NeuroSpine Institute

Infections related to neuromodulation devices such as spinal cord stimulators (SCS) and intrathecal pumps (ITPs) present complex challenges due to potential complications such as localized infections, deep infections, sepsis, and neurological injury. Prompt diagnosis requires patients and providers to be educated on wound management and sepsis symptoms for immediate medical attention. Antibiotic therapy and duration vary based on infection severity, with deep infections often requiring device removal despite recent improvements in salvage rates with aggressive initial intervention. Deep infections necessitate timely diagnosis through imaging modalities such as magnetic resonance imaging (MRI) or computed tomography (CT), followed by device removal and culture-guided antibiotic therapy, often in collaboration with infectious disease specialists and spine surgeons. ITP infections pose similar challenges along with the risk of meningitis and may require careful management of medication withdrawal symptoms during emergent pump removal. Lab monitoring may aid treatment assessment, although negative cultures can occur due to post-antibiotic exposure. Postoperative recommendations stress standardized guidelines, patient education, and vigilant surveillance, with close follow-up crucial for early infection detection and intervention. Managing device-related infections demands a multi-specialty approach to minimize complications and optimize outcomes. This paper outlines best practices for diagnosing, managing, and treating neuromodulation device infections, focusing on guiding clinical decision-making from the onset of infection through treatment and potential reimplantation.

Abstract Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

Como requisito para ser graduado de la educación superior en cualquier país se hace necesario hacer un ejercicio de titulación, procedimiento mediante el cual el egresado universitario, demuestra los conocimientos adquiridos. Algunas variantes de titulación o ejercicio final son: a) el desarrollo de un trabajo de titulación b) la preparación y aprobación de un examen de grado de carácter complexivo. Mediante este trabajo y con la aplicación de la investigación científica, tecnológica e innovación, se presenta una teoría original o derivada de un tema específico y se demuestra su validez. El conocimiento adquirido mediante la investigación científica y la innovación tecnológica son factores que se convierten en capitales en las actividades económicas y en el desarrollo de los países. A partir de lo antes expuesto se persigue como objetivo mostrar la necesidad de aplicar la investigación científica tecnológica y la innovación en las variantes de titulación universitaria y su rol en la solución a los problemas que se derivan de la alta complejidad y movilidad del entorno en las instituciones productivas y sociales.

Objective: To determine the frequency of Baker’s cyst in patients presenting with knee pain, considering MRI as imaging modality. Study Design: Descriptive, Cross-sectional study. Setting: Department of Radiology, JPMC, Karachi. Period: 03 January 2021 till 02 July 2021. Material & Methods: Total 113 patients presenting with knee pain for >4 weeks duration who were referred for knee MRI were selected in the study. Both male and female patients between 15-65 years included in the study. Post-surgical patients and those with contraindication to MRI were excluded from the study. MRI of effected knee was performed in every selected patient by using 1.5 Tesla MRI by placing the knee in extended position with slight external rotation to facilitate imaging. MR images were interpreted by one consultant radiologist for presence or absence of Baker’s cyst. Results: Patients of 15 to 65 years age were included in the study with mean age of 44.94 ± 6.69 years. Out of 113 patients, 65 (57.52%) were male and 48 (42.48%) were female with male to female ratio of 1.4:1. Mean BMI of patients was 27.45 ± 3.02 kg/m2. Mean duration of pain was 5.78 ± 2.30 months. In our study, 22 patients with knee pain were found to have Baker’s cyst on MRI with frequency of 19.47%. Conclusion: This study concluded that frequency of Baker’s cyst on MRI in patients with knee pain is quite high.

In the field of oncology, statistical models are used for the discovery of candidate factors that influence the development of the pathology or its outcome. These statistical models can be designed in a multiblock framework to study the relationship between different multiomic data, and variable selection is often achieved by imposing constraints on the model parameters. A priori graph constraints have been used in the literature as a way to improve feature selection in the model, yielding more interpretability. However, it is still unclear how these graphs interact with the models and how they impact the feature selection. Additionally, with the availability of different graphs encoding different information, one can wonder how the choice of the graph meaningfully impacts the results obtained. We proposed to study the graph penalty impact on a multiblock model. Specifically, we used the SGCCA as the multiblock framework. We studied the effect of the penalty on the model using the TCGA-LGG dataset. Our findings are 3-fold. We showed that the graph penalty increases the number of selected genes from this dataset, while selecting genes already identified in other works as pertinent biomarkers in the pathology. We demonstrated that using different graphs leads to different though consistent results, but that graph density is the main factor influencing the obtained results. Finally, we showed that the graph penalty increases the performance of the survival prediction from the model-derived components and the interpretability of the results. Source code is freely available at https://github.com/neurospin/netSGCCA.

