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Virtual reality (VR) represents a key technology of the 21st century, attracting substantial interest from a wide range of scientific disciplines. With regard to clinical neuropsychology, a multitude of new VR applications are being developed to overcome the limitations of classical paradigms. Consequently, researchers increasingly face the challenge of systematically evaluating the characteristics and quality of VR applications to design the optimal paradigm for their specific research question and study population. However, the multifaceted character of contemporary VR is not adequately captured by the traditional quality criteria (ie, objectivity, reliability, validity), highlighting the need for an extended paradigm evaluation framework. To address this gap, we propose a multidimensional evaluation framework for VR applications in clinical neuropsychology, summarized as an easy-to-use checklist (VR-Check). This framework rests on 10 main evaluation dimensions encompassing cognitive domain specificity, ecological relevance, technical feasibility, user feasibility, user motivation, task adaptability, performance quantification, immersive capacities, training feasibility, and predictable pitfalls. We show how VR-Check enables systematic and comparative paradigm optimization by illustrating its application in an exemplary research project on the assessment of spatial cognition and executive functions with immersive VR. This application furthermore demonstrates how the framework allows researchers to identify across-domain trade-offs, makes deliberate design decisions explicit, and optimizes the allocation of study resources. Complementing recent approaches to standardize clinical VR studies, the VR-Check framework enables systematic and project-specific paradigm optimization for behavioral and cognitive research in neuropsychology.

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourettes syndrome, the supplementary motor area in Parkinsons disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

BACKGROUND:Clinical brain MRI is normal in the majority of patients with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. However, extensive deep white matter damage wasrecently identifiedin these patients using diffusion weighted imaging. Here, our aim was to study a particularly vulnerable brain compartment, the late myelinating superficial white matter. METHODS:Forty-six patients with anti-NMDAR encephalitis were included. Ten out of these were considered neurologically recovered (modified Rankin scale of zero), while 36 patients were non-recovered. In addition, 30 healthy controls were studied. MRI data were collected from all subjects and superficial white matter mean diffusivity derived from diffusion tensor imaging was compared between groups in whole brain, lobar and vertex-based analyses. Patients underwent comprehensive cognitive testing, and correlation analyses were performed between cognitive performance and superficial white matter integrity. RESULTS:Non-recovered patients showed widespread superficial white matter damage in comparison to recovered patients and healthy controls. Vertex-based analyses revealed that damage predominated in frontal and temporal lobes. In contrast, the superficial white matter was intact in recovered patients. Importantly, persistent cognitive impairments in working memory, verbal memory, visuospatial memory and attention significantly correlated with damage of the superficial white matter in patients. CONCLUSIONS:Anti-NMDAR encephalitis is associated with extensive superficial white matter damage in patients with incomplete recovery. The strong association with impairment in several cognitive domains highlights the clinical relevance of white matter damage in this disorder and warrants investigations of the underlying pathophysiological mechanisms.

Objective: Persisting neurological symptoms after COVID‐19 affect up to 10% of patients and can manifest in fatigue and cognitive complaints. Based on recent evidence, we evaluated whether cerebral hemodynamic changes contribute to post‐COVID syndrome (PCS). Methods: Using resting‐state functional magnetic resonance imaging, we investigated brain perfusion and oxygen level estimates in 47 patients (44.4 ± 11.6 years; F:M = 38:9) and 47 individually matched healthy control participants. Group differences were calculated using two‐sample t‐tests. Multivariable linear regression was used for associations of each regional perfusion and oxygen level measure with cognition and sleepiness measures. Exploratory hazard ratios were calculated for each brain metric with clinical measures. Results: Patients presented with high levels of fatigue (79%) and daytime sleepiness (45%). We found widespread decreased brain oxygen levels, most evident in the white matter (false discovery rate adjusted‐p‐value (p‐FDR) = 0.038) and cortical grey matter (p‐FDR = 0.015). Brain perfusion did not differ between patients and healthy participants. However, delayed patient caudate nucleus perfusion was associated with better executive function (p‐FDR = 0.008). Delayed perfusion in the cortical grey matter and hippocampus were associated with a reduced risk of daytime sleepiness (hazard ratio (HR) = 0.07, p = 0.037 and HR = 0.06, p = 0.034). Decreased putamen oxygen levels were associated with a reduced risk of poor cognitive outcome (HR = 0.22, p = 0.019). Meanwhile, lower thalamic oxygen levels were associated with a higher risk of cognitive fatigue (HR = 6.29, p = 0.017). Interpretation: Our findings of lower regional brain blood oxygen levels suggest increased cerebral metabolism in PCS, which potentially holds a compensatory function. These hemodynamic changes were related to symptom severity, possibly representing metabolic adaptations. [ABSTRACT FROM AUTHOR]

