Summary Replay of behavioral sequences in the hippocampus during sharp-wave-ripple-complexes (SWRs) provides a potential mechanism for memory consolidation and the learning of knowledge structures. Current hypotheses imply that replay should straightforwardly reflect recent experience. However, we find these hypotheses to be incompatible with the content of replay on a task with two distinct behavioral sequences (A&B). We observed forward and backward replay of B even when rats had been performing A for >10 minutes. Furthermore, replay of non-local sequence B occurred more often when B was infrequently experienced. Neither forward nor backward sequences preferentially represented highly-experienced trajectories within a session. Additionally, we observed the construction of never-experienced novel-path sequences. These observations challenge the idea that sequence activation during SWRs is a simple replay of recent experience. Instead, replay reflected all physically available trajectories within the environment, suggesting a potential role in active learning and maintenance of the cognitive map.

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The encoding and storage of experience by the hippocampus is essential for the formation of episodic memories and the transformation of individual experiences into semantic structures such as maps and schemas. The rodent hippocampus compresses ongoing experience into repeating theta sequences, but the factors determining the content of theta sequences are not understood. Here we first show that the spatial paths represented by theta sequences in rats extend farther in front of the rat during acceleration and higher running speeds and begin farther behind the rat during deceleration. Second, the length of the path is directly related to the length of the theta cycle and the number of gamma cycles in it. Finally, theta sequences represent the environment in segments or ‘chunks’. These results imply that information encoded in theta sequences is subject to powerful modulation by behavior and task variables. Furthermore, these findings suggest a potential mechanism for the cognitive ‘chunking’ of experience.

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The ubiquity of AI in society means the time is ripe to consider what educated 21st century digital citizens should know about this subject. In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching AI to K-12 students. Inspired by CSTA's national standards for K-12 computing education, the AI for K-12 guidelines will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The AI for K-12 working group is also creating an online resource directory where teachers can find AI- related videos, demos, software, and activity descriptions they can incorporate into their lesson plans. This blue sky talk invites the AI research community to reflect on the big ideas in AI that every K-12 student should know, and how we should communicate with the public about advances in AI and their future impact on society. It is a call to action for more AI researchers to become AI educators, creating resources that help teachers and students understand our work.

We suggest that the hippocampus plays two roles that allow rodents to solve the hidden-platform water maze: self-localization and route replay. When an animal explores an environment such as the water maze, the combination of place fields and correlational (Hebbian) long-term potentiation produces a weight matrix in the CA3 recurrent collaterals such that cells with overlapping place fields are more strongly interconnected than cells with nonoverlapping fields. When combined with global inhibition, this forms an attractor with coherent representations of position as stable states. When biased by local view information, this allows the animal to determine its position relative to the goal when it returns to the environment. We call this self-localization. When an animal traces specific routes within an environment, the weights in the CA3 recurrent collaterals become asymmetric. We show that this stores these routes in the recurrent collaterals. When primed with noise in the absence of sensory input, a coherent representation of position still forms in the CA3 population, but then that representation drifts, retracing a route. We show that these two mechanisms can coexist and form a basis for memory consolidation, explaining the anterograde and limited retrograde amnesia seen following hippocampal lesions.

We present a computational theory of navigation in rodents based on interacting representations of place, head direction, and local view. An associated computer model is able to replicate a variety of behavioral and neurophysiological results from the rodent navigation literature. The theory and model generate predictions that are testable with current technologies. © 1996 Wiley‐Liss, Inc.

We present a conceptual framework for the role of the hippocampus and its afferent and efferent structures in rodent navigation. Our proposal is compatible with the behavioral, neurophysiological, anatomical, and neuropharmacological literature, and suggests a number of practical experiments that could support or refute it. We begin with a review of place cells and how the place code for an environment might be aligned with sensory cues and updated by self‐motion information. The existence of place fields in the dark suggests that location information is maintained by path integration, which requires an internal representation of direction of motion. This leads to a consideration of the organization of the rodent head direction system, and thence into a discussion of the computational structure and anatomical locus of the path integrator. If the place code is used in navigation, there must be a mechanism for selecting an action based on this information. We review evidence that the nucleus accumbens subserves this function. From there, we move to interactions between the hippocampal system and the environment, emphasizing mechanisms for learning novel environments and for aligning the various subsystems upon re‐entry into familiar environments. We conclude with a discussion of the relationship between navigation and declarative memory. Hippocampus 7:15–35, 1997. © 1997 Wiley‐Liss, Inc.