Computational modelling: moonlighting on the neuroscience and medicine

Abstract

Computational modelling has emerged as a powerful tool to study the behaviour of complex systems. Computer simulation may lead to a better understanding of the function of biological systems and the pathophysiological mechanisms underlying various diseases. In neuroscience, modelling techniques have provided knowledge about the electrical properties of neurons, activity of ion channels, synaptic function, information processing, and signalling pathways. Using simulations and analysis in network models has resulted in greater understanding of the behaviour of neural networks and dynamics of synaptic connectivity. Moreover, the correlation between the neurobiological mechanisms and a cluster of physiological, cognitive, and behavioural phenomena may be explored by the computational modelling of the neuronal systems. In this context, a significant progress has been made in understanding of the neural network architectures including those with a high degree of connectivity between the units, information processing, performance of complex cognitive tasks, integration of brain signals, as well as the dynamic mechanisms and computations implemented in the brain for making goal-directed choices. Computational models are able to explore the interactions between the brain areas which are involved in predictive processes and high-level skills. In this review, the significance of computational modelling in the study of neural networks, decision-making procedure, nerve growth factor signalling, and endocannabinoid system along with its medical applications have been highlighted. Biomedical Reviews 2013; 24: 25-31.