Understanding the neuronal basis of learning and memory is a fundamental problem in neuroscience. A leading theory, the origins of which date back to the beginning of the twentieth century, is that the neural basis for memory resides in engrams (also called memory traces), ensembles of cells that are activated during learning and reactivated during memory retrieval. Recent genetic tools have allowed researchers to visualize and manipulate memory traces in small brain regions; however, the ultimate goal is to analyze memory traces across the entire brain in order to better understand how memories are stored in neural networks and how multiple memories may coexist. In order to do so, methods and technologies need to be developed that allow labeling of engram cells throughout the brain, visualization of these cells, and automated quantification of cells in an anatomically precise manner.
The first of these challenges has been addressed through the development over the past several years of different mouse models that permit the labeling of active cells throughout the brain at multiple time points. One of the most powerful models, the ArcCreERT2 mouse line, uses drug-induced genetic recombination to indelibly label cells throughout the brain in an activity-dependent manner. In this thesis, I present our work utilizing this model to solve the second and third challenges: imaging of brain-wide memory traces and automated quantification of labeled cells, as well as the application of these novel methods to understanding the engram network changes following fear extinction. Intact tissue clearing and imaging is a new and rapidly growing area of focus that holds great promise for enabling the brain-wide visualization of memory traces. We utilized the leading protocols for whole-brain clearing and applied them to the ArcCreERT2 mice. We found that CLARITY and passive clarity technique (PACT) greatly distorted the tissue, and immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO) quenched enhanced yellow fluorescent protein (eYFP) fluorescence and hindered immunolabeling. Alternative clearing solutions, such as tert-Butanol, circumvented these harmful effects, but still did not permit whole-brain immunolabeling. Clear unobstructed brain imaging cocktails and computational analysis (CUBIC) and CUBIC with Reagent 1A produced improved antibody penetration and preserved eYFP fluorescence, but also did not allow for whole-brain memory trace visualization. We developed CUBIC with Reagent-1A*, a modified CUBIC protocol that resulted in eYFP fluorescence preservation and immunolabeling of the immediate early gene (IEG) Arc in deep brain areas; however, optimized memory trace labeling still required tissue slicing into mm-thick tissue sections. Nonetheless, our data show that CUBIC with Reagent-1A* is the ideal method for reproducible clearing and immunolabeling for the visualization of memory traces in mm-thick tissue sections from ArcCreERT2 brains.
Recent developments in brain-wide engram tagging strategies, primarily through the use of transgenic mouse models such as the ArcCreERT2 line, and whole brain imaging strategies, such as CLARITY, CUBIC, and iDISCO, have created the circumstances to, for the first time, be able to visualize throughout the brain neuronal activity that is directly linked to behavior. However, as noted above, quantifying and analyzing these brain-wide memory traces presents its own challenge, and widely applicable, readily accessible solutions to this problem have thus far been limited. Although a handful of freely available programs and suites do exist, such as CellProfiler and ClearMap, these are generally tailored to specific approaches, and in particular, no currently available solution exists for quantifying multi-labeled engram cells imaged in three dimensions along the coronal plane, a relatively common scenario that is sure to become even more prominent as greater adoption of the underlying technologies progresses. Using ImageJ and R, we developed an image analysis pipeline to solve precisely this problem. Our strategy allows for the segmentation of both the encoding and retrieval populations, including identification of the reactivated cells, and registration of segmented cells to an anatomical atlas in order to analyze cell activity in a region- and layer-specific manner.
Post-traumatic stress disorder (PTSD) can develop following a traumatic event and results in heightened, inappropriate fear and anxiety. Approximately 8% of the US population suffers from PTSD, the main treatment for which is repeated exposure to triggering stimuli under controlled conditions. A better understanding of the neural circuits modified during this process would help advance therapeutic treatment for PTSD. We sought to determine the brain-wide neuronal activity changes underlying fear extinction, the best laboratory model of exposure therapy, by using the ArcCreERT2 x eYFP mice and our newly developed brain-wide segmentation and registration pipeline. ArcCreERT2 x eYFP mice were administered a 4-shock contextual fear conditioning (CFC) paradigm followed by either a 10-day extinction protocol or re-exposure to the aversive context without extinction. Following the final exposure session, mice were euthanized, and active cells were quantified throughout the brain using the pipeline. We found that fear learning leads to increased functional connectivity of amygdalar and hypothalamic regions, and extinction leads to a decentralization of the fear memory network and disengages the thalamus and striatal amygdala. Additionally, coordinated reactivation of the basomedial amygdala and secondary somatosensory cortex with frontal association regions are differentially modulated following extinction, and we identified the temporal association area and medial habenula as novel brain regions involved in modulating freezing behavior.
In summary, in this thesis, we have developed a novel engram analysis pipeline and shown its potential for quantifying brain-wide memory traces. This is the first study to analyze brain-wide functional connectivity following fear learning and extinction of a recent fear memory, as well as the first study to analyze fear memory trace reactivation patterns across the brain and relate all three measures to behavioral output. This work both greatly enhances our understanding of the neural underpinnings of fear extinction and provides a toolset for readily exploring the neural underpinnings of other behaviors and types of associative memory.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-xk4q-hz30 |
| Date | January 2021 |
| Creators | Lanio, Marcos |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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