Hippocampal-Prefrontal Loop during Navigational Learning

Most of our day-to-day activities involve sequences of actions to navigate to a familiar location. To study this navigational learning, we developed a computational system representing a navigating rodent. The animal was assumed to be familiar with the environment and run with minimal hesitation in a sequence of three turns needed to receive a reward. (snapshot) In any of the eight scenarios, six visual landmarks, known as VL, demarcated the path. The reward was placed at VL5, which made only one sequence of three actions correct (right, left and right). Nine consecutive passes through the maze were analyzed where each full run lasted nine seconds. During the first trial, the animal chose the wrong sequence (right-left-left) and did not get a reward. During the second trial, the animal got a reward after biasing the correct sequence (right-left-right). After choosing VL6 over VL5 during the third pass, the rodent was forced to make the correct sequence again to fully learn the path. During passes five through nine, the animal went to the reward every time showing its learning performance without any biased decisions.

Our simulated brain contained many important cortical structures, which are thought to be responsible for the formation, the consolidation, and the retrieval of sequential and navigational memories. Based on recent in vivo data, we propose a microcircuitry that incorporates the prefrontal cortex as a memory consolidator, the hippocampus as a space locator with the subiculum as a decision maker, and the entorhinal cortex as a regulator. More specifically, during computer-simulated rodent multi-T maze navigation, our circuit-level model replicated the dynamics of the mammalian hippocampal-prefrontal loop. It demonstrated short-term memory during a sequential three binary decisions needed to receive a reward. This first spiking model combining the prefrontal cortex and the hippocampus is a step closer to understanding and treating memory degradation seen in Alzheimer’s patients.

In the near future, our virtual environment will become more complex with a childbot walking in a street where visual landmarks are represented by billboards of different colors and patterns. (See videos)