Higher-order hub cells involved in feedforward motifs as critical factors in epileptic network instability

Neurological and psychiatric disorders are associated with pathological neural dynamics. The fundamental connectivity patterns of cell-cell communication networks that enable pathological dynamics to emerge remain unknown. We studied epileptic circuits using a newly developed integrated computational pipeline applied to cellular resolution functional imaging data. Control and preseizure neural dynamics in larval zebrafish and in chronically epileptic mice were captured using large-scale cellular-resolution calcium imaging. Biologically constrained effective connectivity modeling extracted the underlying cell-cell communication network. Novel analysis of the higher-order network structure revealed the existence of superhub cells that are unusually richly connected to the rest of the network through feedforward motifs. Instability in epileptic networks was causally linked to superhubs whose involvement in feedforward motifs critically enhanced downstream excitation. Disconnecting individual superhubs was significantly more effective in stabilizing epileptic networks compared to disconnecting hub cells defined traditionally by connection count. Collectively, these results predict a new, maximally selective and minimally invasive cellular target for seizure control. HighlightsO_LIHigher-order connectivity patterns of large-scale neuronal communication networks were studied in zebrafish and mice C_LIO_LIControl and epileptic networks were modeled from in vivo cellular resolution calcium imaging data C_LIO_LIRare superhub cells unusually richly connected to the rest of the network through higher-order feedforward motifs were identified C_LIO_LIDisconnecting single superhub neurons more effectively stabilized epileptic networks than targeting conventional hub cells defined by high connection count. C_LIO_LIThese data predict a maximally selective novel single cell target for minimally invasive seizure control C_LI