Speech decoding using cortical and subcortical electrophysiological signals.

Introduction: Language impairments often result from severe neurological disorders, driving the development of neural prosthetics utilizing electrophysiological signals to restore comprehensible language. Previous decoding efforts primarily focused on signals from the cerebral cortex, neglecting subcortical brain structures' potential contributions to speech decoding in brain-computer interfaces. Methods: In this study, stereotactic electroencephalography (sEEG) was employed to investigate subcortical structures' role in speech decoding. Two native Mandarin Chinese speakers, undergoing sEEG implantation for epilepsy treatment, participated. Participants read Chinese text, with 1-30, 30-70, and 70-150 Hz frequency band powers of sEEG signals extracted as key features. A deep learning model based on long short-term memory assessed the contribution of different brain structures to speech decoding, predicting consonant articulatory place, manner, and tone within single syllable. Results: Cortical signals excelled in articulatory place prediction (86.5% accuracy), while cortical and subcortical signals performed similarly for articulatory manner (51.5% vs. 51.7% accuracy). Subcortical signals provided superior tone prediction (58.3% accuracy). The superior temporal gyrus was consistently relevant in speech decoding for consonants and tone. Combining cortical and subcortical inputs yielded the highest prediction accuracy, especially for tone. Discussion: This study underscores the essential roles of both cortical and subcortical structures in different aspects of speech decoding.

Reducing the incidence of persistent headache attributed to retrosigmoid craniotomy: the role of 3D computed tomography venography image-guided technique and bone defects minimization.

OBJECTIVE: The objective of this paper was to assess the risk factors for persistent headache attributed to retrosigmoid craniotomy. Furthermore, we evaluated the role of the 3D computed tomography venography(CTV) image-guided technique in reducing the incidence of persistent headache. METHOD: The study encompassed patients with trigeminal neuralgia who underwent microvascular decompression. Patients were categorized into two groups based on the use of 3D CTV in surgical planning. Factors related to craniotomy and postoperative complications were analyzed between the two groups. Binary logistic regression analysis was conducted to identify risk factors for persistent headache attributed to craniotomy. RESULT: The inclusion criteria yielded 48 patients who underwent craniotomy with 3D CTV image guidance (the image-guided group) and 69 patients who did not use this technique (the control group). The image-guided group experienced significantly shorter craniotomy durations (27.9 ± 4.7 vs. 37.5 ± 8.0 min; p < 0.001), smaller craniotomy areas (472.7 ± 56.7 vs. 617.4 ± 89.7 mm2; p < 0.001), and reduced bone defects (141.8 ± 33.5 vs. 233.2 ± 71.1 mm2; p < 0.001). Bone defect (OR: 1.012; 95% CI: 1.005-1.018; p < 0.001) was found to be significantly associated with persistent headache in the multivariate analysis. CONCLUSIONS: Bone defects constitute an independent risk factor for persistent headache attributed to retrosigmoid craniotomy. The 3D CTV image-guided technique effectively reduces the size of bone defects, thereby leading to a reduced incidence of persistent headache postoperatively.

Reduced-Reference Learning for Target Localization in Deep Brain Stimulation.

This work proposes a supervised machine learning method for target localization in deep brain stimulation (DBS). DBS is a recognized treatment for essential tremor. The effects of DBS significantly depend on the precise implantation of electrodes. Recent research on diffusion tensor imaging shows that the optimal target for essential tremor is related to the dentato-rubro-thalamic tract (DRTT), thus DRTT targeting has become a promising direction. The tractography-based targeting is more accurate than conventional ones, but still too complicated for clinical scenarios, where only structural magnetic resonance imaging (sMRI) data is available. In order to improve efficiency and utility, we consider target localization as a non-linear regression problem in a reduced-reference learning framework, and solve it with convolutional neural networks (CNNs). The proposed method is an efficient two-step framework, and consists of two image-based networks: one for classification and the other for localization. We model the basic workflow as an image retrieval process and define relevant performance metrics. Using DRTT as pseudo groundtruths, we show that individualized tractography-based optimal targets can be inferred from sMRI data with high accuracy. For two datasets of 280x220/272x227 (0.7/0.8 mm slice thickness) sMRI input, our model achieves an average posterior localization error of 2.3/1.2 mm, and a median of 1.7/1.02 mm. The proposed framework is a novel application of reduced-reference learning, and a first attempt to localize DRTT from sMRI. It significantly outperforms existing methods using 3D-CNN, anatomical and DRTT atlas, and may serve as a new baseline for general target localization problems.

