Abstract
How does the dynamics of neurons in a network respond to changes in synaptic weights? Answer to this question would be important for a full understanding of synaptic plasticity. In this article, we report our numerical study of the effects of changes in inhibitory synaptic weights on the spontaneous activity of networks of spiking neurons with conductance-based synapses. Networks with biologically realistic features, which were reconstructed from multi-electrode array recordings taken in a cortical neuronal culture, and their modifications were used in the simulations. The magnitudes of the synaptic weights of all the inhibitory connections are decreased by a uniform amount subjecting to the condition that inhibitory connections would not be turned into excitatory ones. Our simulation results reveal that the responses of the neurons are heterogeneous: while the firing rate of some neurons increases as expected, the firing rate of other neurons decreases or remains unchanged. The same results show that heterogeneous responses also occur for an enhancement of inhibition. This heterogeneity in the responses of neurons to changes in inhibitory synaptic strength suggests that activity-induced modification of synaptic strength does not necessarily generate a positive feedback loop on the dynamics of neurons connected in a network. Our results could be used to understand the effects of bicuculline on spiking and bursting activities of neuronal cultures. Using reconstructed networks with biologically realistic features enables us to identify a long-tailed distribution of average synaptic weights for outgoing links as a crucial feature in giving rise to bursting in neuronal networks and in determining the overall response of the whole network to changes in synaptic strength. For networks whose average synaptic weights for outgoing links have a long-tailed distribution, bursting is observed and the average firing rate of the whole network increases upon inhibition suppression or decreases upon inhibition enhancement. For networks whose average synaptic weights for outgoing links are approximately normally distributed, bursting is not found and the average firing rate of the whole network remains approximately constant upon changes in inhibitory synaptic strength.
Highlights
Synaptic plasticity, the modification of the strength of synaptic connections in response to activity, has long been proposed to play an important and fundamental role in learning and memory (Hebb, 1949)
When synapses are strengthened by activity, the stronger synapses are expected to lead to higher activity and, it is commonly believed that activitydependent synaptic plasticity is a positive feedback process that would lead to instability (Abbott and Nelson, 2000) and a number of stabilization mechanisms have been suggested (Chen et al, 2013; Bannon et al, 2020)
For networks whose average synaptic weights for outgoing links are approximately normally distributed, bursting is not found and the average firing rate of the whole network remains approximately constant upon changes in inhibitory synaptic strength
Summary
The modification of the strength of synaptic connections in response to activity, has long been proposed to play an important and fundamental role in learning and memory (Hebb, 1949). Using experiments and simulations on a neuron of the lobster and on a model neuron, it was found that the effect of changes in synaptic strength saturates and additional changes beyond the saturation point produce no further changes in the dynamics of the neuron (Prinz et al, 2003). This result suggests that changes in the strength of the synapses onto a neuron do not necessarily lead to changes in the spiking activity of that neuron. Direct studies answering the question of how the dynamics of neurons in a network would be altered by changes of synaptic strength would be important for a full understanding of synaptic plasticity
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