# Population-level neural rejuvenation dynamics in addiction: a computational framework for understanding developmental plasticity reactivation

## TL;DR

This paper presents a computational model showing how drug exposure triggers population-level neural rejuvenation, leading to persistent addiction memories through dynamic synaptic changes.

## Contribution

A novel computational framework that models population-level synaptic dynamics during drug exposure and withdrawal, linking rejuvenation mechanisms to addiction memory formation.

## Key findings

- The model shows distinct phases of synaptic population changes during drug exposure and withdrawal, including juvenile synapse conversion and silent synapse generation.
- Memory strength increases through biphasic mechanisms during exposure and withdrawal, with maturation flux driving memory strengthening.
- Parameter sensitivity analysis confirms the model's robustness, and simulations with natural rewards show minimal rejuvenation effects compared to drugs.

## Abstract

The neural rejuvenation hypothesis proposes that drugs of abuse reactivate developmental plasticity mechanisms to create abnormally persistent addiction memories. While individual molecular components have been characterized experimentally, the population-level dynamics and their collective contribution to addiction pathophysiology remain poorly understood.

To develop a computational framework tracking theoretical synaptic population dynamics during simulated drug exposure and withdrawal, and to demonstrate how coordinated population-level transitions could account for key experimental observations in addiction neuroscience.

We constructed a mathematical model tracking four theoretical synaptic populations (adult, juvenile, silent, and matured synapses) using differential equations. The model incorporates two distinct processes: (1) rejuvenation of existing synapses through receptor composition switching, and (2) de novo generation of silent synapses during drug exposure. Critically, the total synapse population is dynamic, increasing during drug exposure due to synaptogenesis and decreasing during withdrawal due to pruning. State transitions are explicitly phase-gated: silent synapse generation occurs only during exposure, while maturation and pruning occur predominantly during withdrawal. Rate constants were derived from experimental time scales reported in the literature, with explicit biological time mapping (1 time unit = 2 h). Simulations involved five intermittent exposures followed by extended withdrawal, with comprehensive parameter sensitivity analysis to assess model robustness across ±50% parameter variations. Initial conditions were fixed to represent the experimentally motivated baseline (adult synapses only); alternative initial states were also tested and did not change qualitative conclusions.

The model demonstrated coordinated synaptic population transformations that qualitatively paralleled experimental observations. In simulation, results revealed distinct phases of neural rejuvenation with characteristic population dynamics: adult-to-juvenile conversion during exposure (reaching ~500 juvenile synapses in the model), de novo silent synapse generation (~400 synapses), and progressive maturation during withdrawal (~300 matured synapses). The modeled total synapse population increased dynamically from baseline (1,000) to ~1,400 during exposure due to de novo synaptogenesis, then decreased to ~1,300 during withdrawal due to pruning. NMDA receptor composition shifted from 80% GluN2A to 80% GluN2B during simulated exposure. Memory strength increased continuously through biphasic mechanisms: during exposure, memory formation was driven by enhanced plasticity capacity; during withdrawal, memory strengthening was driven by the maturation flux (the rate of CP-AMPAR recruitment into silent synapses), with saturation preventing unbounded growth. Parameter sensitivity analysis demonstrated robust qualitative behavior across ±50% parameter variations. Comparative simulations with natural rewards (modeled with kgenesis = 0) showed minimal rejuvenation effects and attenuated incubation, consistent with experimental observations of drug specificity.

This computational framework demonstrates how neural rejuvenation might operate as a population-level phenomenon, with sequential recruitment of different plasticity mechanisms creating robust addiction-related memories. The model generates testable hypotheses and provides a foundation for understanding potential therapeutic intervention windows targeting different phases of rejuvenation.