Brain Disease Research Articles

Mental health and psychological processes associated with cognitive aging and dementia.

This review focuses on the role of psychological factors in cognitive aging and dementia, an area that has received less attention compared to other modifiable factors (e.g. sleep, physical activity, and so on) or reduction of disease risk. A range of mental health and psychological aspects, including clinical symptoms, stable personality traits, and more specific constructs or processes (e.g. repetitive negative thinking, purpose in life), are associated with cognitive aging and dementia risk. Psychological factors can either serve as protective or risk elements, influencing brain health through general mechanisms, including stress regulation and impact on several biological systems, as well as modulate brain resistance and cognitive resilience to Alzheimer's disease and age-related brain changes. Protective psychological traits are linked to healthier lifestyle habits, while risk factors are associated with negative behaviors, and may impact cognitive function across the lifespan, suggesting benefits for psychological education from early life. The review emphasizes the need for greater focus on optimizing psychological well being, particularly in at-risk populations, and suggests that interventions should be tailored to individuals' values and life purposes. Additionally, further research is needed to explore the neurobiological mechanisms through which psychologically focused interventions may influence cognitive decline and dementia.

Review on Fundamental of Electroencephalography and Detection Techniques in Substance and Behavioral Addiction

Addiction is a chronic relapsing brain disease associated with substantial individual and societal burden. It includes complex phyco-physiological conditions and can be recognized by compulsive and harmful behaviors towards a substance or activity, despite negative consequences or “bio-psycho-social-spiritual” disorder. This paper aims to comprehensively review previous research which applied machine learning to electroencephalography (EEG) signals for automatic detection of addiction. A systematic search was done on 200 relevant papers published between 2018 - 2023. The previous studies applied a variety of machine learning algorithms including support vector machines, neural networks, logistic regressions and brain networks to classify addicted individuals against controls based on resting state, cue-reactivity paradigms and neurofeedback tasks. The features utilized spectral power, functional and effective connectivity, graph theoretical measures and event-related potentials. The output accuracy often exceeded 95% across multiple substances including alcohol, nicotine, cannabis and opioids. In this review, the challenges and open questions around data quality, model interpretation and transition to clinical settings were also discussed. In overall, automatic EEG analysis shows significant potential as an objective and accessible tool for addiction diagnosis, treatment monitoring and relapse prevention that projects worthy of continued refinement and validation.

The impact of apolipoprotein E, type ∊4 allele on Alzheimer's disease pathological biomarkers: a comprehensive post-mortem pilot-analysis.

The apolipoprotein E type ∊4 allele (ApoE4) is known as the strongest genetic risk factor for Alzheimer's Disease (AD). Meanwhile, many aspects of its impact on AD pathology remain underexplored. This study conducts a systematic data analysisof donor data from the Seattle Alzheimer's Disease Brain Cell Atlas. Our investigation delves into the intricate interplay between identified biomarkers and their correlation with ApoE4 across all severities of AD. Employing Pearson R correlation, and one-way and two-way ANOVA tests, we elucidate the pathological changes in biomarkers and the altering effects of ApoE4. Remarkably, the phosphorylation of tau observed in neurofibrillary tangles (NFTs) marked by the AT8 antibody, emerges as the most correlated factor with other pathological biomarkers. This correlation is mediated by both tau and amyloid pathology, suggesting a higher hierarchical role in determining AD pathological effects than other biomarkers. However, non-ApoE4 carriers exhibit a more significant correlation with disease progression severity compared to ApoE4 carriers, though ApoE4 carriers demonstrate significance in exacerbating the effect of accumulating phosphorylated tau and amyloid plaques assessed by AT8 and 6E10 antibodies. Furthermore, our analysis does not observe dramatic neuronal changes in grey matter across the span of AD pathology. Glia activation, measured by Iba1 and GFAP, demonstrates an amyloid-specific correlation. This research marks the first human post-mortem analysis providing a comprehensive examination of prevailing AD biomarkers and their interconnectedness with pathology and ApoE4 genetic factor. Limitations in the study are acknowledged, underscoring the need for further exploration and refinement in future research endeavors.

