CNS*2026 Halifax

Introduction
The processing of tactile stimuli relies on complex dynamics within cortical microcircuits. Near the perceptual threshold, unperceived stimuli evoke somatosensory responses that differ from perceived ones, a phenomenon extensively studied with EEG [1]. However, the neural mechanisms underlying this transition are poorly understood. Neural mass models are a tool to describe dynamics of cortical circuits and give a mechanistic understanding of their functions. Here, we present such a model to investigate these unknown dynamics.


Methods
The model consists of two cortical columns representing the primary and secondary somatosensory cortex, each with granular, supra-, and infra-granular layers. It includes pyramidal neurons and interneuron populations of three different types (somatostatin-, parvalbumin-, and vasoactive-intestinal-peptide-expressing interneurons). Mean firing rate and membrane potential are defined based on the Jansen-Rit model [2]. Connectivity, cell counts and synaptic properties are obtained from animal studies and previous models [3,4].


Results
Our approach reveals the characteristics of the somatosensory microcircuit dynamics with respect to model parameters. The model allows for precise predictions of how connectivity pattern and excitation-inhibition balance of each neuronal population shapes its individual functional role in generating tactile evoked responses and in letting input pass to higher cortical areas, reflecting the perception of the tactile stimulus. In combination with feedforward bottom-up input, top-down input from higher areas influences perceptual gating. An observation model transforms firing rates and membrane potential into EEG- and LFP-like signals, allowing future fitting to real recordings to improve interpretability and validity.


Discussion
Our model offers a biologically plausible approach to investigate somatosensory perception. It provides hypothetical mechanisms underlying the processing of tactile stimuli and the transition from subliminal to supraliminal responses. By bridging the gap between macroscopic measurements and microscopic neural dynamics, this model enhances our understanding of the mechanisms underlying tactile perception at multiple levels. Future work will fit the model to empirical data from near-threshold detection tasks.


References

1. Forschack, N., Nierhaus, T., Müller, M. M., & Villringer, A. (2020). Dissociable neural correlates of stimulation intensity and detection in somatosensation. NeuroImage, 217, 116908.
   
2. Jansen, B. H., & Rit, V. G. (1995). Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biological Cybernetics, 73(4), 357–366.
   
3. Isbister, J. B., Ecker, A., Pokorny, ... & Reimann, M. W. (2024). Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part II: Physiology and Experimentation. bioRxiv.
   
4. Jiang, H.-J., Qi, G., Duarte, R., Feldmeyer, D., & Albada, S. J. van. (2023). A Layered Microcircuit Model of Somatosensory Cortex with Three Interneuron Types and Cell-Type-Specific Short-Term Plasticity. bioRxiv.

Acknowledgement
This work was supported by the IMPRS programs. We thank the members of our group BrainNets  and the Neurology department for insightful discussions and continuous feedback. We are also grateful to previous interns who contributed to preliminary simulations.