Search Results (84)

Reward processing is a vital function for health and survival and is impaired in various psychiatric and neurological disorders. Using a monetary gambling task, the current study aims to elucidate neural substrates in the reward network underlying the evaluation of win versus loss outcomes and their association with behavioral characteristics, such as impulsivity and task performance, and neuropsychological functioning. Functional MRI was recorded in thirty healthy, male community volunteers (mean age = 27.4 years) while they performed a monetary gambling task in which they bet with either 10 or 50 tokens and received feedback on whether they won or lost the bet amount. Results showed that a set of key brain structures in the reward network, including the putamen, caudate nucleus, superior and inferior parietal lobule, angular gyrus, and Rolandic operculum, had greater blood oxygenation level-dependent (BOLD) signals during win relative to loss trials, and the BOLD signals in most of these regions were highly correlated with one another. Furthermore, exploratory bivariate analyses between these reward-related regions and behavioral and neuropsychological domains showed significant correlations with moderate effect sizes, including (i) negative correlations between non-planning impulsivity and activations in the putamen and caudate regions, (ii) positive correlations between risky bets and right putamen activation, (iii) negative correlations between safer bets and right putamen activation, (iv) a negative correlation between short-term memory capacity and right putamen activity, and (v) a negative correlation between poor planning skills and left inferior occipital cortex activation. These findings contribute to our understanding of the neural underpinnings of monetary reward processing and their relationships to aspects of behavior and cognitive function. Future studies may confirm these findings with larger samples of healthy controls and extend these findings by investigating various clinical groups with impaired reward processing. Full article

The aim of this study was to evaluate the efficacy of manual therapy based on neurodynamic techniques and electrophysical modalities in the conservative treatment of cubital tunnel syndrome (CuTS). A total of 128 upper limbs affected by CuTS were initially enrolled in this study, with 82 completing the full treatment protocol. The participants were divided into the following two intervention arms: the first arm (MT) (42 arms) received therapy based on sliding and tensioning neurodynamic techniques, while the second arm (EM) (40 arms) underwent physiotherapy based on electrophysical modalities, specifically low-level laser therapy (LLLT) and ultrasound therapy (US). Chi² and Student’s t-test were used to compare the intervention arms, and no statistically significant differences were found. The evaluated outcomes included nerve conduction testing, ultrasound assessments (measuring cross-sectional area and shear modulus), pain levels, two-point discrimination, thresholds for cutaneous sensory perception, symptom severity, functional ability in specific tasks, and overall post-treatment improvement. Baseline comparisons indicated no statistically significant differences in any measured variables between the intervention groups (p > 0.05). Following treatment, each group exhibited significant improvements in their respective parameters (p < 0.01). Comparisons between groups post-intervention revealed statistically significant differences in nerve conduction results, ultrasound measurements (cross-sectional area and shear modulus), two-point discrimination, and sensory perception thresholds. These parameters improved more in the MT intervention arm. The use of neurodynamic techniques, ultrasound, and low-level laser therapy in the conservative treatment of mild to moderate forms of CuTS has a beneficial therapeutic effect. Full article

Background: Suprascapular neuropathy is a known cause of shoulder pain. Although neurodynamic techniques are widely used to treat peripheral neuropathies, the mechanical behavior of the suprascapular nerve in the shoulder region remains poorly understood. Objectives: This study aimed to analyze the mechanical behavior of the suprascapular nerve during a contralateral cervical glide and an infraspinatus muscle contraction. Methods: The study was conducted in two phases. First, nerve movement was analyzed in 12 cryopreserved cadaveric shoulders using anatomical dissection. Second, suprascapular nerve displacement was assessed in 34 shoulders from 17 healthy volunteers using ultrasound imaging. Results: In cadaveric dissections, the contralateral cervical glide produced a proximal nerve displacement of 1.85 mm at the suprascapular notch. In the ultrasound study, this maneuver resulted in horizontal and vertical displacements of 1.18 mm and 0.39 mm, respectively. In contrast, infraspinatus muscle contraction caused a distal displacement of 3.21 mm in the cadaveric study, and ultrasound imaging showed horizontal and vertical displacements of 1.34 mm and 0.75 mm, respectively. All reported displacements were statistically significant (p < 0.05). Conclusions: The findings of both phases of the study contribute to a better understanding of suprascapular nerve biomechanics and may inform clinical neurodynamic interventions. Full article

Neurodynamics is recognized as a powerful tool for addressing various problems in engineering, control, and intelligent systems. Over the past decade, neurodynamics-based methods and models have been rapidly developed, particularly in emerging areas such as neural computation and multi-agent systems. In this paper, we provide a brief survey of neurodynamics applied to computation and multi-agent systems. Specifically, we highlight key models and approaches related to time-varying computation, as well as cooperative and competitive behaviors in multi-agent systems. Furthermore, we discuss current challenges, potential opportunities, and promising future directions in this evolving field. Full article

