Learned Spatial Schemas and Prospective Hippocampal Activity Support Navigation After One-Shot Learning

Abstract

Prior knowledge structures (or schemas) confer multiple behavioral benefits. First, when we encounter information that fits with prior knowledge structures, this information is generally better learned and remembered. Second, prior knowledge can support prospective planning. In humans, memory enhancements related to prior knowledge have been suggested to be supported, in part, by computations in prefrontal and medial temporal lobe (MTL) cortex. Moreover, animal studies further implicate a role for the hippocampus in schema-based facilitation and in the emergence of prospective planning signals following new learning. To date, convergence across the schema-enhanced learning and memory literature may be constrained by the predominant use of hippocampally dependent spatial navigation paradigms in rodents, and non-spatial list-based learning paradigms in humans. Here, we targeted this missing link by examining the effects of prior knowledge on human navigational learning in a hippocampally dependent virtual navigation paradigm that closely relates to foundational studies in rodents. Outside the scanner, participants overlearned Old Paired Associates (OPA- item-location associations) in multiple spatial environments, and they subsequently learned New Paired Associates (NPA-new item-location associations) in the environments while undergoing fMRI. We hypothesized that greater OPA knowledge precision would positively affect NPA learning, and that the hippocampus would be instrumental in translating this new learning into prospective planning of navigational paths to NPA locations. Behavioral results revealed that OPA knowledge predicted one-shot learning of NPA locations, and neural results indicated that one-shot learning was predicted by the rapid emergence of performance-predictive prospective planning signals in hippocampus. Prospective memory relationships were not significant in parahippocampal cortex and were marginally dissociable from the primary hippocampal effect. Collectively, these results extend understanding of how schemas impact learning and performance, showing that the precision of prior spatial knowledge is important for future learning in humans, and that the hippocampus is involved in translating this knowledge into new goal-directed behaviors.

Keywords: hippocampus; medial temporal lobe; memory; navigation; prior knowledge; prospective planning; schema; spatial learning.

Figure 1

Experimental design. Participants were tested on two consecutive days, approximately 24 h apart. The paradigm was a 2D navigational paradigm in which participants were instructed to learn face-cue locations (Old Paired Associates, OPA; in blue) in 36 rooms with differential wallpapers. On Day 1 and the beginning of Day 2, participants learned OPA-locations on a laptop computer. During OPA block 1 they saw the OPA-location and just had to move to it, but for OPA blocks 2–12 they had to search for the hidden OPA-location. After OPA blocks 4, 8 and 12, participants received an associative memory task in which they were asked to pair the right face with the correct environmental/room wallpaper (in red). After finishing OPA training, participants underwent fMRI while they learned a new (New Paired Associates, NPA; in green) location for each room, this time without a face.

Figure 2

Behavioral results OPA-training and NPA-learning. Average group-level behavioral results. (Upper) Normalized path length (or Path efficiency, PE, in blue) and time needed to find the cue (in orange) for each block, both during OPA and NPA learning blocks. (Lower) Associative wallpaper-face memory was tested after every fourth OPA block. OPA, NPA and associative performance significantly improved over blocks, revealing robust learning. Importantly, NPA learning (NPA blocks 2 and 3) was significantly faster than OPA learning (OPA blocks 2 and 3), as supported by a significant condition × block interaction.

Figure 3

Within-subject trial-level behavioral predictors of one-shot NPA learning. Quartiles reflect within-subject binning of environment-by-environment measures into quartiles for visualization purposes only (Linear Mixed Effects, LME analyses used continuous performance differences across each environment). (A) Performance on the most recent retrieval-practice experience with OPA items (i.e., OPA block 12) predicted NPA PE after one-shot learning (i.e., NPA block 2 performance). (B) There was a complex, curvilinear relationship between “luck” in NPA location search in NPA block 1 and one-shot learning success (controlled for in our statistical analyses). *p < 0.05.

Figure 4

Within-subject trial-level relationship between region of interest (ROI) activity and NPA performance after one-shot learning. Quartiles reflect within-subject binning of environment-by-environment measures into quartiles for visualization purposes only (Linear Mixed Effects, LME analyses used continuous performance differences across each environment). (A) During NPA block 2 prospective planning (i.e., after one-shot learning), there was a marginal relationship between hippocampal activity and navigation performance. (B) This relationship was non-significant in parahippocampal cortex. (C) Within hippocampal subdivisions, prospective planning activity in the hippocampal body significantly predicted NPA block 2 navigation performance. Inset graphs: paralleling exploration of our behavioral data, “Lucky Shots” (orange; controlled for in our analyses) altered the relationship between activity and one-shot NPA performance. *p < 0.05, ^~p < 0.1.

Figure 5

Within-subject relationship between OPA performance and hippocampal activity. Quartiles reflect within-subject binning of environment-by-environment measures into quartiles for visualization purposes only (LME analyses used continuous performance differences across each environment). (A) Within the hippocampus, there was a negative relationship between planning activity and OPA_average performance that significantly interacted with “luck” during initial NPA encoding. (B) Controlling for the effect of Lucky Shots, when participants had better OPA_average performance and encountered the NPA location quickly during NPA block 1, they recruited the hippocampus and its subdivisions less on NPA block 2 when planning navigation to the NPA location.