If we live long enough, will our brains one day simply “max out” and run out of room, and if not, why not? Are memories formed and stored differently in the brain as we age? How does the way in which memories are linked over time affect what we remember? What role does sleep play in linking memories across time?
These are some of the captivating—and complex— questions about learning and memory we’re exploring in our lab. We use a multi-level approach integrating molecular, cellular, circuit-level, and behavioral techniques to investigate the dynamic nature of memory. Our primary research themes include memory capacity, temporal memory-linking, and sleep and memory. We’re studying the strategies the brain uses to optimize its capacity for storage; how prior learning influences future behavior; and why emotions may alter memories while we sleep. Building and sharing novel tools and technologies to help answer these and evolving questions in neuroscience is an exciting part of our lab’s work. While much of our research has focused on the hippocampus, we are also exploring the role of the amygdala and medial prefrontal cortex in our memory paradigms. We’re passionate about the open-source movement and committed to building a collaborative and generous neuroscience community.
The human brain is more powerful and more complex than any supercomputer in existence. Yet, how the brain processes, stores, and retrieves information at such massive scale over the course of a lifetime remains a mystery. Understanding these processes has profound implications not only for neuroscience, but for computer science, as well. In our lab, we’re investigating how the brain optimizes its capacity for memory storage and efficiency and how these processes may change over time. We observe and manipulate both neural activity and behavior in mice as they are living, learning, and aging to understand the versatile strategies the brain uses to encode, store, and retrieve memories across the lifespan.
Our discovery that memories encoded close in time are represented in shared populations of neurons in the brain, and that recall of one memory triggers recall of the other, has led us to consider fundamental questions about the ways in which time and emotion impact what and how memories are encoded, stored, and recalled. How do aversive experiences, such as fear, impact the linking and recalling of multiple memories on the levels of cells, circuits, and behavior?What we have called “retrospective memory-linking” has implications for our understanding of both typical development and numerous memory related disorders, including PTSD, age-related conditions such as Alzheimer’s and dementia, and appetitive memory (addiction). We’re studying temporal memory-linking to understand how the integration or separation of memories in the cells and circuits of the brain over time contributes to learning and memory in healthy and diseased brains.
Sleep and Memory
We have been intrigued by the importance of sleep on memory since our findings that sleep is not only critical for stabilizing recently learned memories, but REM sleep enhances creative problem solving by integrating recently learned information with prior experience. Now, our lab is looking at the neurobiological basis of how memories are stabilized and integrated with past information during sleep. This has implications for both normal cognition and memory disorders that show sleep disturbances, such as PTSD and age-related conditions such as Alzheimer’s and dementia.
Powerful new technologies are allowing us to probe a number of critical questions in novel ways about how memories change across time and experience. Our lab is dedicated to building and sharing new techniques and technologies and leveraging the innovative tools designed by other groups to investigate the dynamic nature of memory. We combine calcium imaging, optogenetics, chemogenetics, electrophysiology techniques, behavioral assays and output, and computational approaches to understand how memories are encoded, stored and recalled over time. While much of our work is conducted in freely behaving animals, we’re engaged with multiple collaborators on projects using both in vitro and in vivo approaches. We’re interested, as well, in cross-species experimentation. A challenge for our field will be making sense of the enormous volumes of data our new tools and technologies make it possible for us to obtain. Our lab is actively developing and sharing new analyses pipelines, designed specifically for users with limited background in computer science.
