Tracking animal behavior by video is one of the most common tasks in neuroscience. Previously, we have validated ezTrack, a free, flexible, and easy-touse software for the analysis of animal behavior. ezTrack's Location Tracking Module can be used for the positional analysis of an individual animal and is applicable to a wide range of behavioral tasks. Separately, ezTrack's Freeze Analysis Module is designed for the analysis of defensive freezing behavior. ezTrack supports a range of desirable tools, including options for cropping and masking portions of the field of view, defining regions of interest, producing summary data for specified portions of time, algorithms to remove the influence of electrophysiology cables and other tethers, batch processing of multiple videos, and video down-sampling. Moreover, ezTrack produces a range of interactive plots and visualizations to promote users' confidence in their results. In this protocols paper, we provide step-by-step instructions for the use of ezTrack, from tips for recording behavior to instructions for using the software for video analysis.

Memories are encoded in neural ensembles during learning and stabilized by post-learning reactivation. Integrating recent experiences into existing memories ensures that memories contain the most recently available information, but how neural ensembles accomplish this critical process remains unknown. Here we show that in mice, a strong aversive experience drives the offline ensemble reactivation of not only the recent aversive memory but also a neutral memory formed two days prior, spreading the fear from the recent aversive memory to the previous neutral memory. We find that fear specifically spreads retrospectively, but not prospectively, to neutral memories across days. Consistent with prior studies, we find reactivation of the recent aversive memory ensemble during the offline period following learning. However, a strong aversive experience also increases co-reactivation of the aversive and neutral memory ensembles during the offline period. Finally, inhibiting hippocampal reactivation during this offline period abolishes the spread of fear from the aversive experience to the neutral memory. Taken together, these results demonstrate that strong aversive experience can drive retrospective memory integration through the offline co-reactivation of recent memory ensembles with memory ensembles formed days prior, providing a neural mechanism by which memories can be integrated across days.

Memory-updating is critical in dynamic environments because updating memories with new information promotes versatility. However, little is known about how memories are updated with new information. To study how neuronal ensembles might support memory-updating, we used a hippocampus-dependent spatial reversal task to measure hippocampal ensemble dynamics when mice switched navigational goals. Using Miniscope calcium imaging, we identified neuronal ensembles (co-active neurons) in dorsal CA1 that were spatially tuned and stable across training sessions. When reward locations were moved during a reversal session, a subset of these ensembles decreased their activation strength, correlating with memory-updating. These 'remodeling' ensembles were a result of weakly-connected neurons becoming less co-active with their peers. Middle-aged mice were impaired in reversal learning, and the prevalence of their remodeling ensembles correlated with their memory-updating performance. Therefore, we have identified a mechanism where the hippocampus breaks down ensembles to support memory-updating.

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With the prevalence of age-related cognitive deficits on the rise, it is essential to identify cellular and circuit alterations that contribute to age-related memory impairment. Increased intrinsic neuronal excitability after learning is important for memory consolidation, and changes to this process could underlie memory impairment in old age. Some studies find age-related deficits in hippocampal neuronal excitability that correlate with memory impairment but others do not, possibly due to selective changes only in activated neural ensembles. Thus, we tagged CA1 neurons activated during learning and recorded their intrinsic excitability 5 hours or 7 days post-training. Adult mice exhibited increased neuronal excitability 5 hours after learning, specifically in ensemble (learning-activated) CA1 neurons. As expected, ensemble excitability returned to baseline 7 days post-training. In aged mice, there was no ensemble-specific excitability increase after learning, which was associated with impaired hippocampal memory performance. These results suggest that CA1 may be susceptible to age-related impairments in post-learning ensemble excitability and underscore the need to selectively measure ensemble-specific changes in the brain.