A model of hippocampal circuitry mediating goal-driven navigation in a familiar environment (original) (raw)
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Neural Networks, 2003
We investigated the importance of hippocampal theta oscillations and the significance of phase differences of theta modulation in the cortical regions that are involved in goal-directed spatial navigation. Our models used representations of entorhinal cortex layer III (ECIII), hippocampus and prefrontal cortex (PFC) to guide movements of a virtual rat in a virtual environment. The model encoded representations of the environment through long-term potentiation of excitatory recurrent connections between sequentially spiking place cells in ECIII and CA3. This encoding required buffering of place cell activity, which was achieved by a short-term memory (STM) in EC that was regulated by theta modulation and allowed synchronized reactivation with encoding phases in ECIII and CA3. Inhibition at a specific theta phase deactivated the oldest item in the buffer when new input was presented to a full STM buffer. A 1808 phase difference separated retrieval and encoding in ECIII and CA3, which enabled us to simulate data on theta phase precession of place cells. Retrieval of known paths was elicited in ECIII by input at the retrieval phase from PFC working memory for goal location, requiring strict theta phase relationships with PFC. Known locations adjacent to the virtual rat were retrieved in CA3. Together, input from ECIII and CA3 activated predictive spiking in cells in CA1 for the next desired place on a shortest path to a goal. Consistent with data, place cell activity in CA1 and CA3 showed smaller place fields than in ECIII. q
Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity
Biological Cybernetics, 2000
A computational model of hippocampal activity during spatial cognition and navigation tasks is presented. The spatial representation in our model of the rat hippocampus is built on-line during exploration via two processing streams. An allothetic vision-based representation is built by unsupervised Hebbian learning extracting spatio-temporal properties of the environment from visual input. An idiothetic representation is learned based on internal movement-related information provided by path integration. On the level of the hippocampus, allothetic and idiothetic representations are integrated to yield a stable representation of the environment by a population of localized overlapping CA3-CA1 place fields. The hippocampal spatial representation is used as a basis for goal-oriented spatial behavior. We focus on the neural pathway connecting the hippocampus to the nucleus accumbens. Place cells drive a population of locomotor action neurons in the nucleus accumbens. Reward-based learning is applied to map place cell activity into action cell activity. The ensemble action cell activity provides navigational maps to support spatial behavior. We present experimental results obtained with a mobile Khepera robot.
The ventral hippocampus is involved in multi‐goal obstacle‐rich spatial navigation
Hippocampus, 2018
A large body of evidence shows that the hippocampus is necessary for successful spatial navigation. Various studies have shown anatomical and functional differences between the dorsal (DHC) and ventral (VHC) portions of this structure. The DHC is primarily involved in spatial navigation and contains cells with small place fields. The VHC is primarily involved in context and emotional encoding contains cells with large place fields and receives major projections from the medial prefrontal cortex. In the past, spatial navigation experiments have used relatively simple tasks that may not have required a strong coordination along the dorsoventral hippocampal axis. In this study, we tested the hypothesis that the DHC and VHC may be critical for goal-directed navigation in obstacle-rich environments. We used a learning task in which animals memorize the location of a set of rewarded feeders, and recall these locations in the presence of small or large obstacles. We report that bilateral DHC or VHC inactivation impaired spatial navigation in both large and small obstacle conditions. Importantly, this impairment did not result from a deficit in the spatial memory for the set of feeders (i.e., recognition of the goal locations) because DHC or VHC inactivation did not affect recall performance when there was no obstacle on the maze. We also show that the behavioral performance of the animals was correlated with several measures of maze complexity and that these correlations were significantly affected by inactivation only in the large object condition. These results suggest that as the complexity of the environment increases, both DHC and VHC are required for spatial navigation.
The hippocampo-cortical loop: Spatio-temporal learning and goal-oriented planning in navigation
2013
We present a neural network model where the spatial and temporal components of a task are merged and learned in the hippocampus as chains of associations between sensory events. The prefrontal cortex integrates this information to build a cognitive map representing the environment. The cognitive map can be used after latent learning to select optimal actions to fulfill the goals of the animal. A simulation of the architecture is made and applied to learning and solving tasks that involve both spatial and temporal knowledge. We show how this model can be used to solve the continuous place navigation task, where a rat has to navigate to an unmarked goal and wait for 2 seconds without moving to receive a reward. The results emphasize the role of the hippocampus for both spatial and timing prediction, and the prefrontal cortex in the learning of goals related to the task.
