CNS*2026 Halifax

Introduction
Learning requires neural circuits to remain adaptable while preserving learned representations—a fundamental trade-off known as the plasticity-stability dilemma. Dendritic arbors equipped with compartment-specific inhibition support local gating of excitatory plasticity, allowing multiple input streams to be integrated independently within a single neuron, without disrupting existing knowledge [1]. Co-dependent excitatory and inhibitory plasticity has been shown to account for quick, stable, and long-lasting memory storage in biological networks [2]. However, this co-dependence has been formalized through phenomenological spike-timing rules, leaving the underlying biophysical mechanisms unspecified.


Methods
Motivated by its central role in dendritic integration and long-term plasticity, we hypothesized that intracellular calcium orchestrates the local induction of excitatory and inhibitory plasticity. We extended a three-compartment cortical pyramidal cell model to include compartment-specific calcium dynamics from distinct sources (back-propagating action potentials, voltage-gated calcium channels, and NMDA receptors) and implemented co-dependent excitatory and inhibitory learning rules based on the calcium control hypothesis [3], driven by a shared local calcium signal. We embedded our augmented neuron model into a canonical cortical microcircuit model with cell type-specific connectivity and compartment-specific, differential inhibition.


Results
Our calcium-based learning rules yielded balanced networks with enhanced memory capacity and robustness to noise and continual learning. We identified compartment-specific fixed points for excitation-inhibition balance. Targeted perturbation of compartment-specific calcium dynamics resulted in selective memory retrieval with transient disruption of the local excitation-inhibition balance.


Discussion
Our findings support a biophysically plausible role for calcium compartmentalization in coordinating excitatory and inhibitory plasticity through local heterosynaptic interactions. The compartment-specific excitation-inhibition fixed points likely arise from the locality of calcium signals and their distinct sources, providing mechanistic insight into how cortical networks achieve compartment-specific control of learning-induced plasticity. Altogether, these results bridge synaptic biophysics and network-level computation while generating generalizable principles to inform the development of more efficient, biologically grounded adaptive systems.


References
1. Yang, G. R., Murray, J. D., & Wang, X.-J. (2016). A dendritic disinhibitory circuit mechanism for pathway-specific gating. Nature Communications, 7(1), 12815. https://doi.org/10.1038/ncomms12815
2. Agnes, E. J., & Vogels, T. P. (2024). Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. Nature Neuroscience, 27(5), 964–974. https://doi.org/10.1038/s41593-024-01597-4
3. Graupner, M., & Brunel, N. (2012). Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location. Proceedings of the National Academy of Sciences, 109(10), 3991–3996. https://doi.org/10.1073/pnas.1109359109

Acknowledgement
This work was supported by national funds through FCT—Foundation for Science and Technology, I.P., under the project HetSyn (2023.13758.PEX).