Inhibiting JNK and PI3K-Akt signaling pathways altered spontaneous network bursts and developmental trajectories of neuronal networks
Bibliographic record
Abstract
Abstract Objective. Spontaneous network bursts (NBs) are critical for neuronal circuit development, influencing synaptogenesis and functional organization. While JNK and PI3K-Akt signaling pathways are known to regulate synaptic plasticity, their specific roles in governing NBs dynamics and functional network organization remain poorly understood. This study investigates the roles of JNK and PI3K-Akt signaling in regulating spontaneous NBs dynamics and network organization in cultured neuronal networks. Approach. Using longitudinal microelectrode array (MEA) recordings from cultured cortical neurons (DIV14-49), we pharmacologically inhibited JNK (SP600125, JNK-IN-8) and PI3K-Akt (LY294002, GDC-0941) pathways. We quantitatively analyzed NBs profiles (maximum firing rate/MFR, burst length/BL, rising phase/RP) and functional network properties (modularity, betweenness centrality) during development. Main results. JNK inhibition increased MFR but reduced RP and FP, and decreased betweenness centrality and network modularity, particularly in DIV21. PI3K-Akt inhibition caused delayed effects: decreased MFR at DIV49 with increased RP, while enhancing network modularity. Developmental analysis revealed a transition from core-node-driven NBs (strong MFR-betweenness and BL-betweenness correlation at DIV14) to modularly organized NBs (strong BL-modularity and MFR-modularity correlation at DIV49), with pathway inhibitors differentially altering these relationships. Significance. Our findings demonstrate that JNK and PI3K-Akt pathways play distinct temporal roles in regulating NBs dynamics and network organization. JNK signaling is crucial for maintaining early core-node functionality, whereas PI3K-Akt signaling promotes the development of mature modular architecture. Our findings enhance the understanding of how molecular signaling influences neuronal network dynamics, contributing to a broader framework for studying neurodevelopmental principles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".