Distributed coding of duration in rodent prefrontal cortex during time reproduction
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Evaluation Summary:
This study investigates the neural underpinnings of the bias property of timing, namely an overestimation for short and underestimation for long intervals, during an interval reproduction task in the medial prefrontal cortex of gerbils. The key novel result is that only neural populations with mixed responses, including ramping activity with linear increasing and slope-changing modulations as a function of reproduced durations, can encode the bias effect. Overall, experiment and data analysis are technically sound, and the conclusions are mostly well supported. However, the interpretation is too broad, and the manuscript would benefit of a more focused framing.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)
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Abstract
As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in nonprimate species. Here, we use time interval reproduction to study rodent behavior and its neural correlates in the context of magnitude estimation. We show that gerbils display primate-like magnitude estimation characteristics in time reproduction. Most prominently their behavioral responses show a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results help unveil the organizing neural principles of time reproduction and perhaps magnitude estimation in general.
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Evaluation Summary:
This study investigates the neural underpinnings of the bias property of timing, namely an overestimation for short and underestimation for long intervals, during an interval reproduction task in the medial prefrontal cortex of gerbils. The key novel result is that only neural populations with mixed responses, including ramping activity with linear increasing and slope-changing modulations as a function of reproduced durations, can encode the bias effect. Overall, experiment and data analysis are technically sound, and the conclusions are mostly well supported. However, the interpretation is too broad, and the manuscript would benefit of a more focused framing.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested …
Evaluation Summary:
This study investigates the neural underpinnings of the bias property of timing, namely an overestimation for short and underestimation for long intervals, during an interval reproduction task in the medial prefrontal cortex of gerbils. The key novel result is that only neural populations with mixed responses, including ramping activity with linear increasing and slope-changing modulations as a function of reproduced durations, can encode the bias effect. Overall, experiment and data analysis are technically sound, and the conclusions are mostly well supported. However, the interpretation is too broad, and the manuscript would benefit of a more focused framing.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
This is an interesting and thoroughly performed study that addresses the crucial problem of how the brain optimally encode time magnitudes to reproduce durations with the bias property of timing. The authors developed task where initially the gerbils measured the duration of a black screen stimulus and then reproduced this interval by walking on a treadmill to obtain a food reward. Seven durations in the range of seconds were randomly sampled and used in the task. The animals' behavior showed the regression effect and the scalar property of timing. Next, the authors recorded from neurons in medial prefrontal cortex (mPFC) during task performance. They found that neural responses could be grouped into different categories based on their time varying profiles of activation, including ramp-type neurons with or …
Reviewer #1 (Public Review):
This is an interesting and thoroughly performed study that addresses the crucial problem of how the brain optimally encode time magnitudes to reproduce durations with the bias property of timing. The authors developed task where initially the gerbils measured the duration of a black screen stimulus and then reproduced this interval by walking on a treadmill to obtain a food reward. Seven durations in the range of seconds were randomly sampled and used in the task. The animals' behavior showed the regression effect and the scalar property of timing. Next, the authors recorded from neurons in medial prefrontal cortex (mPFC) during task performance. They found that neural responses could be grouped into different categories based on their time varying profiles of activation, including ramp-type neurons with or without slope changes as a function of the times duration. Notably, the activity patterns were different at the single cell and population levels between the measurement and reproduction epochs of the task. In contrast, the state-space trajectories showed similar properties between epochs, although temporal scaling was mainly present during reproduction. The time decoding showed that only combinations of ramp-to-threshold and linear increasing neurons could reproduce the regression effect. However, is not evident how this mixing is accomplished.
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Reviewer #2 (Public Review):
Henke and colleagues study the activity of neurons in the prefrontal cortex of Mongolian gerbils while they perform a time interval reproduction task. They provide behavioral evidence that the model animals exhibit features typical of interval timing, including temporal scaling and the regression effect. They first analyzed the activity of individual neurons finding response profiles that have been observed. Critically, the observed profiles include neurons with constant-slope ramping activity (time accumulators) and slope-adjusting neurons. They also show that individual neurons exhibit activity that scales with interval duration. Moreover, they performed population-level analyses and they found neural dynamics that closely resemble previous observations. They went one step forward and classified the …
Reviewer #2 (Public Review):
Henke and colleagues study the activity of neurons in the prefrontal cortex of Mongolian gerbils while they perform a time interval reproduction task. They provide behavioral evidence that the model animals exhibit features typical of interval timing, including temporal scaling and the regression effect. They first analyzed the activity of individual neurons finding response profiles that have been observed. Critically, the observed profiles include neurons with constant-slope ramping activity (time accumulators) and slope-adjusting neurons. They also show that individual neurons exhibit activity that scales with interval duration. Moreover, they performed population-level analyses and they found neural dynamics that closely resemble previous observations. They went one step forward and classified the response patterns of individual neurons, and were able to identify a specific response profile that contributed the most to the most to the regression effect of interval timing.
Well performed phenomenological description of the observed neuronal responses using sound analytical approaches, combined with an appropriate behavioral task that allows to separate time encoding from timed motor execution.
Importantly, the paper provides confirmation of previous observations made using different tasks, model organisms, brain regions, and interval duration ranges. It builds up on previous work and proposes a mechanism that potentially explains the regression effect.
Population-level analysis rely on pseudo-population data, which is a suboptimal situation when we want to study neural population coding and population dynamics. Although this is something to consider, by no means this invalidate the results.
However, the framing of the findings in the broad context of magnitude estimation is not fully supported. The manuscript would largely benefit from a more focused framing, narrowing it to time estimation, rather than magnitude estimation in general.
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Reviewer #3 (Public Review):
Henke and colleagues describe a novel behavioral protocol where Gerbilles are trained to estimate and reproduce time intervals while running on a treadmill in a virtual reality environment. By using this method combined with tetrode-based multiunitary neuronal recordings, authors explored the prefrontal cortex neural activity at the single cell and population levels. The results are consistent with previous examples from the primate and rodent literature, and the main observation indicates that interval magnitudes are represented in the population but not in individual neurons. The main strength of this work is the application of several interesting and well conducted analyses on the neural data. The behavioral model is also very interesting and, in my opinion, has great potential. However, the way the …
Reviewer #3 (Public Review):
Henke and colleagues describe a novel behavioral protocol where Gerbilles are trained to estimate and reproduce time intervals while running on a treadmill in a virtual reality environment. By using this method combined with tetrode-based multiunitary neuronal recordings, authors explored the prefrontal cortex neural activity at the single cell and population levels. The results are consistent with previous examples from the primate and rodent literature, and the main observation indicates that interval magnitudes are represented in the population but not in individual neurons. The main strength of this work is the application of several interesting and well conducted analyses on the neural data. The behavioral model is also very interesting and, in my opinion, has great potential. However, the way the introduction and discussion are presented, makes it difficult to extract the novelty of the results. Furthermore, there are several major concerns that should be addressed to increase the clarity of the study. Specially, some important aspects in the behavioral protocol and performance must be clarified and justified before accepting the interpretations.
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