Humans have the capability to interpret and infer patterns in sparse, noisy, and uncertain data. This capability is key to making sense of the world and important to high level functions across society, from medical diagnosis to intelligence analysis. The basis for understanding how cognition leads to this capability lies in the cross-section between behavioral analysis, cognitive science, and neuroscience. Key discoveries in experimental neuroscience provide a window to how neural circuits implement high-level cognitive functions such as spatial perception and decision making. Computational models aim to simulate observed phenomena at a variety of scales and scopes, from neurotransmitters to choice probabilities. The main objective of this special issue is to bring together a representative interrelated set of multidisciplinary modeling approaches to understand how the brain gives rise to sense making. Several key questions will be addressed. How do we decide which information to pay attention to and which to ignore? When and how are those decisions biased? How does the brain learn to solve complex tasks? How do plasticity and dynamics between brain structures evolve with feedback and practice? Topics relevant to this special issue thus include information foraging behavior, cognitive and neural basis for biases, decision making and strategic shifts, memory systems and functions, knowledge structures developed by expertise, and intentional control. Potential topics include, but are not limited to:

• Neuromodulation and Adaptive Behavior
• Spatial and Semantic Reasoning
• Neurally Informed Cognitive Architectures
• Information Foraging Behavior
• Cognitive and Neural Basis for Biases
• Decision Making and Strategic Shifts
• Memory Systems and Functions
• Knowledge Structures Developed by Expertise
• Intentional Control

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