Universität zu Köln

Jiang, Han-Jia ORCID: 0000-0002-9633-2573 (2025). Simulation studies of cortical microcircuitry incorporating multiple interneuron types and astrocytes. PhD thesis, Universität zu Köln.

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Abstract

The cerebral cortex is the center in the mammalian brain for high-level information processing and integration, which are supported by highly differentiated neurons and glial cells. To study cortical signal processing on the cellular level, methods such as microelectrode techniques are used to directly collect data from living cells. However, in such studies the quantity of sampled cells and the extent of manipulation (e.g., stimulation) in each experiment are limited. It is therefore necessary to complement experimental studies with computational models, which enable the systematic analysis of hypothetical neuronal networks and thereby provide testable predictions and directions for experiments. Such computational studies need models that are realistic but generalizable and efficient for simulation, as well as tools for standardized and reproducible model implementations. In this thesis, we develop computational models to study inhibitory interneurons and astrocytes in the cerebral cortex. Cortical interneurons differentiate to form molecularly distinguishable groups that show different inhibitory functions. Due to their diversity, it has been challenging to incorporate them in models of multi-layer cortical circuits for a systematic study. For this purpose, we developed a cortical column model incorporating three major interneuron subtypes with biologically plausible parameters based on experimental data of rodent somatosensory cortex. We incorporate synaptic short-term plasticity of the interneurons in our model and examine its role in network dynamics. The simulation results show that the short-term plasticity can modify population responses to transient cell-type-specific external inputs, likely by shifting the balance between inhibitory pathways. We also implement a somatosensory input based on touch-evoked thalamic activity in vivo and examine the induced cortical cell-type-specific responses in our model. We find that simulations with the original model partly reproduce the in vivo data, whereas slight adjustment of a few model parameters leads to a further improved match with the experimental results. The computational study of astrocytes has established models that describe experimentally observed astrocytic dynamics. To study large-scale neuron-astrocyte interactions, however, simulation tools compatible with high-performance computing are required. To fill this gap, we developed a set of standardized simulation methods based on existing astrocyte models and glutamatergic neuron-astrocyte interactions. In this development, we further introduced a new algorithm for building tripartite neuron-astrocyte connections. This algorithm is compatible with common connectivity rules in neuronal networks and includes parameters to define various neuron-astrocyte connectivity schemes. We verify the efficiency of our implementation with performance benchmarks and validate its scientific use with a simulation study to reproduce an experimentally observed astrocyte-promoted neuronal synchrony. The results show a good simulation performance with parallel computing and an astrocytic effect robust against changes in connectivity pattern and network activity. Our development supports efficient and reproducible simulations of large-scale neuron-astrocyte networks. In conclusion, the results of our work predict network dynamics in the presence of interneuron subtypes and astrocytes. These results can be further explored by experiments and extensions of our models. Through the developed models and software, our work brings new tools for future studies in the same direction to discover functions of the associated cell diversities in the brain.

Item Type:	Thesis (PhD thesis)
Creators:	Creators Email ORCID ORCID Put Code Jiang, Han-Jia hjiang2@smail.uni-koeln.de https://orcid.org/0000-0002-9633-2573 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-790985
Date:	2025
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Biology > Zoologisches Institut
Subjects:	Data processing Computer science Natural sciences and mathematics Life sciences
Uncontrolled Keywords:	Keywords Language inhibitory neurons English spiking neuronal network English short-term synaptic plasticity English barrel cortex English thalamocortical English astrocyte English NEST simulator English neuron-astrocyte interaction English calcium dynamics English glia English connectivity English
Date of oral exam:	6 October 2025
Referee:	Name Academic Title van Albada, Sacha J. Prof. Dr. Nawrot, Martin Prof. Dr.
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/79098