<p>Fuzzy Cognitive Maps (FCMs) are widely used decision-support tools that model complex systems, often incorporating human knowledge alongside other evidence in environments characterized by uncertainty. Despite their extensive application across diverse fields such as risk analysis, environmental management, economics, and public health, the dynamics of FCMs are influenced by several key factors, notably the activation function. This paper explores the role of the activation function in FCMs, emphasizing its impact on model validity, transparency, and interpretability. We propose six measurable characteristics of activation functions and assess their alignment with the needs of FCM practitioners. Through a comprehensive simulation study, we demonstrate how different activation functions lead to distinct behaviors, particularly in terms of convergence and state space accessibility. Our findings reveal that the choice of activation function can significantly affect FCM dynamics, offering new insights into model behavior and supporting better decision-making. This research contributes to the ongoing development of FCM methodology by providing practical guidelines for selecting activation functions tailored to specific modeling contexts.</p>