Summary: Researchers have identified two separate memory functions in the hippocampus: one that is responsible for remembering associations and another that predicts future events based on past experiences. Optogenetics was used in the study to isolate and manipulate one memory function without affecting the other. These findings have important implications for treating memory and navigational deficits in conditions such as dementia and Alzheimer’s disease.
The study, conducted by Cornell University, discovered distinct neural codes for these memory functions, providing insight into the underlying mechanisms of dementia and Alzheimer’s. This knowledge can potentially lead to more targeted interventions in the treatment of memory-related issues.
Key Facts:
- The hippocampus plays a role in two types of memory: associative memory and predictive memory based on past experiences.
- Researchers used advanced optogenetic techniques to manipulate one memory function while leaving the other intact in rats.
- These findings have the potential to guide the development of more specific treatments for dementia and Alzheimer’s disease by targeting the disrupted neural mechanism.
Source: Cornell University
For the first time, a study led by Cornell University in rats has distinguished between two functions of memory in the hippocampus: one that remembers associations between events, time, and place, and another that allows for predicting or planning future actions based on past experiences.
This groundbreaking discovery reveals that these two memory tasks, which are both encoded in the hippocampus, can be separated and manipulated. This has significant implications for potential future treatments of memory and learning disabilities associated with dementia and Alzheimer’s disease.
The study, published in Science, utilized advanced optogenetic techniques to disable one type of memory function while preserving the other.
“We discovered that two distinct neural codes support these crucial aspects of memory and cognition, and that these codes can be dissociated using experimental methods,” explained Antonio Fernandez-Ruiz, assistant professor of neurobiology and behavior.
One neural code is responsible for forming associations, such as remembering that apples can be bought at a nearby grocery store. The other code is predictive and allows individuals to use their memory to plan future behaviors. For example, if you usually take the same route to the store but encounter a closed road one day, you can use your internal mental map to predict an alternative route.
Until now, the relationship between these two memory functions and how the hippocampus supports them has remained unknown.
In the study, rats with manipulated hippocampi had to navigate a maze and find a new path every day to receive a reward. With the manipulation, the rats were unable to remember how to find the reward.
In a second experiment, the rats had to learn to associate a specific location in their environment with a reward. Even with impaired predictive abilities, their associative memory remained intact. This demonstrated the ability to separate these two types of memory.
These findings have implications for the treatment of Alzheimer’s disease and other forms of dementia, where patients experience neural degeneration in the hippocampus along with memory and navigation problems.
“By analyzing the type of memory deficits present in a patient, we can try to determine the compromised neuronal mechanism, which will aid in developing more targeted interventions,” said Fernandez-Ruiz.
About this Memory Research News
Author: Becka Bowyer
Source: Cornell University
Contact: Becka Bowyer – Cornell University
Image: The image is credited to Neuroscience News
Original Research: Closed access.
“Associative and predictive hippocampal codes support memory-guided behaviors” by Antonio Fernandez-Ruiz et al. Science
Abstract
Associative and predictive hippocampal codes support memory-guided behaviors
INTRODUCTION
The brain generates models of the environment that are used to guide flexible behaviors. This process requires learning the states of the world (such as specific locations) as well as the transitional relationships between those states (e.g., successive locations along often-traveled trajectories).
The hippocampal cognitive map is believed to be one such internal model, supporting a variety of behaviors, including associative learning, navigational planning, and inference. It remains unknown which facets of hippocampal coding are required for these different behaviors and how they support both associative and predictive memory functions.
RATIONALE
We hypothesize that two modes of hippocampal activity support learning of world states and state transitions, respectively. On one hand, the synchronous coactivity of groups of hippocampal neurons—cell assemblies—may encode features of individual states, forming an associative code.
On the other hand, the ordered activation of these cell assemblies into behaviorally relevant sequences may encode the relational structure between states, forming a predictive code.
Previous research has not been able to dissociate these two dynamic codes or provide evidence of their specific functions.
We leveraged an optogenetic approach to dissociate these two coding schemes, with the goal of disrupting the predictive code (hippocampal sequences) while preserving the associative code (rate coding and coactivity dynamics) in behaving rats. This dissociation allowed us to examine the different memory functions of these two codes.
RESULTS
We used optogenetic manipulation to disrupt the temporal coordination of hippocampal place cell firing as rats navigated specific spatial trajectories in a novel maze. This manipulation disrupted properties of the predictive code, such as compressed place cell sequences and anticipatory place field shifts, while preserving global network dynamics and single-cell spatial tuning and rate coding properties.
During sleep after the novel experience, we observed the reactivation of task-related cell assemblies encoding specific maze locations in sharp wave-ripples (SWRs), unaffected by the manipulation.
However, the sequential structure of these reactivated assemblies did not match the order in which they were active during the task, resulting in impaired sequential replay for the manipulated trajectories. This demonstrates a dissociation between assembly reactivation and sequence replay, two phenomena that were previously assumed to be the same.
The same manipulation did not disrupt replay of familiar trajectories, suggesting that precise temporal coordination of place cell firing during learning is crucial for subsequent replay. Computational simulations indicate that distinct Hebbian plasticity mechanisms mediate assembly reactivation and sequence replay.
We tested the functional role of the predictive code by deploying our optogenetic manipulation in two different memory tasks dependent on the hippocampus. Associative learning in a conditioned place preference task was unaffected, indicating that it does not require a predictive map or memory replay. On the other hand, flexible memory-guided navigation in a foraging task was impaired by the manipulation and therefore relies on hippocampal predictive coding.
CONCLUSION
Our findings provide a mechanistic and functional distinction between coactivity and sequence codes in the hippocampus.
Hippocampal cells that respond similarly to behavioral variables are activated together, forming functional assemblies during learning. These assemblies are later reactivated during sleep in SWRs and encode discrete states in the environment, comprising an associative code that is sufficient for certain types of episodic memories. As these assemblies are activated in a specific order during behavior, they create temporally compressed hippocampal sequences and promote Hebbian plasticity.
This process allows the replay of behaviorally relevant sequences during SWRs. Hippocampal sequences therefore encode transitional structures of world states, generating a predictive model alongside the associative code formed by individual assemblies.
This new framework enhances our understanding of how memory associations develop into predictive representations of the world, and helps reconcile previously divergent perspectives on hippocampal function.
