Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.
Read more about eLife’s peer review process.Editors
- Reviewing EditorLaura ColginUniversity of Texas at Austin, Austin, United States of America
- Senior EditorLaura ColginUniversity of Texas at Austin, Austin, United States of America
Reviewer #1 (Public Review):
Summary:
In this manuscript by Mou and Ji, the authors describe the correlation between firing rates in the ACC with that of CA1 ensembles during observational learning. Their main findings include trajectory selective (observational) responses in ACC, correlations between ACC and CA1 place cells for specific trajectories during observational learning, and correlations between ACC and CA1 place cells that are reactivated during SWRs, specifically during CA1 replays.
Strengths:
The study is well designed, the data presented is very clear and the conclusions are appropriate regarding their results. The study is novel and of high relevance for the understanding of social learning.
Weaknesses:
Lack of physiological characterization of the neurons that could have been included, such as regular firing rates of neurons in different regions (not only constrained to behavioral landmarks) or PSTH during sharp-wave ripples. The first experiment, NMDA blockage, is a bit disconnected from the rest of the results. Perhaps clarifying in the text a bit further that this proves that ACC is necessary for social learning would help.
Reviewer #2 (Public Review):
Summary:
In the manuscript, Xiang Mou and Daoyun JI investigate how ACC neurons activated by observational learning communicate with the hippocampus. They assess this line of communication through a complex behavioral technique, in vivo electrophysiology, pharmacological approaches, and data analytical techniques. Firstly, the authors find that observational performance is dependent on the ACC, and that the ACC possesses neurons that show side selectivity (trajectory-related) in both the observation box when shuttling to reward, and during subsequent maze running, shuttling to the corresponding same side for reward. The side-selective activation appears stronger for correct trials compared to error trials specifically during observation of Demo rats. They compare how the CA1 of the hippocampus encodes these two environments and find that ACC side-selective neurons show a correlation with side-selective CA1 ensembles during maze behavior, water consumption, and sharp-wave ripples.
Strengths:
Overall, the paper provides strong evidence that ACC neurons are activated by observational learning and that this activation seems to be correlated with CA1 activity.
Weaknesses:
Concerns, however, surround the strength of evidence that links ACC and CA1 activity during observational learning. Only weak correlations between the two regions are shown, and it is unclear if the ACC may lead to CA1 activity or vice versa. It is possible that these processes reflect two parallel pathways. Without manipulation of ACC, it is difficult to assess whether ACC activity influences hippocampal replay.
Reviewer #3 (Public Review):
Summary:
Mou and Ji investigated neuro-computational mechanisms behind observational spatial learning in rats and reported several signs of functional coupling between the ACC and CA1 at the single neuron level. Using multi-site tetrode recording, they found that ACC cells encoding a path on a maze were activated while a rat observed another rat took that path. This activation was also correlated with the activation of CA1 cells encoding the same path and facilitated their replay during sharp-wave ripples (SWRs) before the recording rat ran on the maze by itself. These activity patterns were associated with correct path choice during self-running and were absent in control conditions where the recording rat did not learn the correct choice through observations. Based on these findings, the authors argue that ACC cells capture the critical information during observation to organize hippocampal cell activity for subsequent spatial decisions.
Strengths:
The authors used multiple outcome measures to build a strong case for path-specific spike coordination between ACC and CA1 cells. The analyses were conducted carefully, and proper control measures were used to establish the statistical significance of the detected effects. The authors also demonstrated tight correlations between the spike coordination patterns and the successful use of observed information for future decisions.
Weaknesses:
(1) As evidence for the activation of path information in the ACC during observation, the authors showed positive correlations between firing rates during observation and those during self-running. This argument will be solidified if the authors use a decoding approach to demonstrate the activation of path-selective ACC ensemble activity patterns during observation. This approach will also open the door to uncovering how the activation of ACC path representation is related to the moment-to-moment position of the demonstrator rat and whether it is coupled with the timing of SWRs.
(2) The authors argued that the ACC biases the content of awake replay in CA1 during SWRs in the observation period. The reviewer wonders if a similar bias also occurs during SWRs in the self-run period (i.e., water consumption after the correct choice). This analysis will be helpful in testing if the biased replay occurs due to the need to convert observed information into future choices.
(3) Although the authors demonstrated the necessity of the ACC for the task, it still remains to be determined firing coordination between the ACC and CA1 during observation is necessary for the correct path choice during self-runs. Some discussion on this point, along with future direction, would be beneficial for readers.