This project examines how people understand and organize information when they speak, especially how sentence structure changes to highlight either shared knowledge or new information in conversation. While past research has focused on languages with fixed word order, this study looks at languages where the grammar of sentences (especially word order) is much more dependent on conversational context and other information. It also examines how grammar, word meanings, and context work together and are understood by the brain. By including languages with different types of grammars, the project advances psycholinguistic research to better reflect how people learn and use language in real life, and how they process information in conversation. The methodology relies on the collection of cognitive data, including eye gaze data that measures where people look while listening to, speaking, and reading in their language. The data test how conversational context can make sentences easier, or harder, to process. Findings regarding how cognitive factors interact with real-world knowledge support the development of better artificial intelligence (AI) models, including large language models that are less efficient at incorporating contextual information. Other benefits to society include advances in biotechnology through use-based application of neuroscience technologies and improved AI translation software that more seamlessly relates information between languages. This project invest