Hidden structures in the brain’s wiring diagram


Researchers discover order in supposedly random connections between nerve cells

Our perception is formed in the brain through a complex interplay of nerve cells that are connected to each other via synapses. The number and strength of the connections between certain types of neurons can vary.

Scientists from the University Hospital Bonn (UKB), the University Medical Center Mainz, the Ludwig-Maximilians-University Munich (LMU) and a research team from the Max Planck Institute for Brain Research in Frankfurt have discovered within the framework of the DFG-funded Priority Programme “Computational Connectomics” (SPP2041) that the structure of the supposedly irregular neuronal connection strengths contains a hidden order. This order is essential for the stability of the neuronal network. The results of this study were recently published in the scientific journal “PNAS”.

Already called a milestone in science 10 years ago: Connectomics.

Connectomics, the creation of a map of the connections between the approximately 86 billion nerve cells in the brain, was described ten years ago as a future milestone in science. In complex neuronal networks, neurons are connected by thousands of synapses. The strength of connections between neurons is crucial, as it is responsible for learning and cognitive performance.

“Each synapse is unique and its strength can vary over time. Even in experiments in which the same type of synapse was studied in the same brain region, different values for synaptic strength were revealed. This experimentally observed variability makes it difficult to identify general principles underlying the stable function of neuronal networks”, explains Prof. Dr. Tatjana Tchumatchenko, head of a research group at the Institute for Experimental Epileptology and Cognitive Research of the UKB and at the Institute for Physiological Chemistry of the University Medical Center Mainz, the motivation for conducting the study.

Using target-oriented combinations thanks to the interplay of mathematics and the laboratory

The primary visual cortex (V1) receives visual stimuli that are transmitted from the eye via the thalamus – a switching point for sensory impressions in the diencephalon. As part of the study, the researchers investigated the active connections between the neurons. They experimentally measured the joint response of two classes of neurons to different visual stimuli in the mouse model and simultaneously used mathematical models to predict the strength of synaptic connections.

To explain the laboratory-recorded activities of these network connections in the primary visual cortex, they used the so-called “stabilised supralinear network” (SSN). “It is one of the few non-linear mathematical models that offers the unique possibility to compare theoretically simulated activity with the actually observed activity”, explains Prof. Dr. Laura Busse, head of a research group at LMU’s Department of Neurobiology. “We were able to show that combining SSN with experimental recordings of visual responses in the mouse thalamus and cortex allows us to determine different sets of connection strengths that lead to the recorded visual responses in the visual cortex.”

Ordering between connection strengths as a key module.

The researchers discovered that there was a previously hidden order behind the observed variability in synaptic strength. For example, connections from excitatory to inhibitory neurons were always strongest, while the reverse connections were weaker in the visual cortex. Although the absolute values of synaptic strengths varied in the modelling – similar to previous experimental studies – they nevertheless always maintained a certain order. The relative ratios are thus crucial for the course and strength of the measured activity, not the absolute values.

“It is remarkable that the analysis of previous direct measurements of synaptic connections yielded the same order of synaptic strengths as our model prediction based solely on measured neuronal responses,” says Dr. Simon Renner from LMU Neurobiology. His experimental recordings of cortical and thalamic activity enabled the characterisation of the connections between cortical neurons.

“Our results show that neuronal activity contains a lot of information about the underlying structure of neuronal networks that is not immediately apparent from direct measurements of synapse strengths. Thus, our method opens up a promising perspective for the investigation of network structures that are difficult to access experimentally”, explains Dr. Nataliya Kraynyukova from the Institute for Experimental Epileptology and Cognitive Research of the UKB and Max Planck Institute for Brain Research in Frankfurt. The study is the result of an interdisciplinary collaboration between the labs of Prof Busse and Prof Tchumatchenko, who worked closely together, drawing on the computational and experimental expertise of their labs.

Crucial role for stability and function of neuronal networks.

From these findings, it can be concluded that despite the observed variability in the strength of synapses, a hidden order exists in the brain. This order plays a crucial role in the stability and function of neural networks. The discovery that the relative ratios of synaptic strengths are more important than the absolute values offers a new perspective for understanding neuronal activity and the underlying network structures.

The combination of experimental methods and mathematical models, as applied in this study, makes it possible to better explore the structure and function of neuronal networks and to investigate potentially difficult-to-access network structures. In the long term, these results could contribute to improved methods for the study and treatment of neurological diseases associated with neural network disorders.

The study also demonstrates the potential and benefits of interdisciplinary collaboration between different research fields, such as in this case neurobiology, epileptology, cognitive research and mathematics, to answer complex scientific questions in the field of neuroscience.


Nataliya Kraynyukova*, Simon Renner*, Gregory Born, Yannik Bauer, Martin Spacek, Georgi Tushev, Laura Busse**, and Tatjana Tchumatchenko** [* shared first author; ** shared senior author]: In vivo extracellular recordings of thalamic and cortical visual responses reveal V1 connectivity rules; PNAS; 2022