Spatially selective reward site responses in tonically active neurons of the nucleus accumbens in behaving rats.

To study how hippocampal output signals conveying spatial and other contextual information might be integrated in the nucleus accumbens, tonically active accumbens neurons were recorded in three unrestrained rats as they performed spatial orientation tasks on an elevated round rotatable platform with four identical reward boxes symmetrically placed around the edge. The partially water-deprived rats were required to shuttle either between the pair of reward boxes indicated by beacon cues (lights in the boxes) or between the pair of boxes occupying particular locations in relation to environmental landmark cues. In 43/82 neurons, behaviorally correlated phasic modulations in discharge activity occurred, primarily prior to or after water was provided at the reward boxes. Twenty-two had inhibitory modulation, 12 excitatory, and nine were mixed excitatory and inhibitory. Although tonically active neurons (TANs) have rarely been reported in the rodent, the inhibitory and mixed responses correspond to previously reports in the macaque accumbens of tonically active neurons with activity correlated with reward delivery and, following conditioning, to sensory stimuli associated with rewards. Eighteen of the 43 tonically active accumbens neurons showed spatial selectivity, i.e., behaviorally correlated increases or decreases in firing rate were of different magnitudes at the respective reward boxes. This is the first demonstration that the configuration of environmental sensory cues associated with reward sites are also an effective stimulus for these neurons and that different neurons are selective for different places. These results are consistent with a role for the nucleus accumbens in the initiation of goal-directed displacement behaviors.

Position sensitivity in phasically discharging nucleus accumbens neurons of rats alternating between tasks requiring complementary types of spatial cues.

To determine how hippocampal location-selective discharges might influence downstream structures for navigation, nucleus accumbens neurons were recorded in rats alternating between two tasks guided respectively by lit cues in the maze or by extramaze room cues. Of 144 phasically active neurons, 80 showed significant behavioral correlates including displacements, immobility prior to, or after reward delivery, as well as turning, similar to previous reports. Nine neurons were position-selective, 22 were sensitive to task and platform changes and 40 others were both. Although the accumbens neurons showed the same behavioral correlate in two or four functionally equivalent locations, these responses were stronger at some of these places, evidence for position sensitivity. To test whether position responses were selective for room versus platform cues, the experimental platform was rotated while the rat performed each of the two tasks. This revealed responses to changes in position relative to both platform and room cues, despite the fact that previous studies had shown that place responses of hippocampal neurons recorded in the same task are anchored to room cues only. After these manipulations and shifts between the two tasks, the responses varied among simultaneously recorded neurons, and even in single neurons in alternating visits to reward sites. Again this contrasts with the uniformity of place responses of hippocampal neurons recorded in this same task. Thus accumbens position responses may derive from hippocampal inputs, while responses to context changes are more likely to derive from other signals or intrinsic processing. Considering the accumbens as a limbic-motor interface, we conclude that position-modulated behavioral responses in the accumbens may be intermediate between the allocentric reference frame of position-selective discharges in the hippocampus and the egocentric coding required to organize movement control. The conflicting responses among simultaneously recorded neurons could reflect competition processes serving as substrates for action selection and learning.

Animat navigation using a cognitive graph.

This article describes a computational model of the hippocampus that makes it possible for a simulated rat to navigate in a continuous environment containing obstacles. This model views the hippocampus as a "cognitive graph", that is, a hetero-associative network that learns temporal sequences of visited places and stores a topological representation of the environment. Calling upon place cells, head direction cells, and "goal cells", it suggests a biologically plausible way of exploiting such a spatial representation for navigation that does not require complicated graph-search algorithms. Moreover, it permits "latent learning" during exploration, that is, the building of a spatial representation without the need of any reinforcement. When the rat occasionally discovers some rewarding place it may wish to rejoin subsequently, it simply records within its cognitive graph, through a series of goal and sub-goal cells, the direction in which to move from any given start place. Accordingly, the model implements a simple "place-recognition-triggered response" navigation strategy. Two implementations of place cell management are studied in parallel. The first one associates place cells with place fields that are given a priori and that are uniformly distributed in the environment. The second one dynamically recruits place cells as exploration proceeds and adjusts the density of such cells to the local complexity of the environment. Both implementations lead to identical results. The article ends with a few predictions about results to be expected in experiments involving simultaneous recordings of multiple cells in the rat hippocampus.