Miniscope: an open-source miniature head-mounted microscope for in vivo calcium imaging in freely behaving animals
I am a co-developer of UCLA Miniscopes, a miniature fluorescence microscope based on a design pioneered by Dr. Mark Schnitzer’s lab at Stanford. Miniscopes is a series of inexpensive, open-source head-mounted microscopes that use wide-field fluorescence imaging to record neural activity in awake, freely moving mice. With our collaborators at UCLA and here at Mount Sinai, our lab continues to evolve the Miniscopes system. We have built a wire-free version that enables us to track hundreds-to-thousands of neurons across days to weeks to months and longer in a freely behaving animal. The Miniscopes wiki site provides a centralized location for sharing of design files, parts lists, source code, tutorials, and a way to connect with other Miniscopes users. One of the most exciting parts of the Miniscope Project is meeting neuroscientists from around the world at our Miniscope hands-on workshops where participants build their own Miniscopes, learn surgery methods, and are introduced to the analysis software. Hundreds of labs worldwide are using and building on this powerful technology. https://github.com/DeniseCaiLab/Miniscope_DAQ_Software
Minian: an open-source Miniscopes analysis pipeline with interactive visualization tools
Miniscopes have gained a lot of traction for in vivo calcium imaging in freely behaving animals. However, extracting calcium signals from raw videos is a computationally complex problem and remains a bottleneck for many researchers utilizing single photon in vivo calcium imaging. There is a need for a user-friendly tool that offers informative visualization of how altering parameters affects the output of the data. Our open-source analysis pipeline, Minian, facilitates transparency and accessibility of the underlying algorithm of the pipeline. Minian contains interactive visualization tools for every analysis step, as well as detailed documentation and tips on parameter tuning. The visualization tool guides users to explore and select the appropriate parameters, which is especially helpful in analyzing different cell-types and brain regions. Minian has been validated to reliably and robustly extract calcium events across different cell types and brain regions. https://github.com/DeniseCaiLab/minian
ezTRACK: an open-source video analysis pipeline for the investigation of animal behavior
Tracking small animal behavior by video is one of the most common tasks in neuroscience and psychology. Commercial software to accomplish this task, however, is expensive and often inflexible and free software often relies on complex algorithms. To overcome these hurdles, we developed a simple, free, open-source video analysis pipeline. ezTRACK can be used for automated tracking of the position and speed of animals as well as their freezing behavior (for fear conditioning experiments). It is accessible to researchers who have no programming background, provides numerous easy-to-follow visualizations, accepts a large number of video file formats, produces tabular data in accessible file formats, and is entirely platform independent. ezTrack is freely available on Github and was published on bioRxiv. https://github.com/DeniseCaiLab/ezTrack
Zachary T. Pennington, Zhe Dong, Regina Bowler, Yu Feng, LaurenM Vetere, Tristan Shuman, Denise J. Cai. (2019) ezTrack: An open-source video analysis pipeline for the investigation of animal behavior. bioRxiv. June 4, 2019. https://doi.org/10.1101/592592
Tristan Shuman, Daniel Aharoni, Denise J Cai, Christopher R. Lee, Spyridon Chavlis, Jiannis Taxidis, Sergio E. Flores, Kevin Cheng, Milad Javaherian, Christina C. Kaba, Matthew Shtrahman, Konstantin I. Bakurin, Sotiris Masmanidis, Maljit S. Khakh, Panayoita Poirazi, Alcino J. Silva, Peyman Golshani. (2018). Breakdown of spatial coding and neural synchronization in epilepsy. bioRxiv June 29, 2018. https://www.biorxiv.org/content/10.1101/358580v1
Zhou M, Greenhill S, Huang S, Silva TK, Sano Y, Wu S, Cai Y, Nagaoka Y, Sehgal M, Cai DJ, Lee YS, Fox K, Silva AJ. (2016) CCR5 is a suppressor for cortical plasticity and hippocampal learning and memory. eLife. 2016 Dec 20;5. pii: e20985. PMID: 27996938
Cai DJ*, Aharoni D*, Shuman T*, Shobe J* (*co-first author), Biane J, Song W, Wei B, Veshkini M, La-Vu M, Lou J, Flores S, Kim I, Sano Y, Zhou M, Baumgaertel K, Lavi A, Kamata M, Tuszynski M, Mayford M, Golshani P, Silva AJ. (2016) A shared neural ensemble links distinct contextual memories encoded close in time. Nature, 534(7605),115-118. PMID: 27251287
Rogerson T, Jayaprakash B, Cai DJ, Sano Y, Lee Y, Bekal P, Deisseroth K, Silva AJ. (2016) Molecular and cellular mechanisms for trapping and activating emotional memories. PLOS ONE, 1(8):e0161655. PMID: 27579481
Kastellakis G, Cai DJ, Mednick SC, Silva AJ, Poirazi P. (2015) Synaptic clustering within dendrites: an emerging theory of memory formation. Progress in Neurobiology, 126,19-35. PMID: 25576663
