The Neural Basis of Decision-Making During Sensemaking: Implications for Human-System Interaction
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2015 IEEE. We have created a high-fidelity model of 9 regions of the brain involved in making sense of complex and uncertain situations. Sense making is a proactive form of situation awareness requiring sifting through information of various types to form hypotheses about evolving situations. The MINDS model (Mirroring Intelligence in a Neural Description of Sensemaking) reveals the neural principles and cognitive tradeoffs that explain weaknesses in human reasoning and decision-making. The MINDS computational model is a milestone in neurobiological modeling, explaining human sensemaking at a neural level of detail. Constraints in cognition from neurobiological and cognitive neuroscience literature inform the architecture and processing in the model, and we have validated it against human behavioral data. Few such models exist because it requires expertise in many different regions of the brain, and the direct and indirect interactions make integration challenging. The model explains the origin of certain cognitive biases, and in many cases it is the interactions between component brain regions that are responsible for the strengths and the weaknesses of human decision-making. We will provide examples of this below. Human sense makers bring a lifetime of experience to bear on problems; but since this is nearly impossible to replicate in a computational model, challenge problems were designed to focus on the reasoning and analysis aspect of human sense making. The challenge problems - geospatial reasoning for counter-insurgency operations - require decision-making aspects such as: selecting which type of available information to request next, deciding how much to review older information before making a decision, adapting probabilities over hypotheses as new information comes in, and spatial reasoning including configural or distance judgments. We will give a high level overview of how the human brain makes sense of the world, and describe how our model simulates this. We will briefly describe five studies on different aspects of the sensemaking process, each with a high-level background in the neurobiological justification for our mechanistic explanations, and comparison with the results of a pool of human subjects. Our model is distinguished not only by simulating individual brain regions in depth, but also by detailing their interactions. Cognitive biases in decisionmaking emerge from both. We will conclude with implications for the design of human-system interaction systems.
