Laxpati, N. G. | bioRxiv Science

bioRxiv2026

Kilohertz electrical stimulation drives widespread neuronal activation and temporal interference imposes focal rhythmic modulation

Temporal interference (TI) stimulation has attracted attention as a non-invasive approach that can target deep brain structures through interacting kilohertz-frequency electric fields. Its basic premise is that TI stimulation evokes neuronal responses through low-frequency amplitude modulation (AM), while the underlying kilohertz-frequency stimulation is ineffective to induce activity, the latter of which has not been tested rigorously at the cellular level. Here, we combined two-photon imaging in mouse models with immunohistochemistry and computational modeling to characterize spatiotemporal patterns of neuronal responses during TI stimulation. We found that kilohertz-frequency stimulation was sufficient to evoke activity without AM. In contrast, AM organized neuronal activity into rhythmic responses at AM frequency, with the strongest entrainment near the center of interference. Thus, kilohertz-frequency stimulation can drive widespread neuronal activation, upon which TI imposes focal rhythmic modulation. Our results provide a framework for refining TI stimulation and highlight the potential of kilohertz-frequency stimulation for brain stimulation.

neuroscience↗

bioRxiv2024

Refining Brain Stimulation Therapies: An Active Learning Approach to Personalization

Brain stimulation holds promise for treating brain disorders, but personalizing therapy remains challenging. Effective treatment requires establishing a functional link between stimulation parameters and brain response, yet traditional methods like random sampling (RS) are inefficient and costly. To overcome this, we developed an active learning (AL) framework that identifies optimal relationships between stimulation parameters and brain response with fewer experiments. We validated this framework through three experiments: (1) in silico modeling with synthetic data from a Parkinsons disease model, (2) in silico modeling with real data from a non-human primate, and (3) in vivo modeling with a real-time rat optogenetic stimulation experiment. In each experiment, we compared AL models to RS models, using various query strategies and stimulation parameters (amplitude, frequency, pulse width). AL models consistently outperformed RS models, achieving lower error on unseen test data in silico (p<0.0056, N=1,000) and in vivo (p=0.0036, N=20). This approach represents a significant advancement in brain stimulation, potentially improving both research and clinical applications by making them more efficient and effective. Our findings suggest that AL can substantially reduce the cost and time required for developing personalized brain stimulation therapies, paving the way for more effective and accessible treatments for brain disorders.

neuroscience↗

bioRxiv2022

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

IntroductionBrain stimulation is a fundamental and effective therapy for neurological diseases including Parkinsons disease, essential tremor, and epilepsy. One key challenge in delivering effective brain stimulation is identifying the stimulation parameters, such as the amplitude, frequency, contact configuration, and pulse width, that induce an optimal change in symptoms, behavior, or neural activity. Most clinical and translational studies use constant-frequency pulses of stimulation, but stimulation with irregular pulse patterns or non-pulsatile waveforms might induce unique changes in neural activity that could enable better therapeutic responses. Here, we comprehensively evaluate several optogenetic stimulation waveforms, report their differing effects on hippocampal spectral activity, and compare these induced effects to activity recorded during natural behavior. MethodsSprague-Dawley rats were prepared for pan-neuronal excitatory optogenetic stimulation of the medial septum (hSyn-ChR2) and 16-channel microelectrode recording in CA1 and CA3 layers of the hippocampus. We performed grid and random sampling of the parameters comprising several stimulation waveforms, including standard pulse, nested pulse, sinusoid, double sinusoid, and Poisson pulse waveforms. ResultsWe comprehensively report the effects of changing stimulation parameters in these parameter spaces on two key biomarkers of hippocampal function, theta (4-10 Hz) and gamma (32-50 Hz) power. Similarly, robust excitation of hippocampal gamma power was observed across all waveforms, whereas no set of stimulation parameters was sufficient to consistently increase power in the theta band beyond baseline levels of activity (despite the prominent role of the medial septum in pacing hippocampal theta oscillations). Using a manifold learning algorithm to compare high-dimensional neural activity, we show that irregular stimulation patterns produce differing effects with respect to multi-band patterns of activity and can induce activity patterns that more closely resemble activity recorded during natural behavior than conventional parameters. ConclusionOur counter-intuitive findings - that stimulation of the medial septum ubiquitously does not increase hippocampal theta power, and that different waveforms have similar effects on single power bands - contradict recent trends in brain stimulation research, necessitating greater caution and fewer mechanistic assumptions as to how a given stimulation target or waveform will modulate a neurophysiological biomarker of disease. We also reveal that irregular stimulation patterns can have biomimetic utility, promoting their exploration in medical applications where inducing a particular activity pattern can have therapeutic benefit. Last, we demonstrate a scalable data-driven analysis strategy that can make the discovery of such physiologically informed temporal stimulation patterns more empirically tractable in translational settings.

neuroscience↗