P320 Updating of spatial memories in a systems-model of vector trace cells in the subiculum
Fei Wang*1, Andrej Bicanski1
1Department ofPsychology,Max-Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
*Email:wangf@cbs.mpg.de
Introduction
The Subiculum (Sub) is known as the output layer of the hippocampal formation, and contains boundary vector cells (BVCs), firing for boundaries at specific allocentric directions and distances1, 2. More recently it has been shown that Sub vector cells can exhibits traces that persists for hours after boundary/object removal1 (Fig. 1a).Prior models suggest that such traces can be evoked by place cells (PCs), which index boundary/object presence at encoding2. Vector trace cells (VTCs) mainly occur in the distal Sub (dSub). However, an account of proximo-distal differences remains absent. Here we propose that vector trace cell coding in Sub provides a mismatch signal to update spatial memory representations.
Methods
In our model (Fig. 1b) dSub neurons receive feedforward input from either direct sensory information (BVCs in pSub) or mnemonic information (PCs in CA1). Mismatch between these inputs updates CA1-dSub synapses, with different dSub units having varying updating rates. Following the hypothesized CA1–Sub proximal–distal pathway3, which is implicated in spatial memory specialization, we show how inserted cues affect distal and proximal CA1 (dCA1, pCA1) and their corresponding dSub units. In this model, space-related pCA1 PCs transfer mnemonic information to dSub, while object-related dCA1 PCs exhibit place field drift toward the inserted cue, influencing the probability of synaptic updates between pCA1 and dSub units.
Results
We find that our mismatch-dependent learning model accounts for known VTC properties1, including: (i) the distribution of VTCs along the proximodistal axis, (ii) the percentage of VTCs across different cue types, and (iii) hours-long persistence of vector trace. (iv) By enriching CA1 representations, our model further explains additional empirical findings, including object-centered population coding in CA13. (v) VTCs have longer tuning distances after cue removal.
Discussion
Our model suggests that mismatch detection for updating of associative memory suggests mechanistic explanations for findings in the CA1-Sub pathway, and predicts a function for the Sub in coordinating spatial encoding and memory retrieval. Additionally, it describes the distinctive neural coding for novel objects and familiar contexts and their impacts on memory retrieval. Our work constitutes the first dedicated circuit-level model of computation within the Sub and provides a potential framework to extend the standard model of hippocampal function with a Sub component.
Figure 1. Fig. 1 (a) Experimental Procedure. Rats foraged for food while Sub neurons were recorded. Heatmaps show firing rates as a function of the rat's position (adapted from Poulter et al., 2021). (b) Our model has a perceptual pathway (pSub-dSub) and a memory pathway (CA1-dSub). Arrow widths represent connection strength. dSub units update CA1-dSub weights at varying rates, shown by different colors.
Acknowledgements
AB and FW acknowledge funding from the Max-Planck Society. Additionally, we thank Colin Lever at Durham University for insightful discussions, valuable advice, and access to preliminary data.
References
● Poulter, S., Lee, S. A., Dachtler, J., Wills, T. J., & Lever, C. (2021).Vector trace cells in the subiculum of the hippocampal formation.Nature neuroscience,24(2), 266-275.
● Bicanski, A., & Burgess, N. (2018). A neural-level model of spatial memory and imagery.elife,7, e33752.
● Vandrey, B., Duncan, S., & Ainge, J. A. (2021). Object and object‐memory representations across the proximodistal axis of CA1.Hippocampus,31(8), 881-896.