ChatGPT's potential role in non-English-speaking outpatient clinic settings.

Researchers recently utilized ChatGPT as a tool for composing clinic letters, highlighting its ability to generate accurate and empathetic communications. Here we demonstrated the potential application of ChatGPT as a medical assistant in Mandarin Chinese-speaking outpatient clinics, aiming to improve patient satisfaction in high-patient volume settings. ChatGPT achieved an average score of 72.4% in the Chinese Medical Licensing Examination's Clinical Knowledge section, ranking within the top 20th percentile. It also demonstrated its potential for clinical communication in non-English speaking environments. Our study suggests that ChatGPT could serve as an interface between physicians and patients in Chinese-speaking outpatient settings, possibly extending to other languages. However, further optimization is required, including training on medical-specific datasets, rigorous testing, privacy compliance, integration with existing systems, user-friendly interfaces, and the development of guidelines for medical professionals. Controlled clinical trials and regulatory approval are necessary before widespread implementation. As chatbots' integration into medical practice becomes more feasible, rigorous early investigations and pilot studies can help mitigate potential risks.

Individualized targeting is warranted in subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression: A tractography analysis.

Subcallosal cingulate gyrus (SCG) is a target of deep brain stimulation (DBS) for treatment-resistant depression. However, previous randomized controlled trials report that approximately 42% of patients are responders to this therapy of last resort, and suboptimal targeting of SCG is a potential underlying factor to this unsatisfactory efficacy. Tractography has been proposed as a supplementary method to enhance targeting strategy. We performed a connectivity-based segmentation in the SCG region via probabilistic tractography in 100 healthy volunteers from the Human Connectome Project. The SCG voxels with maximum connectivity to brain regions implicated in depression, including Brodmann Area 10 (BA10), cingulate cortex, thalamus, and nucleus accumbens were identified, and the conjunctions were deemed as tractography-based targets. We then performed deterministic tractography using these targets in additional 100 volunteers to calculate streamline counts compassing to relevant brain regions and fibers. We also evaluated the intra- and inter-subject variance using test-retest dataset. Two tractography-based targets were identified. Tractography-based target-1 had the highest streamline counts to right BA10 and bilateral cingulate cortex, while tractography-based target-2 had the highest streamline counts to bilateral nucleus accumbens and uncinate fasciculus. The mean linear distance from individual tractography-based target to anatomy-based target was 3.2 ± 1.8 mm and 2.5 ± 1.4 mm in left and right hemispheres. The mean ± SD of targets between intra- and inter-subjects were 2.2 ± 1.2 and 2.9 ± 1.4 in left hemisphere, and 2.3 ± 1.4 and 3.1 ± 1.7 in right hemisphere, respectively. Individual heterogeneity as well as inherent variability from diffusion imaging should be taken into account during SCG-DBS target planning procedure.

Challenges and future trends in wearable closed-loop neuromodulation to efficiently treat methamphetamine addiction.

Achieving abstinence from drugs is a long journey and can be particularly challenging in the case of methamphetamine, which has a higher relapse rate than other drugs. Therefore, real-time monitoring of patients' physiological conditions before and when cravings arise to reduce the chance of relapse might help to improve clinical outcomes. Conventional treatments, such as behavior therapy and peer support, often cannot provide timely intervention, reducing the efficiency of these therapies. To more effectively treat methamphetamine addiction in real-time, we propose an intelligent closed-loop transcranial magnetic stimulation (TMS) neuromodulation system based on multimodal electroencephalogram-functional near-infrared spectroscopy (EEG-fNIRS) measurements. This review summarizes the essential modules required for a wearable system to treat addiction efficiently. First, the advantages of neuroimaging over conventional techniques such as analysis of sweat, saliva, or urine for addiction detection are discussed. The knowledge to implement wearable, compact, and user-friendly closed-loop systems with EEG and fNIRS are reviewed. The features of EEG and fNIRS signals in patients with methamphetamine use disorder are summarized. EEG biomarkers are categorized into frequency and time domain and topography-related parameters, whereas for fNIRS, hemoglobin concentration variation and functional connectivity of cortices are described. Following this, the applications of two commonly used neuromodulation technologies, transcranial direct current stimulation and TMS, in patients with methamphetamine use disorder are introduced. The challenges of implementing intelligent closed-loop TMS modulation based on multimodal EEG-fNIRS are summarized, followed by a discussion of potential research directions and the promising future of this approach, including potential applications to other substance use disorders.

