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Single-Cell and Population-Level Neuromodulation Dynamics in Dual-Electrode Intracortical Stimulation

Kim, K.; Sonego, V.; Strohmer, B.; Chang, B.; Liu, X.; Yonza, A. K. I.; Kucharz, K.; Asiminas, A.; Lind, B. L.; Tao, L.; zhang, X.; Fried, S.; Han, A.; Cai, C.

2025-06-25 neuroscience
10.1101/2025.06.25.661479 bioRxiv
Show abstract

In neuroprosthetics, intracortical microstimulation (ICMS) recruits cortical networks to evoke brain responses and sensory perceptions. However, multi-electrode ICMS often generates suboptimal percepts compared to single-electrode ICMS, suggesting nonlinear neuromodulation rather than simple summation by multi-electrode ICMS. Yet, the factors and mechanisms underlying this modulation remain poorly understood. To investigate multi-electrode ICMS, we combined two-photon calcium imaging with a well-controlled dual-electrode ICMS in the mouse visual cortex to investigate how neurons integrate converging ICMS inputs at varying intensities. We found that stimulation intensity significantly shapes neuromodulation at both single-cell and population levels. Specifically, low intensities (5-7 {micro}A) have a minimal effect on neural responses. At intermediate intensities (10-15 {micro}A), we observed diverse, nonlinear bipolar modulation--both enhancement and attenuation--at the single-cell level. However, we achieved net enhancement at the population level. At higher intensities (15-20 {micro}A), although the proportion of modulated neurons increased in both enhancement and attenuation directions, the net effect at the population level was neutral (zero modulation). Furthermore, neurons strongly responsive to single-electrode ICMS were more likely to be attenuated, while weaker responding cells exhibited enhanced modulation. The strongest neuromodulatory effects occur at intermediate spatial distances in between the two electrodes. Computational modeling based on spiking neural network composed of adaptive exponential integrate-and-field neurons implicated the importance of inhibitory network dynamics and network variability as key mechanisms. Our experimental data was used to train an advanced deep learning approach, which successfully predicted the neuromodulation patterns induced by dual-electrode ICMS. Our findings reveal intensity- and spatial-dependent rules of neuromodulation by ICMS, providing necessary insights to optimize multi-electrode ICMS for neuroprosthetic applications. Significance statementUnderstanding how cortical neurons integrate concurrent inputs from multi-electrode intracortical microstimulation (ICMS) is essential for advancing neuroprosthetic technologies. We show that dual-electrode ICMS evokes distinct, predictable neuromodulatory effects that depend on (i) stimulation intensity, (ii) a neurons baseline responsiveness to single electrode input, and (iii) its proximity to the electrodes. Low and intermediate intensity dual-electrode ICMS amplifies neural activity compared to single-electrode ICMS, whereas high-intensity stimulation leads to attenuation, limiting net activation.

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