Effects of spatial constraints of inhibitory connectivity on the dynamical development of criticality in spiking networks
- 1International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- 2Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan
Abstract
Neural systems are hypothesized to operate near criticality, enhancing their capacity for optimal information processing, transmission and storage capabilities. Criticality has typically been studied in spiking neural networks and related systems organized in random or full connectivity, with the balance of excitation and inhibition being a key determinant of the critical point of the system. However, given that neurons in the brain are spatially distributed, with their distances significantly influencing connectivity and signal timing, it is unclear how the spatial organization of excitatory and inhibitory connectivity influences the network’s development towards criticality. Here, we systematically constrain the distance and density of inhibitory connectivity in two-dimensional spiking networks and allow synaptic weights to develop with activity-dependent excitatory and inhibitory plasticity in the presence of a low level of stochastic intrinsic activity. We then investigate the relationship between inhibitory connectivity, synaptic weights, and the resulting network activity during and after development. We find that networks with longer-range inhibitory synapses tend towards more supercritical behavior compared to networks with a similar number of shorter-range inhibitory synapses. We show that this distance dependence is a consequence of weaker long-range synapses after development due to the presence of synaptic delays, which shift most spike pairs outside of the potentiation window of the inhibitory learning rule. Author summary: The brain is thought to operate near a critical state, a regime that supports efficient information processing, transmission, and storage. While previous studies have shown that the balance between excitation and inhibition is important for maintaining criticality, much less is known about how the spatial organization of neural circuits contributes to this process. Using a spatially embedded spiking neural network with biologically motivated synaptic plasticity, we investigated how the range of inhibitory connections influences the development of critical dynamics. We found that networks with predominantly long-range inhibitory connections consistently developed more supercritical activity than networks with similar numbers of short-range inhibitory connections. This effect arose because axonal conduction delays shifted spike timing outside the potentiation window of inhibitory spike-timing-dependent plasticity, preventing distant inhibitory synapses from strengthening effectively. As a result, long-range inhibition provided weaker functional control of network activity despite identical structural connectivity. Our findings identify transmission delays as an important developmental factor linking the spatial organization of inhibitory circuits to network criticality. They further suggest that developmental alterations in inhibitory connectivity may influence brain dynamics by changing the effectiveness of inhibitory interactions, providing experimentally testable predictions for studies of cortical development and neurodevelopmental disorders.
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BibTeX
@article{kern2026effects,
title = {{Effects of spatial constraints of inhibitory connectivity on the dynamical development of criticality in spiking networks}},
author = {Felix Benjamin Kern and Takahisa Date and Zenas C. Chao},
journal = {PLOS Computational Biology},
year = {2026},
month = oct,
doi = {10.1371/journal.pcbi.1014798},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014798},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Effects of spatial constraints of inhibitory connectivity on the dynamical development of criticality in spiking networks
AU - Felix Benjamin Kern
AU - Takahisa Date
AU - Zenas C. Chao
PY - 2026
DA - 2026/10/01
JO - PLOS Computational Biology
DO - 10.1371/journal.pcbi.1014798
UR - https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014798
AB - Neural systems are hypothesized to operate near criticality, enhancing their capacity for optimal information processing, transmission and storage capabilities. Criticality has typically been studied in spiking neural networks and related systems organized in random or full connectivity, with the balance of excitation and inhibition being a key determinant of the critical point of the system. However, given that neurons in the brain are spatially distributed, with their distances significantly influencing connectivity and signal timing, it is unclear how the spatial organization of excitatory and inhibitory connectivity influences the network’s development towards criticality. Here, we systematically constrain the distance and density of inhibitory connectivity in two-dimensional spiking networks and allow synaptic weights to develop with activity-dependent excitatory and inhibitory plasticity in the presence of a low level of stochastic intrinsic activity. We then investigate the relationship between inhibitory connectivity, synaptic weights, and the resulting network activity during and after development. We find that networks with longer-range inhibitory synapses tend towards more supercritical behavior compared to networks with a similar number of shorter-range inhibitory synapses. We show that this distance dependence is a consequence of weaker long-range synapses after development due to the presence of synaptic delays, which shift most spike pairs outside of the potentiation window of the inhibitory learning rule. Author summary: The brain is thought to operate near a critical state, a regime that supports efficient information processing, transmission, and storage. While previous studies have shown that the balance between excitation and inhibition is important for maintaining criticality, much less is known about how the spatial organization of neural circuits contributes to this process. Using a spatially embedded spiking neural network with biologically motivated synaptic plasticity, we investigated how the range of inhibitory connections influences the development of critical dynamics. We found that networks with predominantly long-range inhibitory connections consistently developed more supercritical activity than networks with similar numbers of short-range inhibitory connections. This effect arose because axonal conduction delays shifted spike timing outside the potentiation window of inhibitory spike-timing-dependent plasticity, preventing distant inhibitory synapses from strengthening effectively. As a result, long-range inhibition provided weaker functional control of network activity despite identical structural connectivity. Our findings identify transmission delays as an important developmental factor linking the spatial organization of inhibitory circuits to network criticality. They further suggest that developmental alterations in inhibitory connectivity may influence brain dynamics by changing the effectiveness of inhibitory interactions, providing experimentally testable predictions for studies of cortical development and neurodevelopmental disorders.
SN - 1553-7358
ER -