Video Presentation Portrait
Abstract
Toxoplasma gondii (T.gondii), a protozoan parasite with global prevalence, shows a unique neurotropism that allows it to persist chronically within the central nervous system (CNS). While often clinically silent, chronic toxoplasmosis has been increasingly associated with a range of psychiatric conditions, including schizophrenia, bipolar disorder, suicidal behaviour, and potentially Alzheimer’s disease. The underlying mechanisms are multifactorial,involving direct cyst localization, neuroinflammation, altered neurotransmission, and immunomodulation. In parallel, artificial intelligence (AI) and machine learning (ML) tools are transforming the landscape of biomedical research. In the context of T. gondii, these tools are being employed in neuroimaging analysis, behavioural prediction models, and systems-level simulation of brain-parasite interactions. AI has the potential to enhance early detection of neuroanatomical changes, predict psychiatric outcomes based on infection markers, and uncover latent patterns in large-scale datasets. This descriptive review aims to synthesize the current knowledge on the neurological effects of T. gondii infection while highlighting the emerging integration of AI methodologies in parasitic neuroscience. We discuss pathophysiological mechanisms, psychiatric implications, and how computational tools may bridge gaps in understanding this enigmatic pathogen’s impact on the human brain.