Deep Brain Stimulation for Advanced Parkinson Disease in Developing Countries: A Cost-Effectiveness Study From China.

BACKGROUND: The cost-effectiveness of deep brain stimulation (DBS) is more favorable than best medical treatment (BMT) for advanced Parkinson disease (PD) in developed countries. However, it remains unclear in developing countries, where the cost of DBS may not be reimbursed by health care system. OBJECTIVE: To model and evaluate the long-term cost-effectiveness of DBS for advanced PD in China from a patient payer perspective. METHODS: We developed a Markov model representing the clinical progress of PD to predict the disease progression and related medical costs in a 15-year time horizon. The incremental cost-effectiveness ratio (ICER) and net benefit were used to evaluate the cost-effectiveness of DBS vs BMT. RESULTS: DBS treatment led to discounted total costs of ¥370 768 ($56 515.20) (95% CI, ¥369 621.53-371 914.88), compared with ¥48 808 ($7439.68) (95% CI, ¥48 502.63-49 114.21) for BMT, with an additional 1.51 quality-adjusted life years gained, resulting in an ICER of ¥213 544 ($32 549.96)/quality-adjusted life years (95% CI, ¥208 177.35-218 910.10). Sensitivity analysis showed that DBS-related cost has the most substantial impact on ICER. Nation-wide net benefit of BMT and DBS were ¥33 819 ($5154.94) (95% CI, ¥30 211.24-37 426) and ¥30 361 ($4627.85) (95% CI, ¥25 587.03-39 433.66), respectively. Patient demographic analysis showed that more favorable DBS cost-effectiveness was associated with younger age and less severe disease stage. CONCLUSION: DBS is cost-effective for patients with advanced PD over a 15-year time horizon in China. However, compared with developed countries, DBS remains a substantial economic burden for patients when no reimbursement is provided. Our findings may help inform cost-effectiveness-based decision making for clinical care of PD in developing countries.

Traumatic Brain Injury, Bulging Eyeball, and Skin Lumps.

A 43-year-old man was admitted to the emergency department for motor vehicle collision. First clinical impression was traumatic injury of the right eye with bare light perception. A physical examination revealed multiple nodular skin lesions on the head and neck. Head magnetic resonance imaging and computed tomography scans showed intracerebral hemorrhage, trans-orbital brain herniation, and right sphenoid wing dysplasia. A diagnosis of neurofibromatosis type 1 was made. Sphenoid wing dysplasia (also known as bare orbit sign) in neurofibromatosis type 1 was a contributing factor to the trans-orbital herniation, but also helped reduce intracranial pressure after traumatic brain injury in this rare case. Mannitol was administered, and no neurosurgical intervention was needed for traumatic brain injury. Canthorrhaphy of the right eye was performed to preserve patient's right eyeball. At 1-month follow-up, patient's right eyeball was preserved, and vision improved as well.

White Matter Tracts Associated With Deep Brain Stimulation Targets in Major Depressive Disorder: A Systematic Review.

