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Computerised paradigms have enabled decision making re-searchers to gather rich data on human behaviour, includinginformation on motor execution of a decision, e.g., by track-ing mouse cursor trajectories. As the number and complexityof mouse-tracking studies rapidly increase, more sophisticatedmethodology is needed to analyse the decision trajectories.Here we present a new computational approach to generat-ing decision landscape visualisations based on mouse-trackingdata. Decision landscape is an analogue of energy potentialfield mathematically derived from velocity of mouse move-ment during a decision. Visualised as a 3D surface, it pro-vides a comprehensive overview of motor evolution of deci-sions. Employing the dynamical systems theory framework,we develop a new method for generating decision landscapesbased on arbitrary number of trajectories. The decision land-scape visualisation have potential to become a novel tool foranalysing mouse trajectories during decision execution, whichcan provide new insights into the dynamics of decision mak-ing.