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Mental disorders (MD) are among the top most demanding challenges inworld-wide health. According to the World Health Organization, the burden ofMDs continues to grow with significant impact on health and major social andhuman rights. A large number of MDs exhibit pathological rhythms, which serveas the disorders characteristic biomarkers. These rhythms are the targets forneurostimulation techniques. Open-loop neurostimulation employs stimulationprotocols, which are rather independent of the patients health and brain statein the moment of treatment. Most alternative closed-loop stimulation protocolsconsider real-time brain activity observations but appear as adaptive open-loopprotocols, where e.g. pre-defined stimulation sets in if observations fulfilpre-defined criteria. The present theoretical work proposes a fully-adaptiveclosed-loop neurostimulation setup, that tunes the brain activities powerspectral density (PSD) according to a user-defined PSD. The utilized brainmodel is non-parametric and estimated from the observations via magnitudefitting in a pre-stimulus setup phase. Moreover, the algorithm takes intoaccount possible conduction delays in the feedback connection betweenobservation and stimulation electrode. All involved features are illustrated onpathological alpha- and gamma-rhythms known from psychosis. To this end, wesimulate numerically a linear neural population brain model and a non-linearcortico-thalamic feedback loop model recently derived to explain brain activityin psychosis.

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders