Imagine you’re putting together a complex puzzle, combining pieces from different sets to create a unique masterpiece. Well, scientists have done something similar by developing a large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE. Just like a puzzle, they carefully assembled information from various experimental studies to construct this intricate model. NetPyNE, a user-friendly tool, allowed them to simulate and analyze the model’s behavior, making it more accessible and simpler to explore. By incorporating anatomical and physiological data, the model successfully replicated the original cell morphologies and connectivity properties. It even produced physiological firing rates and patterns similar to real neural activity. But they didn’t stop there—additional experiments were conducted, altering factors like extracellular calcium concentration to mimic different states of brain activity. These manipulated simulations validated the original study and demonstrated their modeling tool’s capabilities. To enhance the model’s realism, thalamic circuits were included, replicating the dynamics of thalamic populations and their interactions with the cortex. This comprehensive model is now available for researchers to investigate neural dynamics, function, and disease in the somatosensory system. So grab your scientific curiosity and delve into the fascinating world of somatosensory TC circuits with this incredible research!

The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. When STP was included, the network generated a 1 Hz oscillation comparable to the original model in vitro-like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 in vivo-like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical (TC) and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of TC interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory TC circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease.

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