Magnetic nanoparticles for single-neuron manipulation to design a customized neural circuit

Abstract The complexity and intricacy of the brain, which is composed of billions of neurons, pose significant challenges to its study. Understanding neural connections and communication at the single-cell level is crucial for unraveling the brain’s functions. This study presents a novel strategy that utilizes magnetic nanoparticles (MNPs) and magnetic fields to manipulate neurons, thereby creating customized small-scale neural circuits for studying neural connections. To establish the feasibility of this approach, the effects of MNPs on neurons were initially investigated, demonstrating their low toxicity. Subsequently, a micromagnet array (MMA) chip was employed to manipulate the neurons, facilitating their precise arrangement on the electrodes. Over several days, the neurons extended their axons and established connections with neighboring cells, forming small-scale circular neural circuits. These artificially engineered circuits offer a simplified and controlled environment for studying neural networks in contrast to naturally occurring biological networks. Furthermore, electrophysiological recordings were conducted to investigate the connections between the manipulated neurons. This study introduces a customized small-scale neural circuit platform with electrode-specific recording and stimulating capabilities, enabling the study of neuron-to-neuron interactions at the single-cell level. By leveraging MNPs and an MMA chip, this research offers a powerful tool for studying neural connections and advancing our understanding of the brain’s intricate workings.

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Publication Details

Journal
Bio-Design and Manufacturing
Published
2025-05-22
DOI
https://doi.org/10.1631/bdm.2400372
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

Magnetic nanoparticles for single-neuron manipulation to design a customized neural circuit

Lingrui Zhao, Sumin Bian, Hongyong Zhang, Mohamad Sawan et al.
2 citations
Bio-Design and Manufacturing
Advanced Memory and Neural Computing
1.46
article

Magnetic nanoparticles for single-neuron manipulation to design a customized neural circuit

Lingrui Zhao, Sumin Bian, Hongyong Zhang, Mohamad Sawan, Xiaobo Zhang, Xu Tian, Nan Huang
article en
2 citations

Abstract

Abstract The complexity and intricacy of the brain, which is composed of billions of neurons, pose significant challenges to its study. Understanding neural connections and communication at the single-cell level is crucial for unraveling the brain’s functions. This study presents a novel strategy that utilizes magnetic nanoparticles (MNPs) and magnetic fields to manipulate neurons, thereby creating customized small-scale neural circuits for studying neural connections. To establish the feasibility of this approach, the effects of MNPs on neurons were initially investigated, demonstrating their low toxicity. Subsequently, a micromagnet array (MMA) chip was employed to manipulate the neurons, facilitating their precise arrangement on the electrodes. Over several days, the neurons extended their axons and established connections with neighboring cells, forming small-scale circular neural circuits. These artificially engineered circuits offer a simplified and controlled environment for studying neural networks in contrast to naturally occurring biological networks. Furthermore, electrophysiological recordings were conducted to investigate the connections between the manipulated neurons. This study introduces a customized small-scale neural circuit platform with electrode-specific recording and stimulating capabilities, enabling the study of neuron-to-neuron interactions at the single-cell level. By leveraging MNPs and an MMA chip, this research offers a powerful tool for studying neural connections and advancing our understanding of the brain’s intricate workings.

Bio-Design and ManufacturingVol. 8(4)
Westlake University (CN)
Affordable and clean energy
Openalex Percentile: Top 17%
Advanced Memory and Neural Computing
1.46
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