Distinct Mechanisms of Over-Representation of Landmarks and Rewards in the Hippocampus

Sato, Masaaki; Mizuta, Kotaro; Islam, Tarikul; Kawano, Masako; Sekine, Yasuji; Takekawa, Takashi; Gómez-Domínguez, Daniel; Schmidt, Alexander; Wolf, Fred; Kim, Karam; Yamakawa, Hiroshi; Ohkura, Masamichi; Lee, Min Goo; Fukai, Tomoki; Nakai, Junichi; Hayashi, Yasunori

doi:10.1016/j.celrep.2020.107864

Cited by 61 publications

(95 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although both the bottleneck model and the over-representation model exhibited chunking effects, the over-representation model is particularly consistent with the experimental observation because theta sequences are segmented at salient landmarks and rewards 32 which are over-represented by hippocampal place cells 38,39 . These results demonstrates that LAM provides a unified mechanism for graph-based representations 6,7 and chunking of sequential activities 32 .…”

Section: Chunked Sequential Activities In Asymmetric Lamsupporting

confidence: 76%

“…We found that both local bottlenecks and over-representations induce the chunking of sequential activities in asymmetric LAM. The over-representation model is particularly interesting because it accounts for the role of salient landmarks and rewards which are overrepresented by place cells 38,39 . We may be able to apply a ring-shape structure with two overrepresentations for modeling typical experiments in which animals run back and forth on a 1-D track to get rewards at both ends, considering that many place cells are directionselective in such experimental setting 47 .…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Associative memory networks for graph-based abstraction

Haga

Fukai

2020

Preprint

Self Cite

View full text Add to dashboard Cite

Our cognition relies on the ability of the brain to segment hierarchically structured events on multiple scales. Recent evidence suggests that the brain performs this event segmentation based on the structure of state-transition graphs behind sequential experiences. However, the underlying circuit mechanisms are only poorly understood. In this paper, we propose an extended attractor network model for the graph-based hierarchical computation, called as Laplacian associative memory. This model generates multiscale representations for communities (clusters) of associative links between memory items, and the scale is regulated by heterogenous modulation of inhibitory circuits. We analytically and numerically show that these representations correspond to graph Laplacian eigenvectors, a popular method for graph segmentation and dimensionality reduction. Finally, we demonstrate that our model with asymmetricity exhibits chunking resembling to hippocampal theta sequences. Our model connects graph theory and the attractor dynamics to provide a biologically plausible mechanism for abstraction in the brain.

show abstract

Section: Chunked Sequential Activities In Asymmetric Lamsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Associative memory networks for graph-based abstraction

Haga

Fukai

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…By conducting a cell‐by‐cell comparison of maps imaged in adjacent sessions, we found that hippocampal map stability is tightly regulated in a salience‐dependent, location‐specific manner (Figure 2). Before reward rearrangement, place‐field stability of the reward location and the landmark location was significantly higher than that of non‐salient locations (Figure 2a,d; Sato et al, 2020). Reward rearrangement triggered a significant reduction in place‐field stability of the previous reward location and non‐salient locations in early phase re‐training (Figure 2b,d).…”

Section: Main Bodymentioning

confidence: 92%

“…It is well‐established that locations associated with behaviorally relevant salient features, such as reward, safety, and local cues, are over‐represented by a disproportionately large number of place cells (PCs) in the hippocampus (Bourboulou et al, 2019; Dupret, O'Neill, Pleydell‐Bouverie, & Csicsvari, 2010; Gauthier & Tank, 2018; Hetherington & Shapiro, 1997; Hollup, Molden, Donnett, Moser, & Moser, 2001; O'Keefe & Conway, 1978; Sato et al, 2020; Wiener, Paul, & Eichenbaum, 1989; Zaremba et al, 2017). Recently, we demonstrated that de novo establishment of these disproportionate maps involves the selective stabilization of PCs that encode salient locations following their conversion from non‐PCs (Sato et al, 2020). However, the cellular dynamics underlying the plasticity of pre‐established maps remained unknown.…”

Section: Main Bodymentioning

confidence: 99%

“…Next, to elucidate the cellular mechanisms underlying the map plasticity, we analyzed functional transitions of individual cells between consecutive sessions (Figures 3,4,5, S2, and S3; Sato et al, 2020). In this analysis, we first identified a population of common cells that belonged to the cell category of interest in the reference session of the two sessions compared and then tracked the position of the place field of each cell in the other session (see Detailed Methods and figure legends).…”

Section: Main Bodymentioning

confidence: 99%

See 1 more Smart Citation

Multiple coordinated cellular dynamics mediate CA1 map plasticity

et al. 2021

Self Cite

View full text Add to dashboard Cite

In the hippocampus, spatial and nonspatial information are jointly represented as a neural map in which locations associated with salient features are over‐represented by increased densities of relevant place cells. Although we recently demonstrated that experience‐dependent establishment of these disproportionate maps is governed by selective stabilization of salient place cells following their conversion from non‐place cells, the underlying mechanism for pre‐established map reorganization remained to be understood. To this end, we investigated the changes in CA1 functional cellular maps imaged using two‐photon calcium imaging in mice performing a reward‐rearrangement task in virtual reality. Mice were pre‐trained on a virtual linear track with a visual landmark and a reward in two distinct locations. Then, they were re‐trained on the same track with the exception that the location of reward was shifted to match the landmark location. We found that, in contrast to de novo map formation, robust map reorganization occurred through parallel coordination of new place field formation, lateral shifting of existing place fields, and selective stabilization of place fields encoding salient locations. Our findings demonstrate that intricate interplay between multiple forms of cellular dynamics enables rapid updating of information stored in hippocampal maps.

show abstract

View cells in the hippocampus and prefrontal cortex of macaques during virtual navigation

et al. 2023

View full text Add to dashboard Cite

Cells selectively activated by a particular view of an environment have been found in the primate hippocampus (HPC). Whether view cells are present in other brain areas, and how view selectivity interacts with other variables such as object features and place remain unclear. Here, we explore these issues by recording the responses of neurons in the HPC and the lateral prefrontal cortex (LPFC) of rhesus macaques performing a task in which they learn new context‐object associations while navigating a virtual environment using a joystick. We measured neuronal responses at different locations in a virtual maze where animals freely directed gaze to different regions of the visual scenes. We show that specific views containing task relevant objects selectively activated a proportion of HPC units, and an even higher proportion of LPFC units. Place selectivity was scarce and generally dependent on view. Many view cells were not affected by changing the object color or the context cue, two task relevant features. However, a small proportion of view cells showed selectivity for these two features. Our results show that during navigation in a virtual environment with complex and dynamic visual stimuli, view cells are found in both the HPC and the LPFC. View cells may have developed as a multiarea specialization in diurnal primates to encode the complexities and layouts of the environment through gaze exploration which ultimately enables building cognitive maps of space that guide navigation.

show abstract

Distinct Mechanisms of Over-Representation of Landmarks and Rewards in the Hippocampus

Abstract: Highlights d CA1 over-representation of reward and landmark emerge with distinct time courses d These cells form stable singularities during experiencedependent map consolidation d The over-representation of landmark but not reward is dependent on Shank2

Cited by 61 publications

References 58 publications

Associative memory networks for graph-based abstraction

Associative memory networks for graph-based abstraction

Multiple coordinated cellular dynamics mediate CA1 map plasticity

View cells in the hippocampus and prefrontal cortex of macaques during virtual navigation

Contact Info

Product

Resources

About