# Experimental and modeling investigations into microcircuit, cellular and subcellular determinants of hippocampal ensemble recruitment to contextual representations

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $680,849

## Abstract

Although neuroscience has recently provided a great deal of information about how neurons represent and
encode behaviorally relevant information at the population level, the fundamental question of how individual
neurons are selected and recruited to memory coding ensembles has been difficult to address. Our group has
been at the forefront of developing experimental methods that allow high-resolution monitoring of identified
neurons, monitoring subcellular events in dendrites and axons, all of which can now be done in awake behaving
animals. We propose to use these experimental methods in combination with circuit modeling to provide a deep
understanding of how the neurons in the mouse hippocampus are recruited to neural ensembles during
contextual memory encoding. Because much is known about the excitatory and inhibitory cell types involved and
their network connections at the main CA1 output node of the rodent hippocampus, this circuit represents a
tractable target for the first major effort to elucidate the microcircuit/cellular/subcellular mechanisms of cell-
selection at a mechanistic level comparable to that achieved in the study of simple invertebrate systems. Aim 1 is
aimed at characterizing collective inhibitory dynamics in CA1 during contextual learning. Aim 2 deals with the
events that occur in cell bodies and dendrites of CA1 pyramidal cells during contextual leaning, including targeted
manipulation in identified inhibitory cells types and understanding the fundamental network architecture by
which cellular activity patterns conducive to memory encoding are regulated. Aim 3 deals with how the
information that is encoded during contextual learning converges onto individual CA1 pyramidal cells during
contextual learning. Finally, Aim 4 builds upon recent work indicating that CA1 pyramidal cells can be reliably
recruited to memory coding ensembles through a plasticity mechanism that requires dendritic spikes and
somatic bursting activity. We will use optogenetic means to create artificial firing fields in neurons and determine
whether these cells can encode context-related and reinforcement related signals; we will also interfere with local
circuit inhibition to determine whether cell selection through plasticity is regulated by inhibition. Throughout
the proposal we will leverage unprecedentedly close interplay between experiment and computation by using a
biophysically detailed model of the hippocampal CA1 microcircuit. To the extent that the model can account for
the experimental observations, we can use it to understand underlying network principles and design
interventional experiments to validate this understanding. To the extent that the model cannot explain results,
it will help point us to aspects of network function that require further elucidation. Taken together, Aims 1-4
provide a tractable path to a major breakthrough in understanding how cognitively important neural activity
dynamics are generated at the microcircuit-, cell...

## Key facts

- **NIH application ID:** 10745299
- **Project number:** 5R01MH124867-04
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Attila Losonczy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $680,849
- **Award type:** 5
- **Project period:** 2021-01-01 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10745299

## Citation

> US National Institutes of Health, RePORTER application 10745299, Experimental and modeling investigations into microcircuit, cellular and subcellular determinants of hippocampal ensemble recruitment to contextual representations (5R01MH124867-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10745299. Licensed CC0.

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