Nonlinear optimization with equation constraints has wide applications in intelligent control systems, acoustic signal processing, etc. Thus, effectively tackling the nonlinear optimization problems with equation constraints is of great significance for the advancement of these fields. Current discrete-time neurodynamics predominantly addresses unperturbed optimization scenarios, exhibiting inherent sensitivity to external noise, which limits the practical application of these methods. To address this issue, we propose a discrete-time noise-suppressed neurodynamics (DTNSN) model in this paper. First, the model integrates the static optimization stability of the gradient-based neurodynamics (GND) model with the time-varying tracking capability of the zeroing neurodynamics (ZND) model. Then, an integral feedback term is introduced to suppress external noise disturbances, thereby enhancing the robustness of the model. Additionally, to facilitate implementation on digital hardware, we employ an explicit linear three-step discretization method to obtain the proposed DTNSN model. Finally, the convergence performance, noise suppression capability, and practicality of the model are validated through theoretical analysis, numerical simulations, and acoustic source localization experiments. The model is applicable to the fields of intelligent control systems, acoustic signal processing, and industrial automation, providing new tools for real-time optimization in noisy environments. Full article

The complex, temporally variant singular value decomposition (SVD) problem is proposed and investigated in this paper. Firstly, the original problem is transformed into an equation system. Then, by using the real zeroing neurodynamics (ZN) method, matrix vectorization, Kronecker product, vectorized transpose matrix, and dimensionality reduction technique, a dynamical model, termed the continuous-time SVD (CTSVD) model, is derived and investigated. Furthermore, a new 11-point Zhang et al. discretization (ZeaD) formula with fifth-order precision is proposed and studied. In addition, with the use of the 11-point and other ZeaD formulas, five discrete-time SVD (DTSVD) algorithms are further acquired. Meanwhile, theoretical analyses and numerical experimental results substantiate the correctness and convergence of the proposed CTSVD model and DTSVD algorithms. Full article

Background: The Upper Limb Neural Tension Test (ULNTT) is a common assessment for neurodynamic function, yet the relationship between ULNTT findings and specific spinal biomechanical patterns remains poorly understood, particularly in the context of cervicobrachial neuralgia. This study aimed to investigate the association between ULNTT asymmetry and cervicothoracic spine biomechanics using advanced motion capture analysis. Methods: A longitudinal experimental study was conducted on two groups of asymptomatic participants: one with ULNTT asymmetry > 10° (AS group, n = 12) and another with symmetrical ULNTT (S group, n = 11). Neurodynamic testing and 3D motion capture of spinal kinematics during head lateral bending were performed at baseline. The AS group then underwent manual medicine intervention targeting spinal mobility impairments, followed by post-intervention reassessment. Spine biomechanics data, focusing on the C5-T4 region, were analyzed using the least squares approximation method to derive parameters describing upper thoracic (T1-T4_VERT) and lower cervical (C5-T1_CONC) lateral bending, and their interrelationship (ANGLE_TANG). Results: At baseline, the AS group showed significant differences between sides in neurodynamic parameters and T1-T4_VERT, with limited upper thoracic lateral bending contralateral to the side of the restricted ULNTT. Significant intergroup differences were also observed for these parameters. Following intervention in the AS group, significant improvements were noted in neurodynamic parameters and T1-T4_VERT, with no significant between-side differences post-intervention. Conclusions: These are preliminary results and preliminary conclusions based on the first study on a small group of patients. Given the limitations, this study provides evidence for a relationship between ULNTT asymmetry and upper thoracic spine biomechanics, specifically a contralateral limitation in lateral bending. These findings suggest a functional link between brachial plexus neurodynamics and upper thoracic spine mobility, offering potential insights into the pathophysiology of cervicobrachial conditions and highlighting the potential role of manual therapy in addressing both neurodynamic and biomechanical impairments. The developed motion capture analysis method offers a novel approach to quantify fine spinal motion patterns. Full article

Background/Objectives: Epilepsy is a common neurological disorder that not only severely impacts patients’ health but also imposes a significant burden on families and society. However, its pathogenesis remains unclear. Astrocytes play a crucial role in epileptic seizures and may serve as potential therapeutic targets. Establishing a network model of epileptic seizures based on the astrocyte–neuron cell coupling and the clinical electroencephalographic (EEG) characteristics of epilepsy can facilitate further research on refractory epilepsy and the development of treatment strategies. Methods: This study constructs a neuronal network dynamic model of epileptic seizures based on the Watts–Strogatz small-world network, with a particular emphasis on the biological mechanisms of astrocyte–neuron coupling. The phase-locking value (PLV) is used to quantify the degree of network synchronization and to identify the key nodes or connections influencing synchronous seizures, such that two epilepsy treatment strategies are proposed: seizure suppression through stimulation and surgical resection simulation therapy. The therapeutic effects are evaluated based on the PLV-quantified network synchronization. Results: The results indicate that the desynchronization effect of random noise and sinusoidal wave stimulation is limited, while square wave stimulation is the most effective. Among the four surgical resection strategies, the effectiveness is the highest when resecting nodes exhibiting epileptic discharges. These findings contribute to the development of rational seizure suppression strategies and provide insights into precise epileptic focus localization and personalized treatment approaches. Full article

