Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity

Brain stimulation is a fundamental therapy for neurological diseases including Parkinson’s disease, essential tremor, and epilepsy. One key challenge in delivering effective brain stimulation is identifying the stimulation parameters (e.g. amplitude, frequency, and pulse width) that optimally change symptoms, behavior, or neural activity. Most clinical and translational studies use constant-frequency pulses of stimulation, but irregular pulse patterns or non-pulsatile waveforms may induce unique neural effects that could enable better therapy. Here, we comprehensively evaluate several optogenetic stimulation waveforms, report their effects on hippocampal bandpower, and compare them to activity recorded during behavior. Sprague-Dawley rats were prepared for pan-neuronal excitatory optogenetic stimulation of the medial septum and 16-channel microelectrode recording in the hippocampus. We performed a comprehensive search of parameters comprising several stimulation waveforms, including standard pulse, nested pulse, sinusoid, double sinusoid, and Poisson pulse waveforms. We report the effects of changing stimulation parameters on two key biomarkers of hippocampal function, theta (4-10 Hz) and gamma (32-50 Hz) power. Similarly robust gamma entrainment was observed across all waveforms, whereas no set of stimulation parameters was sufficient to consistently increase theta power beyond baseline activity (despite the prominent role of the medial septum in pacing hippocampal theta oscillations). Using a manifold learning algorithm, we show that the irregular stimulation patterns can induce activity patterns that more closely resemble activity recorded during natural behavior than conventional parameters. Our counter-intuitive findings – that medial septum stimulation ubiquitously does not increase hippocampal theta power, and that different waveforms have similar effects on single biomarkers – contradict recent trends in brain stimulation research, necessitating fewer assumptions when identifying stimulation targets and waveforms based on neurophysiological biomarkers of disease. We also reveal the biomimetic utility of irregular stimulation patterns and demonstrate a scalable data-driven analysis strategy for the future discovery of physiologically informed patterns in translational settings.