Clinical and safety outcomes associated with aristolochic acid exposure: a systematic review and meta-analysis

Current studies have clearly shown that aristolochic acid (AA) exposure can induce a variety of diseases, such as kidney disease, liver cancer, and urinary tract cancer (UTC). However, no studies have systematically analyzed and integrated these results. Therefore, we aimed to elucidate the association between AA exposure and the risk of safety outcomes for AA-related overall disease and different types of disease it causes. We conducted an exhaustive search of PubMed, EMBASE, Web of Science, and the Cochrane Library for relevant material up to April 2024. For AA-related overall disease, AA exposure was significantly associated with an increased incidence of AA-related overall disease (OR: 1.289, 95% CI: 1.183–1.404). For different types of disease, AA exposure was significantly associated with increased incidence of kidney disease (OR: 1.279, 95% CI: 1.029–1.590), UTC (OR: 1.842, 95% CI: 1.376–2.465), and liver cancer (OR: 1.146, 95% CI: 1.040–1.262). No significant association was found between AA exposure and the incidence of brain disease (OR: 1.161, 95% CI: 0.989–1.362). This study systematically analyzed various safety outcomes associated with AA exposure to provide a solid scientific basis for future prevention strategies and clinical management.

Olfactory mucosa-mesenchymal stem cells with overexpressed Nrf2 modulate angiogenesis and exert anti-inflammation effect in an in vitro traumatic brain injury model

BackgroundTraumatic brain injury (TBI) is a major cause of disability and mortality among children and adults in developed countries. Transcription factor nuclear factor erythroid-derived 2-like 2 (Nrf2) has antioxidant, anti-inflammatory and neuroprotective effects and is closely related to TBI. Olfactory mucosa-mesenchymal stem cells (OM-MSCs) could promote neural regeneration. At present, the effects of OM-MSCs with overexpressed Nrf2 in brain diseases remain to be explored.MethodsThe OM-MSCs were prepared and transfected with Nrf2 overexpression plasmid. Those transfected cells were termed as OM-MSCs with Nrf2 overexpression (OM-MSCsNrf2) and co-cultured with rat pheochromocytoma cells PC12 or murine microglia BV2. The effects of OM-MSCsNrf2 on the survival and angiogenesis of PC12 cells were evaluated through cell counting kit-8 (CCK-8) and tube formation assay, and extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) were calculated to reflect glycolysis. Immunofluorescence assay was applied to determine the effects of OM-MSCsNrf2 on microglial polarization, and the underlying molecular mechanisms were analyzed based on the quantification tests of RT-qPCR and immunoblotting.ResultsCo-culture of OM-MSCsNrf2 and PC12 cells increased the levels of anti-inflammatory cytokines and pro-angiogenesis factors, enhanced the cell survival and angiogenesis. Moreover, we also observed elevated phosphorylation of PI3K/AKT and suppressed BAX protein expression. Meanwhile, OM-MSCsNrf2 inhibited the levels of pro-inflammatory genes and affected the glycolysis in PC12 cells. In the co-cultured system of OM-MSCsNrf2 and BV2 cells, M2 microglial polarization was observed, and the levels of M2 microglia-relevant genes and the phosphorylation of STAT6/AMPKα/SMAD3 were elevated.ConclusionThis study proved the effects of OM-MSCsNrf2 on modulating PC12 and BV2 cells in vitro, which, however, necessitates further in vivo validation.

An Open Access Resource for Marmoset Neuroscientific Apparatus

Abstract The use of the common marmoset (Callithrix jacchus) for neuroscientific inquiry has grown precipitously over the past two decades. Despite windfalls of grant support from funding initiatives in North America, Europe, and Asia to model human brain diseases in the marmoset, marmoset-specific apparatus are of sparse availability from commercial vendors and thus are often developed and reside within individual laboratories. Through our collective research efforts, we have designed and vetted myriad designs for awake or anesthetized magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), as well as focused ultrasound (FUS), electrophysiology, optical imaging, surgery, and behavior in marmosets across the age-span. This resource makes these designs openly available, reducing the burden of de novo development across the marmoset field. The computer-aided-design (CAD) files are publicly available through the Marmoset Brain Connectome (MBC) resource (https://www.marmosetbrainconnectome.org/apparatus/) and include dozens of downloadable CAD assemblies, software and online calculators for marmoset neuroscience. In addition, we make available a variety of vetted touchscreen and task-based fMRI code and stimuli. Here, we highlight the online interface and the development and validation of a few yet unpublished resources: Software to automatically extract the head morphology of a marmoset from a CT and produce a 3D printable helmet for awake neuroimaging, and the design and validation of 8-channel and 14-channel receive arrays for imaging deep structures during anatomical and functional MRI.

