Many fundamental questions about how ensembles of neurons store long-term memories remain unanswered. Due to the limitations of in vivo physiological recording methods, data is limited regarding whether neural ensemble representations of stored information evolve over time scales of weeks or more. This grant proposes to examine such questions in the context of the mammalian CA1 hippocampal representation of physical space and spatial memory. We will capitalize on the established properties of CA1 'place cells', which exhibit elevated spike rates when the mammalian subject is physically situated within a cell's 'place field'. Some theories suggest place cells should retan stable place fields for long-term retention of familiar spatial environments. Other work suggests gradual evolution of place cell representations might aid episodic memory, by encoding different events occurring in the same environment using distinct combinations of cells. Whether CA1 representations of familiar places are stable or not has only been partially explored empirically. To date, the data on place fields'stability has generally been restricted to small numbers of cell recorded over at most a week. These studies have shown the existence of place cells with stable place fields, but the data have been too sparse to assess how place cell codes evolve at the population level. We will deve- lop general methods for tracking long-term coding dynamics by combining multiple, recent technical advances. Our approach will allow the first large-scale studies of how CA1 place cell codes evolve over weeks and yield a powerful means by which neuroscientists can address many unanswered questions about long-term memory. We will combine 4 recently developed optical imaging techniques, which together afford the first chance to track the dynamics of genetically identified CA1 cells over multiple weeks in the live brain. Our two aims are:
Aim 1 : Establish a methodology for time-lapse imaging of CA1 neural dynamics over weeks, across hundreds of genetically targeted neurons in freely behaving mice. This will provide an enabling approach for tracking how information is stored and represented by large ensembles of genetically defined neurons.
Aim 2 : Quantitatively assess the long-term kinetics of CA1 ensemble place codes. We wil track how CA1 representations of space evolve in subjects visiting a familiar environment repeatedly for 60 days. We will compare two competing ideas, that individual cells retain stable place fields upon re-visitation of a familiar environment;or alternatively that individual cells'coding properties gradually evolve over time. We will thus quantify the constancy or changes in individual cells'coding properties, and in ensemble features such as the density of place cell coverage and fraction of observed cells involved in representing a given arena. The results will shed light on how CA1 represents and stores information over durations pertinent to long-term memory. If our work succeeds, many previously unanswerable questions wil be addressable by similar means. Our approach should be widely applicable to other brain areas and forms of memory.

Public Health Relevance

In neuroscience, a current limitation is the inability to reliably track the dynamics and coding properties of individual neurons over periods of weeks or more. Our work seeks to create a brain-imaging technique that will alllow researchers to monitor the dynamics of genetically targeted neurons over long time periods deep in the brains of freely behaving mice. We will then use this imaging technique to examine the evolution over weeks of the neural codes that support the representation of space and long-term spatial memory in the hippocampus, a key brain area implicated in many neuropsychiatric disorders including several diseases of memory.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Exploratory/Developmental Grants (R21)
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Neurobiology of Learning and Memory Study Section (LAM)
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Osborn, Bettina D
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Stanford University
Schools of Medicine
United States
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Chen, Jerry L; Andermann, Mark L; Keck, Tara et al. (2013) Imaging neuronal populations in behaving rodents: paradigms for studying neural circuits underlying behavior in the mammalian cortex. J Neurosci 33:17631-40
Ziv, Yaniv; Burns, Laurie D; Cocker, Eric D et al. (2013) Long-term dynamics of CA1 hippocampal place codes. Nat Neurosci 16:264-6