Background: Deep brain stimulation (DBS) has been proposed as a last-resort treatment for major depressive disorder (MDD) and has shown potential antidepressant effects in multiple clinical trials. However, the clinical effects of DBS for MDD are inconsistent and suboptimal, with 30-70% responder rates. The currently used DBS targets for MDD are not individualized, which may account for suboptimal effect. Objective: We aim to review and summarize currently used DBS targets for MDD and relevant diffusion tensor imaging (DTI) studies. Methods: A literature search of the currently used DBS targets for MDD, including clinical trials, case reports and anatomy, was performed. We also performed a literature search on DTI studies in MDD. Results: A total of 95 studies are eligible for our review, including 51 DBS studies, and 44 DTI studies. There are 7 brain structures targeted for MDD DBS, and 9 white matter tracts with microstructural abnormalities reported in MDD. These DBS targets modulate different brain regions implicated in distinguished dysfunctional brain circuits, consistent with DTI findings in MDD. Conclusions: In this review, we propose a taxonomy of DBS targets for MDD. These results imply that clinical characteristics and white matter tracts abnormalities may serve as valuable supplements in future personalized DBS for MDD.

The Accuracy of Imaging Guided Targeting with Microelectrode Recoding in Subthalamic Nucleus for Parkinson's Disease: A Single-Center Experience.

BACKGROUND: Accurate electrode targeting was essential for the efficacy of deep brain stimulation (DBS). There is ongoing debate about the necessary of microelectrode recording (MER) in subthalamic nucleus (STN)-DBS surgery for accurate targeting. OBJECTIVE: This study aimed to analyze the accuracy of imaging-guided awake DBS with MER in STN for Parkinson's disease in a single center. METHODS: The authors performed a retrospective analysis of 161 Parkinson's disease patients undergoing STN-DBS at our center from March 2013 to June 2021. The implantation was performed by preoperative magnetic resonance imaging (MRI)-based direct targeting with intraoperative MER and macrostimulation testing. 285 electrode tracks with preoperative and postoperative coordinates were included to calculate the placement error in STN targeting. RESULTS: 85.9% of electrodes guided by preoperative MRI were implanted without intraoperative adjustment. 31 (10.2%) and 12 (3.9%) electrodes underwent intraoperative adjustment due to MER and intraoperative testing, respectively. We found 86.2% (245/285) of electrodes with trajectory error ≤2 mm. The MER physiological signals length < 4 mm and ≥4 mm group showed trajectory error > 2 mm in 38.0% and 8.8% of electrodes, respectively. Compared to non-adjustment electrodes, the final positioning of MER-adjusted electrodes deviated from the center of STN. CONCLUSION: The preoperative MRI guided STN targeting results in approximately 14% cases that require electrode repositioning. MER physiological signals length < 4 mm at first penetration implied deviation off planned target. MER combined with intraoperative awake testing served to rescue such deviation based on MRI alone.

Epilepsy surgery for low-grade epilepsy-associated neuroepithelial tumor of temporal lobe: a single-institution experience of 61 patients.

BACKGROUND: Low-grade epilepsy-associated neuroepithelial tumor (LEAT) is highly responsive to surgery in general. The appropriate surgical strategy remains controversial in temporal LEAT. The aim of this study is to analyze the surgical seizure outcome of temporal LEAT, focusing on the aspects of surgical strategy. METHODS: Sixty-one patients from a single epilepsy center with temporal LEAT underwent surgery. The surgical strategy was according to the multidisciplinary presurgical evaluation. Electrocorticogram (ECoG)-assisted resection was utilized. Surgical extent including lesionectomy and extended resection was described in detail. Seizure outcome was classified as satisfactory (Engel class I) and unsatisfactory (Engel classes II-IV). RESULTS: After a median follow-up of 36.0 (30.0) months, 83.6% of patients achieved satisfactory outcome, including 72.1% with Engel class Ia. There was 39.3% (24/61) of patients with antiepileptic drug (AED) withdrawal. Use of ECoG (χ2 = 0.000, P > 0.1), preresection spike (χ2 = 0.000, P = 0.763), or spike residue (P = 0.545) was not correlated with the seizure outcome. For lateral temporal LEAT, outcome from lesionectomy was comparable to extended resection (χ2 = 0.499, P > 0.1). For mesial temporal LEAT, 94.7% (18/19) of patients who underwent additional hippocampectomy were satisfactory, whereas only 25% (1/4) of patients who underwent lesionectomy were satisfactory (P = 0.009). CONCLUSION: Surgical treatment was highly effective for temporal LEAT. ECoG may not influence the seizure outcome. For lateral temporal LEAT, lesionectomy with or without cortectomy was sufficient in most patients. For mesial temporal LEAT, extended resection was recommended.

