Abstract
Sixty-five million people suffer from epilepsy and associated cognitive decline worldwide. Therefore, there is urgent need to identify novel mechanisms involved in epileptic network instability. Densely connected “hub” neurons have been implicated as key controllers of developmental as well as epileptic circuits. While such hub cells are traditionally defined by connection count, how these connections contribute to interictal dynamics is not understood. We performed whole-brain single-cell calcium imaging of the larval zebrafish brain in an acute seizure model. Biologically constrained modeling of cell-cell effective interactions successfully reproduced experimental calcium dynamics and enabled hub identification. Simulated perturbation of single hub neurons in the preseizure state confirmed that such traditional hub cells can exert major influence over global dynamics. Novel higher-order graph analytics revealed that the sensitivity to perturbation is not simply linked to outgoing degrees but rather to overexpression of feedforward motifs surrounding the hub cells that enhance downstream excitation. Model- and species similarity of the key findings was supported by similar results from the hippocampus of chronically epileptic mice. Collectively, these data identify a specific class of high-order hub neuron that is richly involved in feedforward motifs as an attractive new target for seizure control.
Highlights
Whole brain single-cell calcium imaging in zebrafish combined with effective connectivity modeling was used to study epileptic network instability
Preseizure whole brain networks were more sensitive to simulated targeted perturbation of single richly connected “hub” neurons
Higher-order graph clustering revealed overexpression of a class of hub cells engaged in feedforward motifs in the unstable preseizure state
Such higher-order hub neurons enhanced downstream excitation and were causally linked to network instability
Higher-order hub cells were identified in the hippocampus of chronically epileptic mice, showing similar findings across models and species.
Competing Interest Statement
The authors have declared no competing interest.
