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Nahari, T.

Publications and source records attributed to Nahari, T..

2 recordsLinked to original sources

The brain prioritizes information that strengthens the structure of knowledge

Humans learn surprisingly well from remarkably little. One way by which such feat may be accomplished is strategic information processing. In particular, the brain may prioritize new inputs that are likely to support efficient mental models. Here we show that people prefer semantic information that strengthens the small-world configuration of a knowledge system, a topology previously associated with creativity and comprehension. Such information is prioritized by the brains language network and elicits enhanced activation in the ventromedial prefrontal cortex, which is central to the brains valuation system. These findings (replicated across studies) reveal a principle of information prioritization: the brain assigns value and resources to knowledge according to its capacity to improve the structure of what we know.

neuroscience↗

Patchy Perception: Rethinking Eye Movements through the Lens of Foraging Theory

Foraging theory provides a powerful framework for reframing visual attention mechanisms, conceptualizing eye movements and visual search as specialized instances of patch foraging problems, rather than viewing them solely through traditional cognitive psychology paradigms. This approach offers new insights into how visual attention optimizes exploration strategies in humans and animals. Using human data from image exploration tasks with items held in short-term memory, we demonstrate that participants spend more time on informationally rich stimuli (memory-matched images) and employ strategies to minimize travel time to these high-value targets--behaviors consistent with optimal patch foraging. Our proposed analytical approach aims at a more foundational question in movement ecology: Why might animals partition their environment into patches of information as they move through it? This work provides a foundation for new ways to analyze already existing data and design experimental paradigms bridging visual neuroscience and behavioral ecology approaches.

animal behavior and cognition↗