Our model determined that immediate AED treatment is preferable to deferred treatment in adult first-seizure patients over a wide and clinically relevant range of variables. Furthermore, our analysis suggests that the 10-year seizure recurrence rate that justifies AED treatment (38.0%) is substantially lower than the 60% threshold used in the current definition of epilepsy.

Spontaneous activity drives the establishment of appropriate connectivity in different circuits during brain development. In the mouse primary visual cortex, two distinct patterns of spontaneous activity occur before vision onset: local low-synchronicity events originating in the retina, and global high-synchronicity events originating in the cortex. We sought to determine the contribution of these activity patterns to jointly organize network connectivity through different activity-dependent plasticity rules. We found that local events shape cortical input selectivity and topography, while global events have a homeostatic role regulating connection strength. To generate robust selectivity, we predicted that global events should adapt their amplitude to the history of preceding cortical activation, and confirmed by analyzing in vivo spontaneous cortical activity. This adaptation led to the sparsification of spontaneous activity on a slower timescale during development, demonstrating the remarkable capacity of the developing sensory cortex to acquire sensitivity to visual inputs after eye-opening.

Acute hepatic encephalopathy (AHE) is a common form of delirium, a state of confusion, impaired attention, and decreased arousal due to acute liver failure. However, the neurophysiological mechanisms underlying AHE are poorly understood. In order to develop hypotheses for mechanisms of AHE, our work builds on an existing neural mean field model for similar EEG patterns in cerebral anoxia, the bursting Liley model. The model proposes that generalized periodic discharges, similar to the triphasic waves (TPWs) seen in severe AHE, arise through three types of processes a) increased neuronal excitability; b) defective brain energy metabolism leading to impaired synaptic transmission; c) and enhanced postsynaptic inhibition mediated by increased GABA-ergic and glycinergic transmission. We relate the model parameters to human EEG data using a particle-filter based optimization method that matches the TPW interevent-interval distribution of the model with that observed in patients EEGs. In this way our model relates microscopic mechanisms to EEG patterns. Our model represents a starting point for exploring the underlying mechanisms of brain dynamics in delirium.

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