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Brunec, I.

Publications and source records attributed to Brunec, I..

2 recordsLinked to original sources

Expert Navigators Deploy Rational Hierarchical Priorization Over Predictive Maps For Large-Scale Real-World Planning

Efficient planning is a distinctive hallmark of intelligence in humans, who routinely make rapid inferences over complex world contexts. However, studies investigating how humans accomplish this tend to focus on naive participants engaged in simplistic tasks with small state-spaces, which do not reflect the intricacy, ecological validity, and human specialisation in real-world planning. In this study, we examine the street-by-street route planning of London taxi drivers navigating across more than 26,000 streets in London (UK). We explore how planning unfolded dynamically over different phases of journey construction and identify theoretic principles by which these expert human planners rationally precache decisions at prioritised environment states in an early phase of the planning process. In particular, we find that measures of path complexity predict human mental sampling prioritisation dynamics independent of alternative measures derived from the real spatial context being navigated. Our data provide real-world evidence for complexity-driven remote state access within internal models and precaching during human expert route planning in very large structured spaces. Significance statementHumans can plan efficiently in incredibly complex situations. Existing work has looked at naive participants in simple tasks, which might not be representative of how experts plan in the real world. Here, we study the real-world planning process of London taxi drivers - famous for their expert knowledge of London. By analyzing their response times as a proxy for thinking times, we reveal that at an early stage in their thought process, they store decisions at key street junctions to keep them in mind for later planning. Using computational modeling, we show that taxi drivers prioritize inference at street junctions according to normative metrics measuring how critical a particular decision is for reducing the complexity of planning across the entire city.

neuroscience↗

Organization of pRF size along the AP axis of the hippocampus is related to specialization for scenes

The hippocampus is largely recognized for its integral contributions to memory processing. By contrast, its role in perceptual processing remains less clear. Hippocampal properties differ along the anterior-posterior (AP) axis. Based on past research suggesting a gradient in the scale of features processed along the anterior-posterior extent of the hippocampus, the representations have been proposed to differ as a function of granularity along this axis. One way to quantify such granularity is with population receptive field (pRF) size measured during visual processing, which has so far received little attention. In this study, we compare the pRF sizes within the hippocampus to its activation for images of scenes versus faces. We also measure these functional properties in surrounding medial temporal lobe (MTL) structures. Consistent with past research, we find pRFs to be larger in anterior than in the posterior hippocampus. Critically, our analysis of surrounding MTL regions, such as the perirhinal cortex, entorhinal cortex and parahippocampal cortex, shows a similar relationship between scene sensitivity and larger pRF size. These findings provide conclusive evidence for a tight relationship between pRF size and the sensitivity to image content in the hippocampus.

neuroscience↗