Introduction: Genetic predisposition to autoimmune encephalitis with antibodies against N-methyl-D-aspartate receptor (NMDAR) is poorly understood. Given the diversity of associated environmental factors (tumors, infections), we hypothesized that human leukocyte antigen (HLA) and killer-cell immunoglobulin-like receptors (KIR), two extremely polymorphic gene complexes key to the immune system, might be relevant for the genetic predisposition to anti-NMDAR encephalitis. Notably, KIR are chiefly expressed by Natural Killer (NK) cells, recognize distinct HLA class I allotypes and play a major role in anti-tumor and anti-infection responses. Methods: We conducted a Genome Wide Association Study (GWAS) with subsequent control-matching using Principal Component Analysis (PCA) and HLA imputation, in a multi-ethnic cohort of anti-NMDAR encephalitis (n=479); KIR and HLA were further sequenced in a large subsample (n=323). PCAcontrolled logistic regression was then conducted for carrier frequencies (HLA and KIR) and copy number variation (KIR). HLA-KIR interaction associations were also modeled. Additionally, single cell sequencing was conducted in peripheral blood mononuclear cells from 16 cases and 16 controls, NK cells were sorted and phenotyped. Results: Anti-NMDAR encephalitis showed a weak HLA association with DRB1*01:01~DQA1*01:01~DQB1*05:01 (OR=1.57, 1.51, 1.45; respectively), and DRB1*11:01 (OR=1.60); these effects were stronger in European descendants and in patients without an underlying ovarian teratoma. More interestingly, we found increased copy number variation of KIR2DL5B (OR=1.72), principally due to an overrepresentation of KIR2DL5B*00201. Further, we identified two allele associations in framework genes, KIR2DL4*00103 (25.4% vs. 12.5% in controls, OR=1.98) and KIR3DL3*00302 (5.3% vs. 1.3%, OR=4.44). Notably, the ligands of these KIR2DL4 and KIR3DL3, respectively, HLA-G and HHLA2, are known to act as immune checkpoint with immunosuppressive functions. However, we did not find differences in specific KIR-HLA ligand interactions or HLA-G polymorphisms between cases and controls. Similarly, gene expression of CD56dim or CD56bright NK cells did not differ between cases and controls. Discussion: Our observations for the first time suggest that the HLA-KIR axis might be involved in anti-NMDAR encephalitis. While the genetic risk conferred by the identified polymorphisms appears small, a role of this axis in the pathophysiology of this disease appears highly plausible and should be analyzed in future studies. [ABSTRACT FROM AUTHOR]

Memory for object locations in proximity is an essential aspect of everyday activities and has high clinical relevance. Immersive Virtual Reality (VR) has the potential to bridge the gap between the experimental control of laboratory conditions and reliable predictions of functional abilities. We developed the immersive Virtual Memory Task (imVMT), a neuropsychological assessment tool for spatial memory that combines gesture-based natural hand interaction and a head-mounted display. Our aim was to investigate the imVMT task characteristics, to validate the imVMT regarding the underlying cognitive processes, and to evaluate its applicability and feasibility in the clinical context in a sample of thirty-five patients with various neurological disorders and functional deficits. We further aimed to assess object-location memory in a small-scale virtual environment. Our results show that task difficulty can be efficiently manipulated by increasing the number of objects to memorize and rotation angle against the encoding perspective. We demonstrate construct validity as our primary outcome measure was significantly related to spatial memory performance in conventional neuropsychological tests. The imVMT was highly feasible and received high ratings for usability. The imVMT represents an ecologically relevant and valid VR task for assessing object-location memory in a wide range of neurological patients. German Clinical Trials Register identifier: DRKS00024005. [ABSTRACT FROM AUTHOR]

Background: This article is co-authored by a patient with BRAFV600E metastatic melanoma and his treating oncologist. Case Description: The patient describes how he coped with his diagnosis and treatment. He details the pathway of his melanoma treatment, which has spanned over 10 years, including surgical interventions, medical treatment, and participation in clinical trials. He relates his experience of living with the disease—and the adverse effects of treatment—in the long term. The clinical perspective of his treating oncologist reviews the diagnostic process and explains how the therapeutic options were selected for and with the patient. The oncologist also addresses the integration of the patient into clinical trials involving programmed death-1 (PD-1) inhibitors and BRAF/MEK inhibitors. Challenges related to the adverse effects that occurred and the personalised treatment of the patient are also discussed. Finally, the article evaluates current advances in treatment and future therapeutic approaches. Conclusions: This case highlights the challenges of identifying which therapeutic options are most appropriate for individual patients with BRAFV600E metastatic melanoma. Plain Language Summary: About half of all people with melanoma have a BRAFV600E gene mutation. Targeted therapies called BRAF inhibitors may be appropriate; such treatment can rapidly suppress melanoma growth and control the tumour in many patients. Immunotherapies, such as pembrolizumab, have emerged for patients with melanoma that has spread to other parts of the body. Triple combination therapy with a BRAF inhibitor, a MEK inhibitor plus pembrolizumab, can extend the therapeutic effects of BRAF/MEK inhibition, but also cause immune-related adverse events (mainly involving the gut, skin, liver, and lung). Steroids that treat these adverse events may reduce the antitumour response. This article concerns a patient who has lived with BRAFV600E-mutant melanoma for over 10 years and illustrates the situation from the perspective of both the patient and his oncologist. The patient describes how he coped with his diagnosis and treatment challenges, and his melanoma treatment pathway, including surgical interventions, medical treatment, and participation in clinical trials. He relates his experience of living with the disease and the adverse effects of treatment. The patient's oncologist reviews the diagnostic process and explains how the therapeutic options were selected for and with the patient. The oncologist also addresses the integration of the patient into clinical trials involving programmed death-1 (PD-1) inhibitors and BRAF/MEK inhibitors. Challenges related to the adverse effects that occurred and the personalised treatment of the patient are discussed. This partnership encouraged the patient to stay on treatment, enjoy a good quality of life, care for his family, and ultimately enter complete remission. [ABSTRACT FROM AUTHOR]