Investigating the In Vivo Effects of Anti-Prion Protein Nanobodies on Prion Disease with AAV Vector

Prion diseases are fatal neurodegenerative disorders affecting humans and animals, and the central pathogenic event is the conversion of normal prion protein (PrPC) into the pathogenic PrPSc isoform. Previous studies have identified nanobodies that specifically recognize PrPC and inhibit the PrPC to PrPSc conversion in vitro. In this study, we investigated the potential for in vivo expression of anti-PrPC nanobodies and evaluated their impact on prion disease. The coding sequences of three nanobodies were packaged into recombinant adeno-associated virus (rAAV) and were administered via intracerebroventricular (ICV) injection in newborn mice. We found that the expression of these nanobodies remained robust for over 180 days, with no observed detrimental effects. To assess their therapeutic potential, we performed ICV injections of nanobody-expressing rAAVs in newborn mice, followed by intracerebral prion inoculation at 5–6 weeks of age. One nanobody exhibited a small yet statistically significant therapeutic effect, extending survival time from 176 days to 184 days. Analyses of diseased brains revealed that the nanobodies did not alter the pathological changes. Our findings suggest that high levels of anti-PrPC nanobodies are necessary to delay disease progression. Further optimization of the nanobodies, AAV vectors, or delivery methods is essential to achieve a significant therapeutic effect.

Neuroimmunometabolism: how metabolism orchestrates immune response in healthy and diseased brain.

Neuroimmunometabolism describes how neuroimmune cells, such as microglia, adapt their intracellular metabolic pathways to alter their immune functions in the central nervous system (CNS). Emerging evidence indicates that neurons also orchestrate the microglia-mediated immune response through neuro-immune cross talk, perhaps through metabolic signaling. However, little is known about how the brain's metabolic microenvironment and microglial intracellular metabolism orchestrate the neuroimmune response in healthy and diseased brains. This review addresses the balance of immunometabolic substrates in healthy and diseased brains, their metabolism by brain-resident microglia, and the potential impact of metabolic dysregulation of these substrates on the neuroimmune response and pathophysiology of psychiatric disorders. This review also suggests metabolic reprogramming of microglia as a preventive strategy for the management of neuroinflammation-related brain disorders, including psychiatric diseases.

Enlightening the promising role of nanoparticle-based treatments against Naegleria fowleri-induced primary amoebic meningoencephalitis: A brain-eating disease.

Naegleria fowleri, is the causative agent of Primary Amoebic Meningoencephalitis (PAM), a lethal acute brain inflammation with high mortality. The virulent and reproductively active trophozoite stage of N. fowleri migrates to central nervous system (CNS) by entering through nasal passage and causes severe neural infection, brain disease and inflammation with high mortality. In this review we present the current available information about N. fowleri, including its case reports, pathogenesis and the mechanism of host neuroinflammation associated with PAM. Various case reports reveal that the survival rate of patients with PAM is very low. Several anti-microbial, anti-parasitic and anti-inflammatory compounds such as doxycycline, amphotericin, acyclovir, miltefosine, ampicillin, ceftriaxone, azithromycin are widely used to treat PAM. Nanoparticles conjugated drug has now attracted better attention in dealing with free-living amoeba community. Conventional drugs are being conjugated with nanomaterials like gold (Au), sliver (Ag) etc. which have elicited better amoebicidal effect against N. fowleri than unconjugated drugs. This targeted strategy may prove helpful and possibly may reduce neural damage.

Plexins: Navigating through the neural regulation and brain pathology.

Plexins are a family of transmembrane receptors known for their diverse roles in neural development, axon guidance, neuronal migration, synaptogenesis, and circuit formation. Semaphorins are a class of secreted and membrane proteins that act as primary ligands for plexin receptors. Semaphorins play a crucial role in central nervous system (CNS) development by regulating processes such as axonal growth, neuronal positioning, and synaptic connectivity. Various types of semaphorins like sema3A, sema4A, sema4C, sema4D, and many more have a crucial role in developing brain diseases. Likewise, various evidence suggests that plexin receptors are of four types: plexin A, plexin B, plexin C, and plexin D. Plexins have emerged as crucial regulators of neurogenesis and neuronal development and connectivity. When bound to semaphorins, these receptors trigger two major networking cascades, namely Rho and Ras GTPase networks. Dysregulation of plexin networking has been implicated in a myriad of brain disorders, including autism spectrum disorder (ASD), Schizophrenia, Alzheimer's disease (AD), Parkinson's disease (PD), and many more. This review synthesizes findings from molecular, cellular, and animal model studies to elucidate the mechanisms by which plexins contribute to the pathogenesis of various brain diseases.