Rogerson T, Cai DJ, Frank A, Sano Y, Shobe J, Lopez-Aranda MF, Silva AJ. (2014) Synaptic tagging during memory allocation. Nature Reviews Neuroscience, 15(3), 157-169. PMID: 24496410
Sano Y, Shobe JL, Zhou M, Huang S, Shuman T, Cai DJ, Golshani P, Kamata M, Silva AJ. (2014) CREB regulates memory allocation in the insular cortex. Current Biology, 24(33): 2833-2837. PMID: 25454591
Shuman T, Cai DJ, Sage JR, Anagnostaras SG. (2012) Interactions between modafinil and cocaine during the induction and expression of conditioned place preference and locomotor sensitization: implications for addiction. Behavioural Brain Research, 235(2), 105-112. PMID: 22963989
Mednick SC, Cai DJ, Shuman T, Anagnostaras SG, Wixted JT. (2011) A opportunistic theory of cellular and systems consolidation. Trends in Neurosciences, (doi:10.1016/j.physletb.2003.10.071) PMID: 21742389
Anagnostaras SG, Wood SC, Shuman T, Cai DJ, LeDuc AD, Zurn KR, Sage JR, Herrera GM. (2010) Automated assessment of Pavlovian conditioned freezing and shock reactivity using the VideoFreeze system. Frontiers in Behavioral Neuroscience, 4,158. PMID: 20953248
Rieth CA, Cai DJ, Mednick SC. (2010) The role of sleep and practice in implicit and explicit motor learning. Behavioural Brain Research, 214(2), 470-474. PMID: 20553972
Cai DJ, Mednick SA, Harrison EM, Kanady J, Mednick SC. (2009) REM, not incubation, improves creativity by priming associative networks. Proceedings of the National Academy of Sciences, 106(25), 10130-10134. PMID: 19506253
Cai DJ, Shuman T, Harrison EM, Sage JR, Anagnostaras SG. (2009) Sleep-deprivation and Pavlovian fear conditioning. Learning & Memory, 16, 595-599. PMID: 19794184
Cai DJ, Shuman T, Gorman MR, Sage JR, Anagnostaras SG. (2009) Sleep selectively enhances hippocampus-dependent memory in mice. Behavioral Neuroscience, 123(4), 713-719. PMID: 19634928
Cai DJ and Rickard TC. (2009) Reconsidering the role of sleep for motor memory consolidation. Behavioral Neuroscience, 123(6),1153-1157. PMID: 20001099
Mednick SC, Makovski T., Cai DJ, Jiang YV. (2009) Sleep and rest facilitate implicit memory in a visual search task. Vision Research, 49(21), 2557-2565. PMID: 19379769
Mednick SC, Cai DJ, Kanady J, Drummond SPA. (2008) Comparing the benefits of caffeine, naps and placebo on verbal, motor and perceptual memory. Behavioural Brain Research, 193(1), 79-86. PMID: 18554731
Rickard TC, Cai DJ, Rieth CA, Jones J, Ard MC. (2008) Sleep does not enhance motor sequence learning. Journal of Experimental Psychology: Learning, Memory & Cognition, 34(4), 834-842. PMID: 18605872
Next Generation Leader Denise Cai presents on “Linking memories across time” at the 2017 Allen Institute Showcase Symposium hosted by the Allen Institute for Brain Science.
Meet the Team
Denise J. Cai, PhD
I study the neural mechanisms that govern how memories dynamically change across time and experience. As a doctoral student with Drs. Sara Mednick, Stephan Anagnostaras, and Michael Gorman at the University of California, San Diego, I characterized the role of sleep in creativity and memory processing. In my postdoctoral studies with Dr. Alcino Silva at the University of California, Los Angeles, I studied how memories are linked across time. I am also one of the primary developers of the UCLA Miniscope system, an open source suite of novel imaging technologies and techniques. My lab uses a multi-level approach in our research, incorporating in vivo calcium imaging, optogenetic and chemogenetic activity-dependent gene regulation, electrophysiology, and novel behavioral assays. Outside of the lab, I enjoy spending time with my kids, cooking, dancing, and single malt Scotches.
Lingxuan Chen, PhD
I joined the Cai lab as a postdoctoral fellow in 2018. I received my bachelor’s degree in biomedical engineering from Zhejiang University in China, where I was working in a cognitive neuroscience lab. I then did my doctoral training with Dr. Istvan Mody at UCLA. My PhD thesis was on investigating interneuron deficit in a mouse model of Alzheimer’s disease using in vitro and in vivo electrophysiology techniques. Currently, I am interested in what happens during normal aging, specifically how hippocampal excitability changes and affects learning and memory as we age. Outside of the lab, I enjoy watching movies, playing the piano, exploring new food and places in NYC, and observing the amazing human cognitive development in my baby girl.
Zach Pennington, PhD
I joined the Cai Lab after obtaining my PhD from UCLA in 2018, where I studied PTSD in the laboratory of Dr. Michael Fanselow. In the Cai Lab, I am continuing my research on fear and memory processes relevant to PTSD, utilizing a combination of cell tagging strategies and calcium imaging. The overarching goal of this work is to better understand the biological changes that predispose individuals to develop PTSD in the wake of trauma. I am also involved in the development of open-source tools for automated behavior and calcium imaging analysis. When I’m not in lab, I love exploring New York by foot and by bike, trying new food, watching live music, and baking bread.