Hippocampal neuronal position selectivity remains fixed to room cues only in rats alternating between place navigation and beacon approach tasks.

To study the relationship between brain representations and behaviour, we recorded hippocampal neuronal activity in rats repeatedly alternating between two different tasks on a circular platform with four reward boxes along the edge. In the beacon approach task, rewards were provided only at the pair of diametrically opposite boxes that was illuminated. In the place navigation task, rewards were available only at the boxes positioned near the north-east and south-west corners of the room. Performance levels were high and rats rapidly reoriented to changes in lamp cues in the beacon approach task. Neuropsychological studies show that rats with hippocampal lesions readily employ beacon approach strategies, while place navigation is severely impaired. Previous studies suggested that the neurons might change their behavioural correlates as the rat performed the respective tasks. However, of 34 hippocampal 'place cells' recorded, all showed position selectivity fixed with respect to room cues, even in the beacon approach task where coding the position of the rat in the room was of no use for locating rewards. Whether or not hippocampal signals are actually employed for ongoing behaviour would then be decided by structures downstream from the hippocampus. If this is the case, then the 'counterproductive' room referred place-related discharges in the beacon approach task would be a background representation. This would provide support for proposals of multiple memory systems underlying different types of information processing and contrasts with the popular notion that local neuronal activity levels are selectively increased to the degree that the brain region is required for the ongoing function.

Plasticity of directional place fields in a model of rodent CA3.

We propose a computational model of the CA3 region of the rat hippocampus that is able to reproduce the available experimental data concerning the dependence of directional selectivity of the place cell discharge on the environment and on the spatial task. The main feature of our model is a continuous, unsupervised Hebbian learning dynamics of recurrent connections, which is driven by the neuronal activities imposed upon the network by the environment-dependent external input. In our simulations, the environment and the movements of the rat are chosen to mimic those commonly observed in neurophysiological experiments. The environment is represented as local views that depend on both the position and the heading direction of the rat. We hypothesize that place cells are intrinsically directional, that is, they respond to local views. We show that the synaptic dynamics in the recurrent neural network rapidly modify the discharge correlates of the place cells: Cells tend to become omnidirectional place cells in open fields, while their directionality tends to get stronger in radial-arm mazes. We also find that the synaptic learning mechanisms account for other properties of place cell activity, such as an increase in the place cell peak firing rates as well as clustering of place fields during exploration. Our model makes several experimental predictions that can be tested using current techniques.

Biologically based artificial navigation systems: review and prospects.

Diverse theories of animal navigation aim at explaining how to determine and maintain a course from one place to another in the environment, although each presents a particular perspective with its own terminologies. These vocabularies sometimes overlap, but unfortunately with different meanings. This paper attempts to define precisely the existing concepts and terminologies, so as to describe comprehensively the different theories and models within the same unifying framework. We present navigation strategies within a four-level hierarchical framework based upon levels of complexity of required processing (Guidance, Place recognition-triggered Response, Topological navigation, Metric navigation). This classification is based upon what information is perceived, represented and processed. It contrasts with common distinctions based upon the availability of certain sensors or cues and rather stresses the information structure and content of central processors. We then review computational models of animal navigation, i.e. of animats. These are introduced along with the underlying conceptual basis in biological data drawn from behavioral and physiological experiments, with emphasis on theories of "spatial cognitive maps". The goal is to aid in deriving algorithms based upon insights into these processes, algorithms that can be useful both for psychobiologists and roboticists. The main observation is, however, that despite the fact that all reviewed models claim to have biological inspiration and that some of them explicitly use "Cognitive Map"-like mechanisms, they correspond to different levels of our proposed hierarchy and that none of them exhibits the main capabilities of real "Cognitive Maps"--in Tolman's sense--that is, a robust capacity for detour and shortcut behaviors.