Concentric Ring Trajectory Sampling With k-Space Reordering Enables Assessment of Tissue-Specific T1 and T2 Relaxation for 2H-Labeled Substrates in the Human Brain at 7 T.

Deuterium metabolic imaging (DMI) is an emerging Magnetic Resonance technique providing valuable insight into the dynamics of cellular glucose (Glc) metabolism of the human brain invivo using deuterium-labeled (2H) glucose as non-invasive tracer. Reliable concentration estimation of 2H-Glc and downstream synthesized neurotransmitters glutamate + glutamine (Glx) requires accurate knowledge of relaxation times, but so far tissue-specific T1 and T2 relaxation times (e.g., in gray and white matter) have not been determined. Such measurements are time-consuming and particularly challenging in the presence of dynamically changing metabolite levels (e.g. 2H Glc and 2H Glx). This study aimed to assess T1 and T2 relaxation times of deuterated resonances, i.e., water, Glc and Glx in human gray and white matter using inversion recovery and Hahn spin-echo 2H MRSI (magnetic resonance spectroscopic imaging), respectively, with non-Cartesian concentric ring trajectory readout (CRT) including specific k-space reordering at 7 T. The sequence was validated using phantom measurements and all results were compared to unlocalized acquisitions. Thirteen healthy volunteers participated in the study, with 10 of them scanned ~90 min after oral administration of 0.8 g/kg [6,6'-2H]-glucose. Significantly different T1 and T2 relaxation was observed between GM and WM for 2H water (T1 GM/WM/unlocalized = 358 ± 21/328 ± 12/335 m ± 6 ms, p = 0.01) and 2H Glx (T2 GM/WM/unlocalized = 37 ± 2/35 ± 2/33 ± 3 ms, p = 0.02), respectively, consistent with unlocalized acquisitions. No significant regional differences were found for 2H water (T2 GM/WM/unlocalized = 36 ± 2/34 ± 2/31 ± 2 ms, p = 0.08), 2H Glc (T1 GM/WM/unlocalized = 70 ± 5/73 ± 4/80 ± 5 ms, p = 0.13; T2 GM/WM/unlocalized = 36 ± 1/34 ± 2/34 ± 2 ms, p = 0.24) and Glx (T1 GM/WM/unlocalized = 172 ± 15/172 ± 12/165 ± 11 ms, p = 1.00). Knowledge of tissue-specific relaxation times can enhance the accuracy of concentration estimation and metabolic flux rates in future studies, potentially improving our understanding of various brain diseases such as cancer, neurodegenerative diseases or diabetes, which are often linked to impaired glucose metabolism.

Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis.

Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis. To address these problems, we propose a multi-channel spatio-temporal graph attention contrastive network for DBNs analysis. Specifically, we first construct dynamic brain functional networks from fMRI data with sliding windows, and embed the structural connectivity derived from diffusion tensor imaging (DTI) to the dynamic functional connectivity graph representation to construct multi-modal brain network. Second, we develop a multi-channel spatial attention contrastive network to extract topological features from the brain network within each time window. This network incorporates an intra-window graph contrastive constraint to enhance the discriminative ability of the extracted features. Moreover, temporal dependencies across windows are captured by integrating feature embeddings through a self-attention mechanism, and the inter-window recurrent contrastive constraint is devised to extract higher-order spatio-temporal topological features. Finally, a multi-layer perceptron (MLP) is used to classify the brain networks. Experiments on epilepsy and ADNI datasets show that our method outperforms several state-of-the-art approaches in diagnosing performance, and it provides discriminative graph features for related brain diseases.

Molecular cell atlas of the brain in neuronopathic Gaucher disease

Molecular cell atlas of the brain in neuronopathic Gaucher disease

Brain health is a human right: Implications for policy and research.

