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Growth-adaptive spring electronics for long-term, same-neuron mapping in the developing rat brain
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Growth-adaptive spring electronics for long-term, same-neuron mapping in the developing rat brain

Ariel J. Lee, Hao Sheng, Arnau Marin-Llobet +11 more
February 2026
 ·
bioRxiv
 ·
DOI 
10.64898/2026.02.16.705931
94
%
Reproducible
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It ranks in the top 1% of preprints assessed in Bioengineering this quarter.
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Why this is interesting

By solving the mechanical barrier of recording the same neurons across rapid neonatal brain growth, this work overturns the population-wide model of cortical desynchronization, revealing it is driven by a discrete transitioning neuronal subpopulation.

QED claims analysis

Summary

Growth-adaptive spring electronics that accommodate depth-wise brain expansion enable continuous single-neuron tracking throughout rat postnatal development (P10-P45), revealing that cortical activity decorrelation arises not from uniform population-wide changes but from trajectory-specific maturation in which a distinct subset of neurons (chorister-to-soloists) progressively transitions from high to low population coupling during postnatal weeks 3-5, while other neurons maintain stable coupling states throughout development.

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Main Claim 1 –

Helical springs provide anisotropic compliance for postnatal brain growth

Supporting evidence

  • Planar spirals transform into implanted 3D helical spring electrodes
  • Protective neonatal headstage enables stable chronic implants with dam care
Main Claim 2 –

VLM-assisted pipeline probabilistically matches spikes across developmental days

Supporting evidence

  • High-density arrays localize units from multi-channel spatial amplitude profiles
  • Tracked neurons show age-related declines in bursting and correlations
Main Claim 3 –

Population coupling is bimodal, supporting distinct low/high coupling states

Main Claim 4 –

Same-neuron mapping reveals three population-coupling developmental trajectories

Supporting evidence

  • Trajectory composition and transition timing differ between V1 and mPFC
  • Trajectories differ across 14 electrophysiological metrics and functional space

Abstract

Neural activity reorganizes profoundly after birth, transitioning from highly synchronous population events to sparse, decorrelated firing in the mature brain. Although inhibitory maturation and shifts in excitation-inhibition balance have been implicated in this process, how individual neurons implement the transition remains unclear because rapid brain growth has prevented long-term, same-neuron mapping. Here, we introduce growth-adaptive spring electronics that provide depth-wise compliance during tissue expansion, maintaining a stable electrode-tissue interface over weeks of neonatal development. We developed a vision-language model-assisted spike processing pipeline for the developing brain that probabilistically matches units across days using high-density waveform spatial footprints, despite developmental changes in the neonatal brain. Together, these innovations enable spike-resolved mapping of the same neurons in rat visual cortex and medial prefrontal cortex from postnatal day 10 to 45. Using population coupling to quantify each neuron’s coordination with local population activity, we show that developmental decorrelation is driven primarily by a distinct subset of neurons that progressively shifts from strong to weak coupling during postnatal weeks 3 to 5, whereas other neurons remain stably weakly or strongly coupled throughout development. These results resolve population-level desynchronization into identifiable neuron-specific trajectories. This framework enables direct tests in neurodevelopmental disorder models, including schizophrenia and autism, of whether altered maturation reflects global circuit imbalance or selective disruption and mistiming of specific developmental programs.

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