Understanding human cortical neurodynamics is increasingly important, as highlighted by the European Innovation Council, which prioritises tools for measuring and stimulating brain activity. Unravelling how cytoarchitecture, morphology, and connectivity shape neurodynamics is essential for developing technologies that target specific brain regions. Given the dynamic and non-stationary nature of neural interactions, there is an urgent need for non-linear signal analysis methods, in addition to the linear ones, to track local neurodynamics and differentiate cortical parcels. Here, we explore linear and non-linear methods using data from a public stereotactic intracranial EEG (sEEG) dataset, focusing on the superior temporal gyrus (STG), postcentral gyrus (postCG), and precentral gyrus (preCG) in 55 subjects during resting-state wakefulness. For this study, we used a linear Power Spectral Density (PSD) estimate and three non-linear measures: the Higuchi fractal dimension (HFD), a one-dimensional convolutional neural network (1D-CNN), and a one-shot learning model. The PSD was able to distinguish the regions in α, β, and γ frequency bands. The HFD showed a tendency of a higher value in the preCG than in the postCG, and both were higher in the STG. The 1D-CNN showed promise in identifying cortical parcels, with an 85% accuracy for the training set, although performance in the test phase indicates that further refinement is needed to integrate dynamic neural electrical activity patterns into neural networks for suitable classification. Full article

Objective: To assess the immediate effects of dynamic cupping on median nerve mechanosensitivity, measured by the upper limb neurodynamic test 1 (ULNT1), in healthy participants. Methods: After completing the questionnaire, 60 healthy participants were randomly assigned to two groups: the intervention group (IG; n = 30), which received dynamic cupping therapy, and the control group (CG; n = 30), which received no intervention. In the first assessment (M0), the ULNT1 was conducted on the dominant upper limb. The elbow extension range of motion was measured at the onset of symptoms and at the maximum tolerated point using a smartphone (iPhone 6, iOS 12.4.5, Apple Inc., Cupertino, CA, USA) as a goniometer substitute. Immediately following the intervention or control, both groups were assessed again (M1). Results: There were no significant differences between groups in terms of the range of motion for elbow extension at the onset of symptoms (IG: 23.8 ± 21.4° vs. CG: 24.8 ± 22.5°; p = 0.946) and at the maximum tolerated point of the ULNT1 (IG: 57.0 ± 19.9° vs. CG: 67.0 ± 19.4°; p = 0.236). Conclusions: These findings indicate that dynamic cupping does not appear to affect the mechanosensitivity of the median nerve in healthy participants. These results suggest that dynamic cupping may not be effective for immediate changes in nerve mechanosensitivity in asymptomatic individuals, but further research is needed to explore its effects in symptomatic populations, such as patients with carpal tunnel syndrome or cervical radiculopathy. Full article

Background/Objectives: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated versatility in various applications but faces challenges in specialized domains like neurology. This study evaluates a specialized LLM’s capability and trustworthiness in complex neurological diagnosis, comparing its performance to neurologists in simulated clinical settings. Methods: We deployed GPT-4 Turbo (OpenAI, San Francisco, CA, US) through Neura (Sciense, New York, NY, US), an AI infrastructure with a dual-database architecture integrating “long-term memory” and “short-term memory” components on a curated neurological corpus. Five representative clinical scenarios were presented to 13 neurologists and the AI system. Participants formulated differential diagnoses based on initial presentations, followed by definitive diagnoses after receiving conclusive clinical information. Two senior academic neurologists blindly evaluated all responses, while an independent investigator assessed the verifiability of AI-generated information. Results: AI achieved a significantly higher normalized score (86.17%) compared to neurologists (55.11%, p < 0.001). For differential diagnosis questions, AI scored 85% versus 46.15% for neurologists, and for final diagnosis, 88.24% versus 70.93%. AI obtained 15 maximum scores in its 20 evaluations and responded in under 30 s compared to neurologists’ average of 9 min. All AI-provided references were classified as relevant with no hallucinatory content detected. Conclusions: A specialized LLM demonstrated superior diagnostic performance compared to practicing neurologists across complex clinical challenges. This indicates that appropriately harnessed LLMs with curated knowledge bases can achieve domain-specific relevance in complex clinical disciplines, suggesting potential for AI as a time-efficient asset in clinical practice. Full article