The call to synergize brain health with mental health has major ramifications for research and policy. Mental health has been recognized as a universal human right, but no such declaration exists for brain health. Here, I defend the right to lifelong brain health as a derived, intermediary, and generative right. It is derived from the right to physical health because it is reducible to facts about the health of the body. This grounds brain health in the right to physical health, a long-standing right with hard legal status, while avoiding "rights inflation." It is intermediary because it bridges the gap between physical and mental health, since the brain is an organ that is central to both physical and mental health. It is generative because it provides impetus to downstream actions including the creation of health-based "neurorights" and bolstering the right to a healthy environment to protect collective cognitive health. Thus, the right to lifelong brain health would guarantee the right of citizens to live and grow in a brain health-promoting environment. A rights-based approach to brain health also has important consequences for research. It would help to move research away from the disease paradigm that focuses on individual risk and responsibility to the study of deeper contributions to brain health and disease through a population neuroscience approach to public brain health. Until the right to brain health is recognized alongside mental health, their synergy will remain incomplete, and brain health promotion will lack unity.

Investigating the frequency of neural autoantibodies in refractory focal epilepsy.

There have been conflicting reports about the frequency of neural autoantibodies in epilepsy cohorts, which is confounded by the lack of clear distinction of epilepsy from acute symptomatic seizures due to encephalitis. The aim of this study was to determine the frequency of neural autoantibodies in a well characterised population of refractory focal epilepsy of known and unknown cause. Cases were recruited from epilepsy outpatient clinics at the Princess Alexandra, Mater, Royal Brisbane and Women's and Cairns Base Hospitals from 2021 - 2023. Included cases were refractory to medical therapy, met the ILAE definition of focal epilepsy and were characterised using anatomo-electro-clinical correlation. Cases with prior encephalitis, inflammatory neurological disease or prior parenchymal brain insults were excluded. A total of 100 patients were recruited. No cases with clinically significant neural autoantibodies were discovered. One was positive for serum anti-NMDAR antibodies, however autoantibodies were absent from CSF. Cases were also screened using a predictive score (McGinty et al.). From this, 2 cases were identified as seronegative autoimmune associated epilepsy and demonstrated significant reduction in seizure frequency with administration of immunotherapy. These cases had common features including temporo-perisylvian semiology especially ictal piloerection and high seizure frequency. Clinically relevant neural autoantibodies are uncommon in well characterised chronic focal epilepsy populations. Despite this there are isolated cases that still demonstrate improved seizure control with the use of immunotherapy. Such cases highlight the need for further studies to understand the role of immunity in novel pathophysiological mechanisms in epilepsy.

Grey-Matter Structure Markers of Alzheimer's Disease, Alzheimer's Conversion, Functioning and Cognition: A Meta-Analysis Across 11 Cohorts.

Alzheimer's disease (AD) brain markers are needed to select people with early-stage AD for clinical trials and as quantitative endpoint measures in trials. Using 10 clinical cohorts (N = 9140) and the community volunteer UK Biobank (N = 37,664) we performed region of interest (ROI) and vertex-wise analyses of grey-matter structure (thickness, surface area and volume). We identified 94 trait-ROI significant associations, and 307 distinct cluster of vertex-associations, which partly overlap the ROI associations. For AD versus controls, smaller hippocampus, amygdala and of the medial temporal lobe (fusiform and parahippocampal gyri) was confirmed and the vertex-wise results provided unprecedented localisation of some of the associated region. We replicated AD associated differences in several subcortical (putamen, accumbens) and cortical regions (inferior parietal, postcentral, middle temporal, transverse temporal, inferior temporal, paracentral, superior frontal). These grey-matter regions and their relative effect sizes can help refine our understanding of the brain regions that may drive or precede the widespread brain atrophy observed in AD. An AD grey-matter score evaluated in independent cohorts was significantly associated with cognition, MCI status, AD conversion (progression from cognitively normal or MCI to AD), genetic risk, and tau concentration in individuals with none or mild cognitive impairments (AUC in 0.54-0.70, p-value < 5e-4). In addition, some of the grey-matter regions associated with cognitive impairment, progression to AD ('conversion'), and cognition/functional scores were also associated with AD, which sheds light on the grey-matter markers of disease stages, and their relationship with cognitive or functional impairment. Our multi-cohort approach provides robust and fine-grained maps the grey-matter structures associated with AD, symptoms, and progression, and calls for even larger initiatives to unveil the full complexity of grey-matter structure in AD.

Focused ultrasound widely broadens AAV-delivered Cas9 distribution and activity.

