P060 Neural Dynamics and Non-Linear Integration: Computational Insights for Next-Generation Visual Prosthetics
Tanguy Damart*1, Jan Antolík1
1Faculty of Mathematics and Physics, Charles University, Prague, The Czech Republic
*Email: tanguy.damart@protonmail.com Introduction
Eliciting percepts akin to natural vision using brain computer interfaces is the holy grail of vision prosthetics. However, progress has been slowed by our lack of understanding of how external perturbations, such as electrical stimulation via multi-electrode arrays (MEAs), might perturb the recurrent cortical dynamics and engage the inherent visual representations embedded in the cortical circuitry. Furthermore, investigating these questions directly remains difficult as we rarely have the opportunity to probe the human cortexin-vivo. From this limitation and thanks to the current exponential increase in computing capabilities, modeling and simulation tools naturally came to complement experimental studies. Methods We present here a model of intracortical microstimulation (ICMS) applied to a model of columnar primary visual cortex (V1) [1]. The V1 model, built from point neuron models, contains functional retinotopy and orientation maps which are both essential for studying the interaction between external drives such as ICMS and structured spontaneous dynamics. The ICMS is modeled through a phenomenological representation of a MEA that, when activated, causes ectopic spikes in the surrounding cells. The model reproduces two key features of ICMS: sparse and distributed recruitment of neurons, and ectopic spike induction in activated neurons. Results We demonstrate that our model reproduces the stereotypical dynamics in V1 seen as a response to ICMS: a transient excitation followed by a lasting inhibition. Comparing the population activity induced by ICMS to the one induced as a response to drifting gratings, we show that ICMS targeting specific orientation columns moderately biases the population activity toward a representation of this orientation. Activating multiple electrodes leads to a slight increase in that orientation bias and produces non-linear activation that could not be predicted by simply adding single-electrode effects. Finally, training a decoder model on responses of the model to natural images, we are also able to show what activity induced by ICMS looks like. Discussion Current visual prosthetics rely on phosphene-based encoding through intracortical microstimulation, but this approach underutilizes the complex dynamics of the visual cortex. By investigating how ICMS-induced activity in V1 relates to natural visual activity, we show that current ICMS methods are unlikely to produce anything other than phosphenes and that the non-linear spatio-temporal integrative properties of V1 could be leveraged to enhance visual prosthetic outcomes beyond the resolution limitations of current multi-electrode arrays. The computational framework we developed also enables systematic exploration of stimulation parameters without invasive procedures, such as the development of closed-loop stimulation protocols.
Acknowledgements The publication was supported by ERDF-Project Brain dynamics, No. CZ.02.01.01/00/22_008/0004643. References 1. https://doi.org/10.1371/journal.pcbi.1012342
