Imagine you’re trying to solve a complex jigsaw puzzle. You carefully examine each piece, comparing its shape and color, until you accumulate enough evidence to confidently decide where it fits. This process of gathering and weighing evidence is similar to how our brains make decisions. Scientists use evidence accumulation models (EAMs) to understand these underlying cognitive processes. Until recently, EAMs were mainly used for simple tasks, like deciding which button to press. However, researchers have now applied these models to real-life scenarios, such as air traffic control, driving, and medical image analysis. By studying these safety-critical decisions, scientists hope to unravel the intricate workings of human cognition in high-pressure situations. The insights gained from these studies could lead to improved training programs for professionals in various fields, ensuring better decision-making and potentially saving lives! If you’re curious about how EAMs are revolutionizing our understanding of decision-making in the wild, dive into the fascinating research article linked below!

Evidence accumulation models (EAMs) are a class of computational cognitive model used to understand the latent cognitive processes that underlie human decisions and response times (RTs). They have seen widespread application in cognitive psychology and neuroscience. However, historically, the application of these models was limited to simple decision tasks. Recently, researchers have applied these models to gain insight into the cognitive processes that underlie observed behaviour in applied domains, such as air-traffic control (ATC), driving, forensic and medical image discrimination, and maritime surveillance.

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