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| 001 | 280245 | ||
| 005 | 20250827101638.0 | ||
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| 100 | 1 | _ | |a Khanzada, Shahrukh |0 P:(DE-2719)9001867 |b 0 |e First author |
| 245 | _ | _ | |a Dynamic mapping of network-level LTP in the hippocampus via high-resolution bioelectrical sensing. |
| 260 | _ | _ | |a Melville, NY |c 2025 |b AIP Publishing |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a 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. |
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| 700 | 1 | _ | |a Hu, Xin |0 P:(DE-2719)2814182 |b 1 |
| 700 | 1 | _ | |a Emery, Brett Addison |0 P:(DE-2719)9001361 |b 2 |
| 700 | 1 | _ | |a Średniawa, Władysław |0 0000-0002-3152-4785 |b 3 |
| 700 | 1 | _ | |a Wójcik, Daniel K |0 0000-0003-0812-9872 |b 4 |
| 700 | 1 | _ | |a Kempermann, Gerd |0 P:(DE-2719)2000011 |b 5 |
| 700 | 1 | _ | |a Amin, Hayder |0 P:(DE-2719)2812628 |b 6 |e Last author |
| 773 | _ | _ | |a 10.1063/5.0258985 |g Vol. 9, no. 3, p. 036109 |0 PERI:(DE-600)2916708-5 |n 3 |p 036109 |t APL bioengineering |v 9 |y 2025 |x 2473-2877 |
| 856 | 4 | _ | |u https://pub.dzne.de/record/280245/files/DZNE-2025-00923.pdf |y OpenAccess |
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