Because children have little temporal exposure to environment and aging, most pediatric neurological diseases are inherent, i.e. genetic. Since postnatal neurons and astrocytes are mostly non-replicating, gene therapy and genome editing present enormous promise in child neurology. Unlike in other organs, which are highly permissive to adeno-associated viruses (AAV), the mature blood-brain barrier (BBB) greatly limits circulating AAV distribution to the brain. Intrathecal administration improves distribution but to no more than 20% of brain cells. Focused ultrasound (FUS) opens the BBB transiently and safely. In the present work we opened the hippocampal BBB and delivered a Cas9 gene via AAV9 intrathecally. This allowed brain first-pass, and subsequent vascular circulation and re-entry through the opened BBB. The mouse model used was of Lafora disease, a neuroinflammatory disease due to accumulations of misshapen overlong-branched glycogen. Cas9 was targeted to the gene of the glycogen branch-elongating enzyme glycogen synthase. We show that FUS dramatically (2000-fold) improved hippocampal Cas9 distribution and greatly reduced the pathogenic glycogen accumulations and hippocampal inflammation. FUS is in regular clinical use for other indications. Our work shows that it has the potential to vastly broaden gene delivery or editing along with clearance of corresponding pathologic basis of brain disease.

Abstract DP12: Leukocyte Telomere Length as a Predictor of Age-Related Brain Diseases: Evidence from the UK Biobank

Abstract DP12: Leukocyte Telomere Length as a Predictor of Age-Related Brain Diseases: Evidence from the UK Biobank

Dodecyl creatine ester, a promising treatment to deliver creatine to neurons, achieves pharmacology efficacy in creatine transporter deficiency.

Dodecyl creatine ester (DCE) is a creatine prodrug currently developed for brain diseases, including creatine transporter deficiency (CTD), an incurable rare genetic disease. A dual strategy combining a prodrug to bypass the non-functional creatine transporter and its delivery via the nose-to-brain pathway has been proposed to replenish creatine levels in cerebral cells, particularly in neurons of CTD patients. In vitro and in vivo studies in various animal models, including wild-type non-human primates and creatine transporter deficient mice, show that formulated DCE, when administered intranasally, achieves significant cerebral distribution up to the target cells, the neurons, and modulates the expression of neuronal markers related to cognitive function at doses intended for patients. These compelling results contribute to a better understanding of the pharmacokinetics and pharmacodynamics of DCE after nasal administration, with a particular focus on the crucial role of the nose-to-brain pathway in DCE distribution.

The impact of channel density, inverse solutions, connectivity metrics and calibration errors on OPM-MEG connectivity analysis: A simulation study.

Magnetoencephalography (MEG) systems based on optically pumped magnetometers (OPMs) have rapidly developed in the fields of brain function, health, and disease. Functional connectivity analysis related to the resting-state has gained popularity as a field of research in recent years. Several studies have attempted to use OPM-based MEG (OPM-MEG) for brain network estimation research; however, the choice of source connectivity analysis pipeline may lead to outcome variability. Several methods and related parameters must be selected carefully at each step of the analysis. Therefore, this study assessed the effect of such analytical variability on the OPM-MEG connectivity analysis by conducting simulations. Synthetic MEG data corresponding to two default mode networks (DMN) with six or ten DMN regions were generated using the Gaussian Graphical Spectral (GGS) model. Six intersensor spacings were constructed, and six inverse algorithms and six functional connectivity measures were selected to assess their impact on the network reconstruction accuracy. Three potential sources of error-errors in the sensor gain, crosstalk, and angular errors of the sensitive axis of the OPM-were also assessed. Analytical variability with regard to the tested intersensor spacings, inverse solutions, and functional connectivity measures led to high result variability. Crosstalk exerted a significant impact on the accuracy, which may lead to network reconstruction failure. The accuracy improvement caused by an increase in the sensor density may be reduced by gain and angular errors. The minimum norm estimate (MNE) and weighted minimum norm estimate (wMNE) exhibited low robustness to sensor noise and calibration errors. Hence, a calibration workflow for accurate sensor parameters, such as the gain and direction of the sensitive axis, before commencing OPM-MEG measurement and a careful choice of different method combinations play crucial roles in ensuring that OPMs yield optimal results for functional connectivity analysis. A thorough framework for analyzing brain connectivity networks was provided herein.