Deciphering Essential Tremor: Computational Exploration of Inferior Olive Dynamics in Cerebellar Networks: TREMBLE-ICED
Essential tremor (ET) during Human Ageing
Essential tremor (ET) is a neurological condition characterised by involuntary shaking, primarily affecting the hands during voluntary movements, but it can also impact other areas, such as the neck or eyes. The severity of ET varies significantly, ranging from a mild inconvenience to a condition that severely disrupts daily life. ET becomes increasingly common with age, affecting approximately 40 out of every 1,000 individuals aged over 65. Recent population-based studies report an incidence rate of 616 per 100,000 in older adults, with over 70% of cases previously undiagnosed, highlighting its widespread prevalence among the elderly.
The exact cause of ET remains uncertain, but it is thought to result from dysfunction in the cerebellum, particularly in the inferior olive (IO), a crucial part of the olivo-cerebellar network that plays a key role in motor coordination. Research has shown that substances such as harmaline can induce synchronised rhythmic activity in the IO, which acts as a pacemaker for tremors. This rhythmic activity is transmitted through cerebellar pathways to motor neurons, leading to tremors, even in the absence of structural abnormalities. Disruptions in the IO’s oscillatory dynamics or its influence on motor pathways may result in abnormal motor signals, contributing to the manifestation of tremors.
Despite advances in ET research, much of the current work focuses on isolated neural responses, limiting our understanding of the broader dynamics of cerebellar networks. TREMBLE-ICED seeks to address this gap by performing integrated simulations of the IO, cerebellum, and systems such as the vestibulo-ocular reflex (VOR). These simulations aim to elucidate the IO’s role in timing, modulation, and coordination within cerebellar circuits and identify disruptions linked to ET. The project also explores new diagnostic approaches and potential therapeutic interventions by manipulating IO functions in silico. By identifying targets to mitigate tremors and enhance motor coordination, this work aims to improve early diagnosis and advance understanding of ET’s underlying mechanisms.