# Analysis of the Neural Control of Behavior

> **NIH NIH R37** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2024 · $642,593

## Abstract

PROJECT SUMMARY/ABSTRACT
Spaced training is known to be more efficacious in producing long-term memories than training with short inter-
trial intervals (massed training). Attempts to optimize the spacing effect generally are based on trial-and-error
approaches for choosing the optimal intervals. Consequently, most, if not all, training protocols used in animal
and human studies are probably not optimal. We believe that the explanation for why one protocol is more
effective than another lies, at least in part, in the dynamic interactions of key signaling molecules involved in the
induction of long-term synaptic plasticity. The present proposal will investigate the dynamics of signaling
cascades critical for the efficacy of training protocols that lead to induction of long-term memory (LTM), using
long-term synaptic facilitation (LTF) at sensorimotor synapses as a model system.. An understanding of these
interactions would provide insights into mechanisms for LTM induction and consolidation in other systems. The
present proposal will analyze the dynamics of key protein kinases such as protein kinase A (PKA), extracellular
signal–regulated kinase (ERK), ribosomal S6 kinase (RSK), and p38 mitogen-activated protein kinase (p38
MAPK); and key transcription factors such as cAMP-response element binding protein 1 (CREB1) and its
repressor CREB2, CCAAT/enhancer binding protein (C/EBP), and methyl-CpG-binding protein 2 (MeCP2) for
periods up to 48 hours after different training protocols (Aim 1). In Aim 2, the quantitative contribution of these
processes to LTF will be assessed using pharmacological and RNAi techniques. Aim 1 will provide a detailed
description of how kinases and transcription factors are regulated by different LTF-inducing protocols for up to
48 h after treatment. Aim 2 will characterize the necessity of critical signaling molecules to the induction,
consolidation, and maintenance of LTF. By comparing the commonality and differences among the time courses
of kinases and transcription factors activated by different protocols, we will identify key components for induction,
consolidation, and persistence of LTF. These data will be used to predict improved single-block and multi-block
training protocols for enhancing/prolonging LTF and LTM (Aim 3).

## Key facts

- **NIH application ID:** 10832092
- **Project number:** 5R37NS019895-41
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** John H Byrne
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $642,593
- **Award type:** 5
- **Project period:** 1983-04-01 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10832092

## Citation

> US National Institutes of Health, RePORTER application 10832092, Analysis of the Neural Control of Behavior (5R37NS019895-41). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10832092. Licensed CC0.

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