A feed-forward model of spatial and directional selectivity of hippocampal place cells
In recent years a wealth of studies have focused on the role of the Hippocampus in spatial learning and navigation, triggered by the finding of place sensitive cells in this area. These cells have been interpreted as being responsible for coding a representation of space [9, 10]. Even though the term place cell suggests that location is the unique determinant of firing of hippocampal cells, there exist several other factors which influence hippocampal activity.
2014
Background: Despite decades of research on spatial memory, we know surprisingly little about how the brain guides navigation to goals. While some models argue that vectors are represented for navigational guidance, other models postulate that the future path is computed. Although the hippocampal formation has been implicated in processing spatial goal information, it remains unclear whether this region processes pathor vector-related information. Results: We report neuroimaging data collected from subjects navigating London's Soho district; these data reveal that both the path distance and the Euclidean distance to the goal are encoded by the medial temporal lobe during navigation. While activity in the posterior hippocampus was sensitive to the distance along the path, activity in the entorhinal cortex was correlated with the Euclidean distance component of a vector to the goal. During travel periods, posterior hippocampal activity increased as the path to the goal became longer, but at decision points, activity in this region increased as the path to the goal became closer and more direct. Importantly, sensitivity to the distance was abolished in these brain areas when travel was guided by external cues.
A Model for Navigation in Unknown Environments Based on a Reservoir of Hippocampal Sequences
Hippocampal place cell populations are activated in sequences on multiple time scales during active behavior, resting and sleep states, suggesting that these sequences are the genuine dynamical motifs of the hippocampal circuit. Recently, prewired hippocampal place cell sequences have even been reported to correlate to future behaviors, but so far there is no explanation of what could be the computational benefits of such a mapping between intrinsic dynamical structure and external sensory inputs. Here, I propose a computational model in which a set of predefined internal sequences is used as a dynamical reservoir to construct a spatial map of a large unknown maze based on only a small number of salient landmarks. The model is based on a new variant of temporal difference learning and implements a simultaneous localization and mapping algorithm. As a result sequences during intermittent replay periods can be decoded as spatial trajectories and improve navigation performance, which s...
Memory for places: A navigational model in support of Marr's theory of hippocampal function
Hippocampus, 1996
In this paper we describe a model that applies Marr's theory of hippocampal function to the problem of map based navigation. Like many others we attribute a spatial memory function to the hippocampus, but we suggest that the additional functional components required for map based navigation are located elsewhere in the brain. One of the key functional components in this model is an egocentric map of space, located in the neocortex, that is continuously updated using ideothetic (self motion) information. The hippocampus stores snapshots of this egocentric map. The modelled activity pattern of head direction cells is used to set the best egocentric map rotation to match the snapshots stored in the hippocampus, resulting in place cells with a non-directional ring pattern. We describe an evaluation of this model using a mobile robot, and demonstrate that with this model the robot can recognise an environment and nd a hidden goal. This model is discussed in the context of prior experiments that were designed to discover the map based spatial processing of animals. We also predict the results of further experiments.
Hippocampal CA1 activity correlated with the distance to the goal and navigation performance
Hippocampus, 2017
Coding the distance to a future goal is an important function of a neural system supporting navigation. While some evidence indicates the hippocampus increases activity with proximity to the goal, others have found activity to decrease with proximity. To explore goal distance coding in the hippocampus we recorded from CA1 hippocampal place cells in rats as they navigated to learned goals in an event arena with a win-stay lose-shift rule. CA1 activity was positively correlated with the distance - decreasing with proximity to the goal. The stronger the correlation between distance to the goal and CA1 activity, the more successful navigation was in a given task session. Acceleration, but not speed, was also correlated with the distance to the goal. However, the relationship between CA1 activity and navigation performance was independent of variation in acceleration and variation in speed. These results help clarify the situations in which CA1 activity encodes navigationally relevant in...
Solving the detour problem in navigation: a model of prefrontal and hippocampal interactions
Frontiers in Human Neuroscience, 2015
Adapting behavior to accommodate changes in the environment is an important function of the nervous system. A universal problem for motile animals is the discovery that a learned route is blocked and a detour is required. Given the substantial neuroscience research on spatial navigation and decision-making it is surprising that so little is known about how the brain solves the detour problem. Here we review the limited number of relevant functional neuroimaging, single unit recording and lesion studies. We find that while the prefrontal cortex (PFC) consistently responds to detours, the hippocampus does not. Recent evidence suggests the hippocampus tracks information about the future path distance to the goal. Based on this evidence we postulate a conceptual model in which: Lateral PFC provides a prediction error signal about the change in the path, frontopolar and superior PFC support the re-formulation of the route plan as a novel subgoal and the hippocampus simulates the new path. More data will be required to validate this model and understand (1) how the system processes the different options; and (2) deals with situations where a new path becomes available (i.e., shortcuts).