scholarly journals Replays of spatial memories suppress topological fluctuations in cognitive map

2019 ◽  
Vol 3 (3) ◽  
pp. 707-724 ◽  
Author(s):  
Andrey Babichev ◽  
Dmitriy Morozov ◽  
Yuri Dabaghian
Keyword(s):  
Computational Model ◽  
Place Cells ◽  
Cognitive Map ◽  
Ambient Space ◽  
Topological Map ◽  
New Information ◽  
Representation Of Space ◽  
Spatial Memories ◽  
Hippocampal Network ◽  
Topological Fluctuations

The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an internalized representation of the ambient space—a cognitive map. These cells do not only exhibit location-specific spiking during navigation, but also may rapidly replay the navigated routs through endogenous dynamics of the hippocampal network. Physiologically, such reactivations are viewed as manifestations of “memory replays” that help to learn new information and to consolidate previously acquired memories by reinforcing synapses in the parahippocampal networks. Below we propose a computational model of these processes that allows assessing the effect of replays on acquiring a robust topological map of the environment and demonstrate that replays may play a key role in stabilizing the hippocampal representation of space.

scholarly journals The hippocampus as a predictive map

2016 ◽  
Author(s):  
Kimberly L. Stachenfeld ◽  
Matthew M. Botvinick ◽  
Samuel J. Gershman
Keyword(s):  
Spatial Representation ◽  
Predictive Coding ◽  
Place Cells ◽  
Cognitive Map ◽  
Basis Set ◽  
Cell Responses ◽  
Future Reward ◽  
Representation Of Space ◽  
Predictive Map ◽  
Low Dimensional

ABSTRACTA cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity, and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. Furthermore, we argue that entorhinal grid cells encode a low-dimensional basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.

scholarly journals Dissociation of exteroceptive and idiothetic orientation cues⋮ effect on hippocampal place cells and place navigation

1997 ◽  
Vol 352 (1360) ◽  
pp. 1515-1524 ◽  
Author(s):  
J. Bures ◽  
A. A. Fenton ◽  
Yu. Kaminsky ◽  
J. Rossier ◽  
B. Sacchetti ◽  
...  
Keyword(s):  
Spatial Cognition ◽  
Reference Frames ◽  
Target Location ◽  
Place Cells ◽  
Related Information ◽  
Place Navigation ◽  
Preference Task ◽  
Spatial Memories ◽  
Place Avoidance ◽  
Orientation Cues

Navigation by means of cognitive maps appears to require the hippocampus; hippocampal place cells (PCs) appear to store spatial memories because their discharge is confined to cell–specific places called firing fields (FFs). Experiments with rats manipulated idiothetic and landmark–related information to understand the relationship between PC activity and spatial cognition. Rotating a circular arena in the light caused a discrepancy between these cues. This discrepancy caused most FFs to disappear in both the arena and room reference frames. However, FFs persisted in the rotating arena frame when the discrepancy was reduced by darkness or by a card in the arena. The discrepancy was increased by ’field clamping’the rat in a room–defined FF location by rotations that countered its locomotion. Most FFs dissipated and reappeared an hour or more after the clamp. Place–avoidance experiments showed that navigation uses independent idiothetic and exteroceptive memories. Rats learned to avoid the unmarked footshock region within a circular arena. When acquired on the stable arena in the light, the location of the punishment was learned by using both room and idiothetic cues; extinction in the dark transferred to the following session in the light. If, however, extinction occurred during rotation, only the arena–frame avoidance was extinguished in darkness; the room–defined location was avoided when the lights were turned back on. Idiothetic memory of room–defined avoidance was not formed during rotation in light; regardless of rotation, there was no avoidance when the lights were turned off, but room–frame avoidance reappeared when the lights were turned back on. The place–preference task rewarded visits to an allocentric target location with a randomly dispersed pellet. The resulting behaviour alternated between random pellet searching and target–directed navigation, making it possible to examine PC correlates of these two classes of spatial behaviour. The independence of idiothetic and exteroceptive spatial memories and the disruption of PC firing during rotation suggest that PCs may not be necessary for spatial cognition; this idea can be tested by recordings during the place–avoidance and preference tasks.

scholarly journals A general model of hippocampal and dorsal striatal learning and decision making

2020 ◽  
Vol 117 (49) ◽  
pp. 31427-31437
Author(s):  
Jesse P. Geerts ◽  
Fabian Chersi ◽  
Kimberly L. Stachenfeld ◽  
Neil Burgess
Keyword(s):  
Decision Making ◽  
Reference Frame ◽  
Place Cells ◽  
Cognitive Map ◽  
Relational Structure ◽  
Place Learning ◽  
Response Learning ◽  
Adaptive Combination ◽  
Stimulus Response ◽  
Model Free

Humans and other animals use multiple strategies for making decisions. Reinforcement-learning theory distinguishes between stimulus–response (model-free; MF) learning and deliberative (model-based; MB) planning. The spatial-navigation literature presents a parallel dichotomy between navigation strategies. In “response learning,” associated with the dorsolateral striatum (DLS), decisions are anchored to an egocentric reference frame. In “place learning,” associated with the hippocampus, decisions are anchored to an allocentric reference frame. Emerging evidence suggests that the contribution of hippocampus to place learning may also underlie its contribution to MB learning by representing relational structure in a cognitive map. Here, we introduce a computational model in which hippocampus subserves place and MB learning by learning a “successor representation” of relational structure between states; DLS implements model-free response learning by learning associations between actions and egocentric representations of landmarks; and action values from either system are weighted by the reliability of its predictions. We show that this model reproduces a range of seemingly disparate behavioral findings in spatial and nonspatial decision tasks and explains the effects of lesions to DLS and hippocampus on these tasks. Furthermore, modeling place cells as driven by boundaries explains the observation that, unlike navigation guided by landmarks, navigation guided by boundaries is robust to “blocking” by prior state–reward associations due to learned associations between place cells. Our model, originally shaped by detailed constraints in the spatial literature, successfully characterizes the hippocampal–striatal system as a general system for decision making via adaptive combination of stimulus–response learning and the use of a cognitive map.

