Mechanisms of vagus nerve stimulation for the treatment of neurodevelopmental disorders: a focus on microglia and neuroinflammation
Bibliographic record
Abstract
The vagus nerve (VN) is the primary parasympathetic nerve, providing two-way communication between the body and brain through a network of afferent and efferent fibers. Evidence suggests that altered VN signaling is linked to changes in the neuroimmune system, including microglia. Dysfunction of microglia, the resident innate immune cells of the brain, is associated with various neurodevelopmental disorders, including schizophrenia, attention deficit hyperactive disorder (ADHD), autism spectrum disorder (ASD), and epilepsy. While the mechanistic understanding linking the VN, microglia, and neurodevelopmental disorders remains incomplete, vagus nerve stimulation (VNS) may provide a better understanding of the VN's mechanisms and act as a possible treatment modality. In this review we examine the VN's important role in modulating the immune system through the inflammatory reflex, which involves the cholinergic anti-inflammatory pathway, which releases acetylcholine. Within the central nervous system (CNS), the direct release of acetylcholine can also be triggered by VNS. Homeostatic balance in the CNS is notably maintained by microglia. Microglia facilitate neurogenesis, oligodendrogenesis, and astrogenesis, and promote neuronal survival via trophic factor release. These cells also monitor the CNS microenvironment through a complex sensome, including groups of receptors and proteins enabling microglia to modify neuroimmune health and CNS neurochemistry. Given the limitations of pharmacological interventions for the treatment of neurodevelopmental disorders, this review seeks to explore the application of VNS as an intervention for neurodevelopmental conditions. Accordingly, we review the established mechanisms of VNS action, e.g., modulation of microglia and various neurotransmitter pathways, as well as emerging preclinical and clinical evidence supporting VNS's impact on symptoms associated with neurodevelopmental disorders, such as those related to CNS inflammation induced by infections. We also discuss the potential of adapting non-invasive VNS for the prevention and treatment of these conditions. Overall, this review is intended to increase the understanding of VN's potential for alleviating microglial dysfunction involved in schizophrenia, ADHD, ASD, and epilepsy. Additionally, we aim to reveal new concepts in the field of CNS inflammation and microglia, which could serve to understand the mechanisms of VNS in the development of new therapies for neurodevelopmental disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".