Local accumbens in vivo imaging during deep brain stimulation reveals a strategy-dependent amelioration of hedonic feeding.

Impulsive overeating is a common, disabling feature of eating disorders. Both continuous deep brain stimulation (DBS) and responsive DBS, which limits current delivery to pathological brain states, have emerged as potential therapies. We used in vivo fiber photometry in wild-type, Drd1-cre, and A2a-cre mice to 1) assay subtype-specific medium spiny neuron (MSN) activity of the nucleus accumbens (NAc) during hedonic feeding of high-fat food, and 2) examine DBS strategy-specific effects on NAc activity. D1, but not D2, NAc GCaMP activity increased immediately prior to high-fat food approach. Responsive DBS triggered a GCaMP surge throughout the stimulation period and durably reduced high-fat intake. However, with continuous DBS, this surge decayed, and high-fat intake reemerged. Our results argue for a stimulation strategy-dependent modulation of D1 MSNs with a more sustained decrease in consumption with responsive DBS. This study illustrates the important role in vivo imaging can play in understanding effects of such novel therapies.

Power efficient refined seizure prediction algorithm based on an enhanced benchmarking.

Deep learning techniques have led to significant advancements in seizure prediction research. However, corresponding used benchmarks are not uniform in published results. Moreover, inappropriate training and evaluation processes used in various work create overfitted models, making prediction performance fluctuate or unreliable. In this study, we analyzed the various data preparation methods, dataset partition methods in related works, and explained the corresponding impacts to the prediction algorithms. Then we applied a robust processing procedure that considers the appropriate sampling parameters and the leave-one-out cross-validation method to avoid possible overfitting and provide prerequisites for ease benchmarking. Moreover, a deep learning architecture takes advantage of a one-dimension convolutional neural network and a bi-directional long short-term memory network is proposed for seizure prediction. The architecture achieves 77.6% accuracy, 82.7% sensitivity, and 72.4% specificity, and it outperforms the indicators of other prior-art works. The proposed model is also hardware friendly; it has 6.274 k parameters and requires only 12.825 M floating-point operations, which is advantageous for memory and power constrained device implementations.

On-Site Biolayer Interferometry-Based Biosensing of Carbamazepine in Whole Blood of Epileptic Patients.

On-site monitoring of carbamazepine (CBZ) that allows rapid, sensitive, automatic, and high-throughput detection directly from whole blood is of urgent demand in current clinical practice for precision medicine. Herein, we developed two types (being indirect vs. direct) of fiber-optic biolayer interferometry (FO-BLI) biosensors for on-site CBZ monitoring. The indirect FO-BLI biosensor preincubated samples with monoclonal antibodies towards CBZ (MA-CBZ), and the mixture competes with immobilized CBZ to bind towards MA-CBZ. The direct FO-BLI biosensor used sample CBZ and CBZ-horseradish peroxidase (CBZ-HRP) conjugate to directly compete for binding with immobilized MA-CBZ, followed by a metal precipitate 3,3'-diaminobenzidine to amplify the signals. Indirect FO-BLI detected CBZ within its therapeutic range and was regenerated up to 12 times with negligible baseline drift, but reported results in 25 min. However, Direct FO-BLI achieved CBZ detection in approximately 7.5 min, down to as low as 10 ng/mL, with good accuracy, specificity and negligible matric interference using a high-salt buffer. Validation of Direct FO-BLI using six paired sera and whole blood from epileptic patients showed excellent agreement with ultra-performance liquid chromatography. Being automated and able to achieve high throughput, Direct FO-BLI proved itself to be more effective for integration into the clinic by delivering CBZ values from whole blood within minutes.

A connectomic analysis of deep brain stimulation for treatment-resistant depression.

