Evidence map›Paper›PMID 40740280›Full record

ArticleAPL bioengineering2025

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

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

Abstract read
In one paragraph

Article in APL bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shahrukh KhanzadaGroup of "Biohybrid Neuroelectronics (BIONICS)," German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, 01307 Dresden, Germany.ORCID https://orcid.org/0000-0002-5958-4851
Xin HuGroup of "Biohybrid Neuroelectronics (BIONICS)," German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, 01307 Dresden, Germany.ORCID https://orcid.org/0000-0001-6151-2032
Brett Addison EmeryGroup of "Biohybrid Neuroelectronics (BIONICS)," German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, 01307 Dresden, Germany.ORCID https://orcid.org/0000-0001-9614-4567
Władysław ŚredniawaLaboratory 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.ORCID https://orcid.org/0000-0002-3152-4785
Daniel K WójcikLaboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, Warsaw 02-093, Poland.ORCID https://orcid.org/0000-0003-0812-9872

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID40740280
PMCPMC12310272

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.