Knowledge of facts and events, called episodic memory, is thought to be acquired by an interaction between several brain regions during behavior and during sleep. It is hypothesized that the neocortex sends information to the hippocampus during behavior and the hippocampus learns the associations between these inputs rapidly during behavior. Then, during a subsequent period of sleep, especially during the slow-wave sleep oscillations, the hippocampus is thought to transfer the recently learned information about events back to the neocortex for storage. This process is called memory consolidation. While there is tantalizing evidence from research over many years supporting this hypothesis, the mechanisms by which this is accomplished have remained elusive. Using in-vivo whole-cell and ensemble electrophysiology, single-cell pharmacology, and computational modeling we will address some of the gaps in our knowledge about cortico-hippocampal interaction. Towards this goal, we will focus on the entorhinal cortex. The entorhinal cortex acts as a gateway between neocortex and hippocampus. A vast majority of neocortical inputs to the hippocampus arrive through the entorhinal cortex and conversely, a majority of hippocampal outputs go to the entorhinal cortex. Further, removal of entorhinal cortical inputs to the hippocampus results in profound impairments in learning and memory consolidation. Thus, an understanding the functioning of entorhinal cortical activity during sleep oscillations is critical for understanding episodic memory acquisition. In vitro studies show that when entorhinal cortical neurons are stimulated, they continue to persist in the elevated activity state called persistent activity. However, it is unclear if conditions required for generating persistent activity exist in vivo, and the mechanisms that can accomplish this are unknown. We will test a novel hypothesis that persistent activity can occur spontaneously during sleep oscillations and contribute to memory consolidation. Further, the entorhinal cortex has many parts, each containing distinct types of neurons which have very different distribution of ion channels. These parts of entorhinal cortex are connected to each other, yet they have distinct roles in learning. Hence, we will test the hypothesis that not only the cellular mechanisms but interactions between networks of neurons will play a key role in entorhinal persistent activity during sleep oscillations. To achieve these goals we will measure the subthreshold membrane potential of identified entorhinal neurons from all parts of the entorhinal cortex in vivo, and develop analysis tools to relate the entorhinal persistent activity in vivo to both the cellular properties of these neurons and the activity of connected ensembles of neocortical and hippocampal neurons. We will develop computational models to determine how the interaction between cellular and network mechanisms influence the entorhinal persistent activity during sleep oscillations, and how the persistent activity influences cortico-hippocampal interaction. The predictions of the model will be tested experimentally using pharmacological manipulation of activity of single cells intracellularly. Intellectual Merit: The project will provide the first evidence of subthreshold persistent activity in vivo, determine how cellular and network mechanisms generate it, and how it could orchestrate activity patterns of several parts of the brain to influence episodic memory formation. An improved understanding of these mechanisms will be useful in approaches to treating memory related disorders, which are part of many psychiatric diseases including depression, dementia and schizophrenia. Hahn is one of the first persons to do hippocampal whole-cell measurements in vivo. Mehta has developed many models of learning, developed analysis tools and applied them to the in vivo data. Hahn and Mehta have jointly published two papers on related topics. They have the tools and skills needed to do this research. Broader Impacts: Mehta lab has involved thirty undergraduates in the past research of which half were women and five were minority. They will continue this process. Further, experimental and theoretical tools will be shared between Germany and the US. This work will teach biological facts and tools to physics students and teach quantitative tools to biologists and clinicians. This interdisciplinary research and education will prepare the next generation of neuro-physicists that are comfortable with both experimental biology, mathematical methods and possibly clinical real life phenomena, thereby improving the research infrastructure in participating institutes.
An understanding of persistent activity would provide a better understanding of neural mechanisms of working memory and treating disorders of memory. Excessive persistent activity in the entorhinal cortex can mediate certain forms of epilepsy. Hence, understanding the mechanisms of generation and cessation of persistent activity in vivo would point to ways of treating these types of epilepsy.
|Acharya, Lavanya; Aghajan, Zahra M; Vuong, Cliff et al. (2016) Causal Influence of Visual Cues on Hippocampal Directional Selectivity. Cell 164:197-207|
|Aghajan, Zahra M; Acharya, Lavanya; Moore, Jason J et al. (2015) Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality. Nat Neurosci 18:121-8|
|Mehta, Mayank R (2015) From synaptic plasticity to spatial maps and sequence learning. Hippocampus 25:756-62|
|Ravassard, Pascal; Kees, Ashley; Willers, Bernard et al. (2013) Multisensory control of hippocampal spatiotemporal selectivity. Science 340:1342-1346|
|Cushman, Jesse D; Aharoni, Daniel B; Willers, Bernard et al. (2013) Multisensory control of multimodal behavior: do the legs know what the tongue is doing? PLoS One 8:e80465|
|Hahn, Thomas T G; McFarland, James M; Berberich, Sven et al. (2012) Spontaneous persistent activity in entorhinal cortex modulates cortico-hippocampal interaction in vivo. Nat Neurosci 15:1531-8|
|Ahmed, Omar J; Mehta, Mayank R (2012) Running speed alters the frequency of hippocampal gamma oscillations. J Neurosci 32:7373-83|
|Resnik, Evgeny; McFarland, James M; Sprengel, Rolf et al. (2012) The effects of GluA1 deletion on the hippocampal population code for position. J Neurosci 32:8952-68|
|Ghorbani, Maryam; Mehta, Mayank; Bruinsma, Robijn et al. (2012) Nonlinear-dynamics theory of up-down transitions in neocortical neural networks. Phys Rev E Stat Nonlin Soft Matter Phys 85:021908|
|McFarland, James M; Hahn, Thomas T G; Mehta, Mayank R (2011) Explicit-duration hidden Markov model inference of UP-DOWN states from continuous signals. PLoS One 6:e21606|
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