OBJECTIVE: Deep brain stimulation (DBS) has been used as a treatment of last resort for treatment-resistant depression (TRD) for more than a decade. Many DBS targets have been proposed and tested clinically, but the underlying circuit mechanisms remain unclear. Uncovering white matter tracts (WMT) activated by DBS targets may provide crucial information about the circuit substrates mediating DBS efficacy in ameliorating TRD. METHODS: We performed probabilistic tractography using diffusion magnetic resonance imaging datas from 100 healthy volunteers in Human Connectome Project datasets to analyze the structural connectivity patterns of stimulation targeting currently-used DBS target for TRD. We generated mean and binary fiber distribution maps and calculated the numbers of WMT streamlines in the dataset. RESULTS: Probabilistic tracking results revealed that activation of distinct DBS targets demonstrated modulation of overlapping but considerably distinct pathways. DBS targets were categorized into 4 groups: Cortical, Striatal, Thalamic, and Medial Forebrain Bundle according to their main modulated WMT and brain areas. Our data also revealed that Brodmann area 10 and amygdala are hub structures that are associated with all DBS targets. CONCLUSIONS: Our results together suggest that the distinct mechanism of DBS targets implies individualized target selection and formulation in the future of DBS treatment for TRD. The modulation of Brodmann area 10 and amygdala may be critical for the efficacy of DBS-mediated treatment of TRD.

Input-specific modulation of murine nucleus accumbens differentially regulates hedonic feeding.

Hedonic feeding is driven by the "pleasure" derived from consuming palatable food and occurs in the absence of metabolic need. It plays a critical role in the excessive feeding that underlies obesity. Compared to other pathological motivated behaviors, little is known about the neural circuit mechanisms mediating excessive hedonic feeding. Here, we show that modulation of prefrontal cortex (PFC) and anterior paraventricular thalamus (aPVT) excitatory inputs to the nucleus accumbens (NAc), a key node of reward circuitry, has opposing effects on high fat intake in mice. Prolonged high fat intake leads to input- and cell type-specific changes in synaptic strength. Modifying synaptic strength via plasticity protocols, either in an input-specific optogenetic or non-specific electrical manner, causes sustained changes in high fat intake. These results demonstrate that input-specific NAc circuit adaptations occur with repeated exposure to a potent natural reward and suggest that neuromodulatory interventions may be therapeutically useful for individuals with pathologic hedonic feeding.

Intradural osteomas: Report of two cases.

BACKGROUND: Intradural osteoma is very rarely located in the subdural or subarachnoid space. Unfortunately, intradural osteoma lacks specificity in clinical manifestations and imaging features and there is currently no consensus on its diagnosis method or treatment strategy. Moreover, the pathogenesis of osteoma without skull structure involvement remains unclear. CASE SUMMARY: We describe two cases of intradural osteomas located in the subdural and subarachnoid spaces, respectively. The first case involved a 47-year-old woman who presented with a 3-year history of intermittent headache and dizziness. Intraoperatively, a bony hard mass was found in the left frontal area, attached to the inner surface of the dura mater and compressing the underlying arachnoid membrane and brain. The second case involved a 56-year-old woman who had an intracranial high-density lesion isolated under the right greater wing of the sphenoid. Intraoperatively, an arachnoid-covered bony tumor was found in the sylvian fissure. The pathological diagnosis for both patients was osteoma. CONCLUSION: Surgery and pathological examination are required for diagnosis of intradural osteomas, and craniotomy is a safe and effective treatment.

Accumbens coordinated reset stimulation in mice exhibits ameliorating aftereffects on binge alcohol drinking.

BACKGROUND: Alcohol use disorder (AUD) affects nearly 5% of the world's adult population. Despite treatment, AUD often manifests with relapse to binge drinking, which has been associated with corticostriatal hypersynchrony involving the nucleus accumbens (NAc). METHODS: A modified "Drinking in the Dark" protocol was used to provoke binge-like alcohol drinking. We implemented Coordinated Reset Stimulation (CRS), a computationally designed, spatio-temporal stimulation algorithm, to desynchronize abnormal neuronal activity via a deep brain stimulation (DBS) electrode in the NAc of mice exhibiting binge-like alcohol drinking. Integral CRS charge injected would be 2.5% of that of conventional high-frequency DBS. RESULTS: NAc CRS delivery during only the initial phase of exposure to alcohol and prior to the exposure (but not during) significantly reduced binge-like drinking without interfering with social behavior or locomotor activity. CONCLUSIONS: NAc CRS ameliorates binge-like alcohol drinking and preliminarily exhibits sustained aftereffects that are suggestive of an unlearning of hypersynchrony.