Successive auditory inputs are rarely independent, their relationships ranging from local transitions between elements to hierarchical and nested representations. In many situations, humans retrieve these dependencies even from limited datasets. However, this learning at multiple scale levels is poorly understood. Here, we used the formalism proposed by network science to study the representation of local and higher-order structures and their interaction in auditory sequences. We show that human adults exhibited biases in their perception of local transitions between elements, which made them sensitive to high-order network structures such as communities. This behavior is consistent with the creation of a parsimonious simplified model from the evidence they receive, achieved by pruning and completing relationships between network elements. This observation suggests that the brain does not rely on exact memories but on a parsimonious representation of the world. Moreover, this bias can be analytically modeled by a memory/efficiency trade-off. This model correctly accounts for previous findings, including local transition probabilities as well as high-order network structures, unifying sequence learning across scales. We finally propose putative brain implementations of such bias.

Parkinson's disease mild cognitive impairment (PD-MCI) is frequent and heterogenous. There is no consensus about its influence on subthalamic deep brain stimulation (STN-DBS) outcomes. To determine the prevalence of PD-MCI and its subtypes in candidates to STN-DBS. Secondarily, we sought to identify MRI structural markers associated with cognitive impairment in these subgroups. Baseline data from the French multicentric PREDISTIM cohort were used. Candidates to STN-DBS were classified according to their cognitive performance in normal cognition (PD-NC) or PD-MCI. The latter included frontostriatal (PD-FS) and posterior cortical (PD-PC) subtypes. Between-group comparisons were performed on demographical and clinical variables as well as on T1-weighted MRI sequences at the cortical and subcortical levels. 320 patients were included: 167 (52%) PD-NC and 153 (48%) PD-MCI patients. The latter group included 123 (80%) PD-FS and 30 (20%) PD-PC patients. There was no between-group difference regarding demographic and clinical variables. PD-PC patients had significantly lower global efficiency than PD-FS patients and significantly worse performance on visuospatial functions, episodic memory, and language. Compared to PD-NC, PD-MCI patients had cortical thinning and radiomic-based changes in the left caudate nucleus and hippocampus. There were no significant differences between the PD-MCI subtypes. Among the candidates to STN-DBS, a significant proportion has PD-MCI which is associated with cortical and subcortical alterations. Some PD-MCI patients have posterior cortical deficits, a subtype known to be at higher risk of dementia.

Sarcopenia is a muscle-wasting disease common among older adults. The condition has been associated with adverse perioperative and postoperative outcomes following spinal surgery. The combination of this muscle-wasting syndrome and spondylolisthesis and how we approached the case makes it a compelling study for surgeons attempting to treat this patient population more effectively. In this case study, we examine a 76-year-old male patient with chronic sarcopenia who needed transforaminal lumbar interbody fusion (TLIF) surgery for his grade 1 L4-5 spondylolisthesis, L4-5 degenerative disc disease, bilateral facet effusions and lumbosacral radiculopathy with active and chronic denervation. He consulted our neurosurgeon for his back pain and left lower extremity paresthesia. Magnetic resonance imaging (MRI) showed degenerative disc disease with bilateral facet effusion in multiple levels of the lumbar spine as well as broad disc bulge in L5-S1. Due to the patient’s past medical history of muscle wasting disease, a muscle biopsy of the left quadriceps was performed and revealed rare denervated fibers indicative of sarcopenia. Minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) was performed as the most optimal surgical method for this condition. The patient experienced a massive decline in his VAS score from 9/10 to 0/10 two months from surgery, reflecting the fast wound healing process and recovery. Postoperatively, the AP X-ray of the lumbar spine showed dextroscoliosis and stable L4/5 TLIF instrumentation. The surgeon provided the patient guidance regarding his nutrition and exercise to maximize the treatment. This case illustrates the employment of the minimally invasive surgery (MIS) approach to diminish complications and tissue trauma of patients with sarcopenia and spondylolisthesis who are undergoing lumbar spine surgery.

A fundamental question in neuroscience is what type of internal representation leads to complex, adaptive behavior. When faced with a deadline, individuals' behavior suggests that they represent the mean and the uncertainty of an internal timer to make near-optimal, time-dependent decisions. Whether this ability relies on simple trial-and-error adjustments or whether it involves richer representations is unknown. Richer representations suggest a possibility of error monitoring, that is, the ability for an individual to assess its internal representation of the world and estimate discrepancy in the absence of external feedback. While rodents show timing behavior, whether they can represent and report temporal errors in their own produced duration on a single-trial basis is unknown. We designed a paradigm requiring rats to produce a target time interval and, subsequently, evaluate its error. Rats received a reward in a given location depending on the magnitude of their timing errors. During the test trials, rats had to choose a port corresponding to the error magnitude of their just-produced duration to receive a reward. High-choice accuracy demonstrates that rats kept track of the values of the timing variables on which they based their decision. Additionally, the rats kept a representation of the mapping between those timing values and the target value, as well as the history of the reinforcements. These findings demonstrate error-monitoring abilities in evaluating self-generated timing in rodents. Together, these findings suggest an explicit representation of produced duration and the possibility to evaluate its relation to the desired target duration.