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通过高分辨率生物电传感对海马体中网络水平的长时程增强进行动态映射。

Dynamic mapping of network-level LTP in the hippocampus via high-resolution bioelectrical sensing.

作者信息

Khanzada Shahrukh, Hu Xin, Emery Brett Addison, Średniawa Władysław, Wójcik Daniel K, Kempermann Gerd, Amin Hayder

机构信息

Group of "Biohybrid Neuroelectronics (BIONICS)," German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, 01307 Dresden, Germany.

Laboratory of Neurophysiology of Mind, Centre of Excellence for Neural Plasticity and Brain Disorders (BrainCity), Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, Warsaw 02-093, Poland.

出版信息

APL Bioeng. 2025 Jul 29;9(3):036109. doi: 10.1063/5.0258985. eCollection 2025 Sep.

Abstract

Understanding the complexity of neural network dynamics demands advanced biosensing technologies capable of capturing large-scale interactions with high spatial and temporal precision. Traditional approaches, such as patch-clamp and field recordings, are inherently limited in resolving network-wide synaptic connections, particularly long-term potentiation (LTP), due to their localized scope and indirect access to hippocampal subfields. To address these challenges, we introduce EvoNES, a CMOS-based high-definition 4096 microelectrode array platform that leverages bidirectional stimulus-responsive biosensing functionality. By coupling precise external electrode stimulation targeting the Schaffer collateral and medial perforant pathways with simultaneous on-chip bioelectrical recordings, EvoNES enables the first real-time quantification of evoked responses and LTP dynamics across the entire hippocampal circuit. This system bridges critical gaps in traditional techniques, providing a mesoscopic-scale view of cell assemblies interplay and delivering unprecedented insights into the distributed mechanisms underlying memory encoding and learning processes. Advanced computational analyses generate variation maps revealing distinct voltage fluctuation patterns and differential sensitivity across hippocampal subregions during synaptic potentiation. Our findings identify four distinct waveform classes within the CA1-CA3 network and three unique evoked firing patterns in the dentate gyrus (DG). Post-tetanic responses show faster induction, expanded activated zones, and the activation of previously silent cell assemblies, indicating significant network restructuring. Applied in aged mice, EvoNES demonstrates age-dependent changes in network LTP, both quantitatively and qualitatively. This high-resolution biosensing platform in a live neural context provides unprecedented insights into hippocampal memory formation and offers a powerful tool for investigating neural plasticity and network interactions in both health and disease states.

摘要

理解神经网络动力学的复杂性需要先进的生物传感技术,这些技术能够以高空间和时间精度捕捉大规模的相互作用。传统方法,如膜片钳和场记录,在解析全网络突触连接方面存在固有局限性,特别是在解析长时程增强(LTP)时,因为它们的范围局限且只能间接访问海马亚区。为应对这些挑战,我们引入了EvoNES,这是一个基于CMOS的高清4096微电极阵列平台,它利用了双向刺激响应生物传感功能。通过将精确的外部电极刺激靶向海马伞和内侧穿通通路,并同时进行片上生物电记录,EvoNES能够首次实时量化整个海马回路中诱发反应和LTP动力学。该系统弥补了传统技术中的关键差距,提供了细胞组件相互作用的介观尺度视图,并为记忆编码和学习过程背后的分布式机制提供了前所未有的见解。先进的计算分析生成了变化图,揭示了突触增强期间海马亚区不同的电压波动模式和差异敏感性。我们的研究结果在CA1-CA3网络中识别出四种不同的波形类别,在齿状回(DG)中识别出三种独特的诱发放电模式。强直后反应显示出更快的诱导、扩大的激活区域以及先前沉默的细胞组件的激活,表明网络发生了显著重组。应用于老年小鼠时,EvoNES在定量和定性方面都证明了网络LTP存在年龄依赖性变化。这种在活体神经环境中的高分辨率生物传感平台为海马记忆形成提供了前所未有的见解,并为研究健康和疾病状态下的神经可塑性和网络相互作用提供了强大工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9c2/12310272/527ee9526b8d/ABPID9-000009-036109_1-g001.jpg

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