Periodic Reporting for period 4 - NeurogenesisCode (Deciphering the role of adult neurogenesis in hippocampal memory codes by optically imaging neuronal activity in freely behaving mice)
Reporting period: 2019-11-01 to 2020-10-31
The hippocampus is important for memory of place and events. It is also one of the few areas in the adult mammalian brain that exhibits neurogenesis, the continuous generation of new neurons. Much evidence indicates that adult neurogenesis contributes to hippocampal-dependent cognition, but the nature of this contribution remains elusive. Moreover it has remained unclear to what extent hippocampal neural code that underlie spatial memory are stable over long periods of time and to what extent ongoing neurogenesis affect the stability of such codes. The study of such coding dynamics requires longitudinal recordings of neuronal ensembles over periods of weeks, since this is the timescale on which new hippocampal neurons mature. In this project we used and further developed optical recording of Ca2+ dynamics from hundreds the same genetically defined neurons in the hippocampus of freely behaving mice over periods of multiple weeks. We established a probabilistic method (CellReg) for the automated identification of the same neurons (cell registration) across multiple imaging sessions (Scheituch et al, Cell Reports 2017). We have found that hippocampal ensemble dynamics time-stamp experienced events via unique patterns of neuronal activity for specific days, suggesting a role for representational drift in forming a mental timeline in which experiences could be mnemonically associated or dissociated based on their temporal proximity (Rubin et al, eLife 2015). By tracking the activity of hippocampal ensembles across a time span of minutes to weeks, we discovered that multiple distinct representations of the same spatial context can stably coexist in the mouse hippocampus, suggesting that a memory of a given context could be associated with multiple representations, rather than just one (Sheintuch et al, Current Biology 2020). We have further revealed that different aspects of neural code stability are differentially governed by time and experience, and that these effects differ across brain areas that support spatial memory. With respect to the effects of ongoing neurogenesis in the dentate gyrus on downstream CA1 codes, we have found, unexpectedly, that promoting neurogenesis in the dentate gyrus (i.e. increasing circuit rewiring) does not increase representational drift in CA1, but rather contributes to a more informative and stable place code. By conducting large-scale recordings of neuronal activity, we developed a novel approach to studying and interpreting neuronal activity data (Rubin et al, Nature Communications 2019). Using this approach, we showed that the internal structure of neuronal activity itself can be used to reconstruct neuronal representations and discover new encoded variables hidden within a neural code. This approach offers a new means to quantifying the quality and stability of the neural code, with minimal a-priori assumptions, and irrespective of the identities of the neurons that participate in the population activity or of the variables they encode. Overall, our work promotes our understanding of how the hippocampus supports long-term memory, by revealing basic mechanisms and dynamics of it neural code.
Much of the current ERC project relies on optical imaging in freely behaving mice, and specifically on the ability to chronically record large populations of the same neurons and longitudinally analyze their coding properties. This technological aspect is important to all aims of the ERC project. Therefore, we decided to further develop and validate our own algorithms for tracking the same neurons across days and weeks. This findings and technology from this work were recently published (Sheintuch et al, Cell Reports 2017), and presented at the Society for Neuroscience (SfN) Annual meeting. Summary of the project: Ca2+ imaging techniques permit time-lapse recordings of neuronal activity from large populations over weeks. However, without identifying the same neurons across imaging sessions (cell registration), longitudinal analysis of the neural code is restricted to population-level statistics. Accurate cell registration becomes challenging with increased numbers of cells, sessions, and inter-session intervals. Current cell registration practices, whether manual or automatic, do not quantitatively evaluate registration accuracy, possibly leading to data misinterpretation. We developed a probabilistic method that automatically registers cells across multiple sessions and estimates the registration confidence for each registered cell. Using large-scale Ca2+ imaging data recorded over weeks from the hippocampus and cortex of freely behaving mice, we show that our method performs more accurate registration than previously used routines, yielding estimated error rates <5%, and that the registration is scalable for many sessions. Thus, our method allows reliable longitudinal analysis of the same neurons over long time periods.
In another project (Rubin et al, eLife 2015) we tested our hypothesis that ongoing changes in the cellular composition and firing patterns of hippocampal ensembles over timescales of days uniquely timestamp experienced episodes in long-term memory. We performed time-lapse imaging of Ca2+ dynamics in large populations of hippocampal neurons in freely behaving mice to record hippocampal neural coding of episodes that occurred in different contexts and at different times over the course of two weeks. Our experiments revealed that CA1 neuronal dynamics carried temporal information via ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred, whereas temporally remote episodes had distinct timestamps, even if occurred within the same spatial context. Based on these results, we propose that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance.
In another project (Rubin et al, eLife 2015) we tested our hypothesis that ongoing changes in the cellular composition and firing patterns of hippocampal ensembles over timescales of days uniquely timestamp experienced episodes in long-term memory. We performed time-lapse imaging of Ca2+ dynamics in large populations of hippocampal neurons in freely behaving mice to record hippocampal neural coding of episodes that occurred in different contexts and at different times over the course of two weeks. Our experiments revealed that CA1 neuronal dynamics carried temporal information via ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred, whereas temporally remote episodes had distinct timestamps, even if occurred within the same spatial context. Based on these results, we propose that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance.
To understand the function of adult neurogenesis we would like to reveal the changes that occur in the coding properties of dentate gyrus neurons throughout their development, and the changes that these neurons impose on neural codes generated by the hippocampus. We will do this using a combination of novel optical imaging and genetic targeting techniques for reading out and manipulating the activity of newborn neurons in the hippocampus.