Beyond the Cognitive Map: From Place Cells to Episodic Memory. A. David Redish

2000 ◽  
Vol 75 (4) ◽  
pp. 491-492
Author(s):  
Tom V. Smulders ◽  
Robert E. Hampson
Keyword(s):  
Episodic Memory ◽  
Place Cells ◽  
Cognitive Map

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.

Composition and replay of mnemonic sequences: The contributions of REM and slow-wave sleep to episodic memory

2013 ◽  
Vol 36 (6) ◽  
pp. 610-611 ◽  
Author(s):  
Sen Cheng ◽  
Markus Werning
Keyword(s):  
Episodic Memory ◽  
Eye Movement ◽  
Slow Wave ◽  
Rem Sleep ◽  
Neural Activity ◽  
Slow Wave Sleep ◽  
Place Cells ◽  
Object Representations ◽  
Episodic Memories ◽  
Gamma Band Oscillations

AbstractWe propose that rapid eye movement (REM) and slow-wave sleep contribute differently to the formation of episodic memories. REM sleep is important for building up invariant object representations that eventually recur to gamma-band oscillations in the neocortex. In contrast, slow-wave sleep is more directly involved in the consolidation of episodic memories through replay of sequential neural activity in hippocampal place cells.

scholarly journals Hippocampal place cells, context, and episodic memory

Hippocampus ◽  
2006 ◽  
Vol 16 (9) ◽  
pp. 716-729 ◽  
Author(s):  
David M. Smith ◽  
Sheri J.Y. Mizumori
Keyword(s):  
Episodic Memory ◽  
Place Cells

scholarly journals Space, time, and episodic memory: The hippocampus is all over the cognitive map

Hippocampus ◽  
2017 ◽  
Vol 28 (9) ◽  
pp. 680-687 ◽  
Author(s):  
Arne D. Ekstrom ◽  
Charan Ranganath
Keyword(s):  
Episodic Memory ◽  
Space Time ◽  
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 Different encoding of reward location in dorsal and ventral hippocampus

2021 ◽  
Author(s):  
Przemyslaw Jarzebowski ◽  
Y. Audrey Hay ◽  
Benjamin F. Grewe ◽  
Ole Paulsen
Keyword(s):  
Calcium Imaging ◽  
Hippocampal Neurons ◽  
Dorsal Hippocampus ◽  
Spatial Navigation ◽  
Ventral Hippocampus ◽  
Place Cells ◽  
Cognitive Map ◽  
Population Activity ◽  
Reward Seeking ◽  
Seeking Behavior

SummaryHippocampal neurons encode a cognitive map for spatial navigation1. When they fire at specific locations in the environment, they are known as place cells2. In the dorsal hippocampus place cells accumulate at current navigational goals, such as learned reward locations3–6. In the intermediate-to-ventral hippocampus (here collectively referred to as ventral hippocampus), neurons fire across larger place fields7–10 and regulate reward- seeking behavior11–16, but little is known about their involvement in reward-directed navigation. Here, we compared the encoding of learned reward locations in the dorsal and ventral hippocampus during spatial navigation. We used calcium imaging with a head- mounted microscope to track the activity of CA1 cells over multiple days during which mice learned different reward locations. In dorsal CA1 (dCA1), the overall number of active place cells increased in anticipation of reward but the recruited cells changed with the reward location. In ventral CA1 (vCA1), the activity of the same cells anticipated the reward locations. Our results support a model in which the dCA1 cognitive map incorporates a changing population of cells to encode reward proximity through increased population activity, while the vCA1 provides a reward-predictive code in the activity of a specific subpopulation of cells. Both of these location-invariant codes persisted over time, and together they provide a dual hippocampal reward-location code, assisting goal- directed navigation17, 18.

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