ArticlePLoS computational biology2025
In vivo neural activity of electrosensory pyramidal cells: Biophysical characterization and phenomenological modeling.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Small-Conductance CaNeuroscience bulletin · 2026Review
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4 authors.
Funding
Abstract
Burst firing is an important property of neuronal activity, thought to enhance sensory encoding. While previous studies show significant differences in burst firing between in vivo and in vitro conditions, how burst firing contributes to neural coding in vivo and how it is modulated by underlying biophysical mechanisms when neurons are under active synaptic bombardments remains poorly understood. Here, we combined intracellular recordings and computational modeling to investigate how cellular and synaptic mechanisms can explain the in vivo firing activity of electrosensory lateral line lobe (ELL) pyramidal cells in Apteronotus leptorhynchus. We developed a biophysically detailed compartmental model incorporating voltage-gated currents, NMDA receptor-mediated calcium (Ca2 + ) influx, Ca2 + -activated SK channels, Ca2 + mobilization, and stochastic synaptic inputs to reproduce in vivo firing activities of ELL pyramidal cells. Specifically, using bifurcation analysis, we identified dynamical transitions between quiescent, tonic, and bursting regimes, governed by interactions among SK conductance, NMDA receptor activation, and applied current. Model parameters were optimized against in vivo data, accurately reproducing action potential waveforms and temporal dynamics, including characteristic bimodal interspike interval distributions reflecting intra- and inter-burst intervals. We further developed a modified Hindmarsh-Rose model incorporating dual adaptation variables and stochastic noise. This simplified phenomenological model successfully captured burst firing comparable to that observed in the biophysical model and recorded data, while replicating diverse firing patterns observed across the population. Finally, parameter sensitivity analysis revealed slow adaptation dynamics and noise intensity as key determinants of spiking variability within cells. Overall, our modeling results demonstrate that in vivo bursting arises from synergistic interactions between intrinsic conductances (e.g., NMDA-SK coupling), Ca2 + mobilization, and synaptic stochasticity, offering a potential reconciliation for discrepancies with in vitro firing activity. The models provide mechanistic insights into how background synaptic activity modulates burst firing.
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