William Mau, PhD
I joined the lab as a postdoctoral fellow in 2019. After my undergraduate work with David Smith at Cornell University, I did my graduate training with Howard Eichenbaum and Steve Ramirez at Boston University. At BU, I investigated amygdala responses during fear relapse and long-term activity patterns of hippocampal sequences. My interests lie in understanding how the dynamic brain stores information over time, which I study using longitudinal in vivo calcium imaging and behavior. Outside of the lab, I can be found bouldering and imbibing craft beers.
I earned my undergraduate degree at Nankai University, China, where I majored in biology, and spent a lot of time working in a structural biology lab. Toward the end of my studies, I became fascinated by the anime series Ghost in the Shell and at the same time became interested in the question of consciousness. I was convinced that memory lies at the heart of consciousness and decided to study memory as a doctoral student. I got interested, as well, in the emergent properties of systems and was fascinated by computational neuroscience. My current research interest is studying how particular memories evolve across time and how they may influence the formation of future memories. In addition, I am also working on developing open-source software for calcium imaging analysis. My interests outside of neuroscience include video games, rock music, math, and martial arts.
I completed my undergraduate training at Northeastern University in Behavioral Neuroscience and Computer Science. During that time, I worked in the labs of Dr. Sandeep Robert Datta, Dr. Leon Reijmers, and Dr. Steve Ramirez, where I studied olfactory processing, fear extinction learning, and fear relapse respectively and gained interest in understanding the dynamic nature of memory. I am currently a graduate student in the labs of Dr. Denise Cai and Dr. Kanaka Rajan. I am interested in how the brain constructs dynamic representations of the external world to inform robust but flexible behaviors. I currently use in vivo calcium imaging to study how prior experiences influence future learning, and I conduct in vivo manipulations (e.g. chemo- and opto-genetics) to address how perturbing neural activity influences learning and its underlying neural population dynamics. Alongside these experimental approaches, I use the calcium imaging datasets from our lab to build network models of memory flexibility. These models can produce hypotheses about mechanisms of memory that are testable in vivo. Outside of the lab, I enjoy writing stories with my camera, curating playlists on my Spotify, spending half my weekends baking desserts, and spending the other half eating the desserts.
- On behalf of our lab, I am pleased to announce that I have been awarded the NIH Director’s Innovator Award (2019).
- I was invited to present at IBRIO 2019 in Daegu, South Korea on a panel dedicated to “Visualizing and Controlling Circuits that Generate Emotional Behavior” (September 2019).
- As winner of the 2019 One Mind-Otsuka Rising Start Research Award, I was thrillec to present my research “Temporal memory-linking: a circuit mechanism of PTSD” at the One Mind Music Festival for Brain Health in Rutherford, CA (September 2019).
Daniel Aharoni, Ph.D., Assistant Professor, UCLA
Mark Baxter, Ph.D., Professor, Icahn School of Medicine at Mount Sinai
Ian Maze, Ph.D., Associate Professor, Icahn School of Medicine at Mount Sinai
Paul Kenny, Ph.D., Professor, Icahn School of Medicine at Mount Sinai
Sima Rabinowitz, Writer and Editor
Kanaka Rajan, Ph.D., Assistant Professor, Icahn School of Medicine at Mount Sinai
Tristan Shuman, Ph.D., Assistant Professor, Icahn School of Medicine at Mount Sinai
Paul Slesinger, Ph.D., Professor, Icahn School of Medicine at Mount Sinai
Zhuoli Huang, Researcher, TAL’s Brain-lab
My (Mimi) La-Vu, PhD student, UCLA
Christopher Lee, PhD student, UCSD
Brandon Wei, Medical student, Texas Tech University
Maojuan Zhuang, Associate Researcher, Icahn School of Medicine at Mount Sinai
Funding and Awards
• NIH Director’s New Innovator Award, 2019
• One Mind Rising Star Award, 2019
• McKnight Memory and Cognitive Disorder Award, 2019
• NARSAD Young Investigator Award, 2019
• Brain Research Foundation Award, 2018
• Klingenstein-Simons Fellowship Award, 2018
• Friedman Brain Scholar Award, 2018
• Outstanding Teaching Award, ISMMS, 2018
• Botanical Center Pilot Award, 2018
• Allen Institute Next Generation Leader, 2017
- Together, we achieve more.
- Open dialogue is as important as open source.
- We have individual goals and shared goals. I will do my very best to support both.
- We love hard questions, complex challenges, and unexpected results.
- We’re creative and we take risks. This means that sometimes we’re disappointed in the outcomes. Every “failed” effort is a new opportunity.
- Mind/body health is critical to do good science. We take care of ourselves and each other.