Cognitive Map Formation Through Sequence Encoding by Theta Phase Precession

2004 ◽  
Vol 16 (12) ◽  
pp. 2665-2697 ◽  
Author(s):  
Hiroaki Wagatsuma ◽  
Yoko Yamaguchi
Keyword(s):  
Field Potential ◽  
Computer Experiments ◽  
Cognitive Map ◽  
Phase Precession ◽  
Spatial Environment ◽  
Hippocampal Network ◽  
Theta Phase ◽  
Space Coding ◽  
Temporal Sequences ◽  
Theta Phase Precession

The rodent hippocampus has been thought to represent the spatial environment as a cognitive map. The associative connections in the hippocampus imply that a neural entity represents the map as a geometrical network of hippocampal cells in terms of a chart. According to recent experimental observations, the cells fire successively relative to the theta oscillation of the local field potential, called theta phase precession, when the animal is running. This observation suggests the learning of temporal sequences with asymmetric connections in the hippocampus, but it also gives rather inconsistent implications on the formation of the chart that should consist of symmetric connections for space coding. In this study, we hypothesize that the chart is generated with theta phase coding through the integration of asymmetric connections. Our computer experiments use a hippocampal network model to demonstrate that a geometrical network is formed through running experiences in a few minutes. Asymmetric connections are found to remain and distribute heterogeneously in the network. The obtained network exhibits the spatial localization of activities at each instance as the chart does and their propagation that represents behavioral motions with multidirectional properties. We conclude that theta phase precession and the Hebbian rule with a time delay can provide the neural principles for learning the cognitive map.

scholarly journals Recalibration of path integration in hippocampal place cells

2018 ◽  
Author(s):  
Ravikrishnan P. Jayakumar ◽  
Manu S. Madhav ◽  
Francesco Savelli ◽  
Hugh T. Blair ◽  
Noah J. Cowan ◽  
...  
Keyword(s):  
Path Integration ◽  
Gain Factor ◽  
Place Cells ◽  
Cognitive Map ◽  
Mammalian Brain ◽  
Positional Error ◽  
Visual Landmarks ◽  
Augmented Reality System ◽  
Behavioral Evidence ◽  
Integration Gain

SummaryHippocampal place cells are spatially tuned neurons that serve as elements of a “cognitive map” in the mammalian brain1. To detect the animal’s location, place cells are thought to rely upon two interacting mechanisms: sensing the animal’s position relative to familiar landmarks2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations4–7. The latter mechanism, known as path integration, requires a finely tuned gain factor that relates the animal’s self-movement to the updating of position on the internal cognitive map, with external landmarks necessary to correct positional error that eventually accumulates8,9. Path-integration-based models of hippocampal place cells and entorhinal grid cells treat the path integration gain as a constant9–14, but behavioral evidence in humans suggests that the gain is modifiable15. Here we show physiological evidence from hippocampal place cells that the path integration gain is indeed a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In a novel, augmented reality system, visual landmarks were moved in proportion to the animal’s movement on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path integration gain, as estimated from the place cells after the landmarks were extinguished. We propose that this rapid plasticity keeps the positional update in register with the animal’s movement in the external world over behavioral timescales (mean 50 laps over 35 minutes). These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path integration system, as has been previously shown4,8,16–19, but also rapidly fine-tune the integration computation itself.

scholarly journals Preexisting hippocampal network dynamics constrain optogenetically induced place fields

2019 ◽  
Author(s):  
Sam McKenzie ◽  
Roman Huszár ◽  
Daniel F. English ◽  
Kanghwan Kim ◽  
Euisik Yoon ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Inhibitory Interneuron ◽  
Neuronal Circuits ◽  
Place Field ◽  
Large Reservoir ◽  
New Information ◽  
Place Fields ◽  
Hippocampal Network ◽  
Fundamental Tension ◽  
Existing Structure

SummaryNeuronal circuits face a fundamental tension between maintaining existing structure and changing to accommodate new information. Memory models often emphasize the need to encode novel patterns of neural activity imposed by “bottom-up” sensory drive. In such models, learning is achieved through synaptic alterations, a process which potentially interferes with previously stored knowledge 1-3. Alternatively, neuronal circuits generate and maintain a preconfigured stable dynamic, sometimes referred to as an attractor, manifold, or schema 4-7, with a large reservoir of patterns available for matching with novel experiences 8-13. Here, we show that incorporation of arbitrary signals is constrained by pre-existing circuit dynamics. We optogenetically stimulated small groups of hippocampal neurons as mice traversed a chosen segment of a linear track, mimicking the emergence of place fields 1,14,15, while simultaneously recording the activity of stimulated and non-stimulated neighboring cells. Stimulation of principal neurons in CA1, but less so CA3 or the dentate gyrus, induced persistent place field remapping. Novel place fields emerged in both stimulated and non-stimulated neurons, which could be predicted from sporadic firing in the new place field location and the temporal relationship to peer neurons prior to the optogenetic perturbation. Circuit modification was reflected by altered spike transmission between connected pyramidal cell – inhibitory interneuron pairs, which persisted during post-experience sleep. We hypothesize that optogenetic perturbation unmasked sub-threshold, pre-existing place fields16,17. Plasticity in recurrent/lateral inhibition may drive learning through rapid exploration of existing states.

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