to seizure and electrode allergy. Notably, all heterogeneity was successfully resolved through sensitivity analyses, supporting the robustness of the findings.

Conclusions: Noninvasive BCI-assisted rehabilitation is a safe and effective adjunct to conventional therapy, enhancing motor recovery after stroke. While all included RCTs evaluated noninvasive systems, the potential value and efficacy of invasive and minimally invasive BCIs may require further consideration.