Background/Objective: To assess the effectiveness of therapy based on sliding and tensioning neurodynamic techniques in the conservative treatment of mild and moderate forms of cubital tunnel syndrome (CuTS) compared to sham therapy. Methods: A single-blinded, randomized placebo-controlled trial. The study was conducted at several medical clinics. Individuals diagnosed with CuTS (initially 136 subjects, of whom 91 completed the full protocol) participated in the experiment. In the experimental group (MT), sliding and tensioning neurodynamic techniques were applied, whereas in the control group (ST), a sham therapy was used, involving the performance of neurodynamic techniques in an intermediate position without following the specific neurodynamic sequence for the ulnar nerve. The therapy was administered five times per week over the course of 10 sessions. All participants underwent assessments, including nerve conduction studies, ultrasound imaging (cross-sectional area and shear modulus), pain levels, two-point discrimination sensation, cutaneous sensory perception threshold, symptoms, ability to perform certain activities, and changes in improvement following treatment. Results: A baseline assessment revealed no significant inter-group differences in all examined parameters (p > 0.05). After therapy, there was a statistically significant intra-group improvement in all parameters tested (p < 0.01). In the MT group, the intra-group differences were significant across all parameters tested (p < 0.01). However, in the ST group (sham therapy), only the shear modulus showed statistically significant changes, while the other tested parameters remained unchanged. Conclusions: Neurodynamic techniques demonstrate superior therapeutic effects compared to sham therapy in the treatment of mild to moderate forms of CuTS. Full article

Background: Low back pain (LBP) is a leading cause of disability worldwide, often driven by distinct pain mechanisms: nociceptive, neuropathic, and central sensitization. Accurate classification of these mechanisms is critical for guiding effective, targeted treatments. Methods: A scoping review was conducted following the Joanna Briggs Institute methodology and reported according to PRISMA-ScR guidelines. A comprehensive literature search was performed in MEDLINE, Cochrane CENTRAL, Scopus, PEDro, and Web of Science. Eligible studies included adults with LBP and focused on clinical criteria for classifying pain mechanisms. Data on study methods, population characteristics, and outcomes were extracted and synthesized. Results: Nine studies met the inclusion criteria. Nociceptive pain was characterized by localized symptoms proportional to mechanical triggers, with no neurological signs. Neuropathic pain was associated with burning sensations, dysaesthesia, and a positive neurodynamic straight leg raise (SLR) test. Central sensitization featured widespread pain, hyperalgesia, and disproportionate symptoms. Tools such as painDETECT, DN4, and the Central Sensitisation Inventory (CSI) were validated for neuropathic and central sensitization pain. Central sensitization and neuropathic pain were linked to greater disability and psychological distress compared to nociceptive pain. Conclusions: This review aims to provide a historical perspective on pain mechanism classifications and to explore how previous frameworks have influenced current diagnostic concepts in physiotherapy practice. By synthesizing key clinical criteria used to differentiate between nociceptive, neuropathic, and central sensitization pain, this review proposes a practical framework to improve the accuracy of pain classification in clinical settings. Full article

Background: When performing the Upper Limb Neurodynamic Test 1 (ULNT1), the order of joint movement can be varied to place more stress onto certain nerve segments. However, the mechanisms underlying this phenomenon are still unclear. This study aimed to analyze the differences in the stiffness of the median nerve (MN) and the brachial plexus (BP) using ultrasound shear wave elastography during three sequences of the ULNT1: standard (ULNT1-STD), distal-to-proximal (ULNT1-DIST), and proximal-to-distal (ULNT1-PROX). Methods: Shear wave velocity (SWV) was measured at the initial and final position of each sequence at the MN (wrist) and at the C5 and C6 nerve roots (interscalene level) in 31 healthy subjects. Results: A significant interaction was found between ULNT1 sequence and location (p < 0.001). The ULNT1-STD and ULNT1-DIST induced a greater stiffness increase in the MN (5.67 ± 0.91 m/s, +113.94%; 5.65 ± 0.98 m/s, +115.95%) compared to C5 and C6 (p < 0.001). The ULNT1-PROX resulted in a significantly smaller increase in stiffness at the MN (4.13 ± 0.86 m/s, +54.17%, p < 0.001), but a greater increase at C5 (4.88 ± 1.23 m/s, +53.39%, p < 0.001) and at C6 (4.87 ± 0.81 m/s, +31.55%). The differences for the ULNT1-PROX at C6 were only significant compared to the ULNT1-STD (p < 0.001), but not the ULNT1-DIST (p = 0.066). Conclusions: BP and MN stiffness vary depending on the joint movement sequence during neurodynamic testing. However, the influence of the surrounding tissues may have affected SWV measurements; consequently, these results should be interpreted with caution. Full article