The secret structure in the brain wiring diagram of PNAS

In the brain, our perception comes from complex interactions between neurons that are connected together
by synapses.
But the number and strength of connections between certain types of neurons are different
.
Researchers from the University Hospital Bonn (UKB), the University Medical Center Mainz and the Ludwig-Maximilian-Munich University (LMU), as well as a team from the Max Planck Institute for the Brain in Frankfurt, have now discovered that the structure of seemingly irregular neuronal connection strength contains a hidden sequence
.
This is essential
for the stability of neural networks.
The study has been published in
PNAS.

A decade ago, connectomics, which maps the connections between the roughly 86 billion neurons in the brain, was declared a milestone
for future science.
This is because in a complex network of neurons, neurons are connected
by thousands of synapses.
Here, the strength of the connections between individual neurons is important because it is critical
for learning and cognitive performance.
"However, each synapse is unique, and its intensity changes
over time.
Even experiments measuring the same type of synapse in the same brain region have yielded different synapse strength values
.
However, the variability observed by such experiments makes it difficult to find the rationale for the robust functioning of neural networks," says Professor Tatjana Tchumatchenko, who is head of the research team at the Institute of Experimental Epilepsy and Cognitive Research at Royal Roads University and the Institute of Physiological Chemistry at the University Medical Centre Mainz, explaining the motivation
for conducting the study.

Math and laboratory are purposefully combined

In the primary visual cortex (V1), visual stimuli transmitted by the eye through the thalamus (the switching point of sensory impressions in the diencephalon) are first
recorded.
The researchers took a closer look at the connections between neurons active in the
process.
To do this, the researchers experimentally measured the combined responses
of two types of neurons to different visual stimuli in a mouse model.
At the same time, they used mathematical models to predict the strength of
synaptic connections.
To explain the activity of this network connection in the primary visual cortex they recorded in the lab, they used so-called "stable superlinear networks" (SSNs).

"This is one of the few nonlinear mathematical models that offers the unique possibility of comparing activities simulated in theory with those observed in practice," says
Professor Laura Busse, head of the LMU neurobiology research group.
"We were able to demonstrate that combining SSN with experimental recordings of visual responses in the thalamus and cortex of mice allowed us to determine the different sets of connection intensities that lead to visual responses recorded in the
visual cortex.
"

The order between the strength of the connection is key

The researchers found that there was an order behind the observed changes in synaptic strength
.
For example, the connection from excitatory neurons to inhibitory neurons is always the strongest, while the reverse connection of the visual cortex is weaker
.
This is because the absolute value of synaptic strength varies during modeling—as they did in earlier experimental studies—but always in a certain order
.
Therefore, relative ratios are critical for measuring the process and intensity of activity, not absolute values
.
Dr Simon Renner, of LMU's neurobiology, said: "Analysis of early direct measurements of synaptic connections shows that the order of synaptic intensity is the same as our model predictions based solely on measured neuronal
responses, which is noteworthy.
" His experimental documentation of cortical and thalamic activity allows to describe the connections
between cortical neurons.
"Our results show that neuronal activity contains a wealth of information about the underlying structure of neuronal networks that is not immediately apparent from direct measurements of synaptic strength
.
" Our approach therefore opens up a promising prospect for the study of network structures that are difficult to obtain experimentally," explains
Dr.
Nataliya Kraynyukova from the Institute for Experimental Epilepsy and Cognitive Research of the British Academy of Sciences and the Max Planck Institute for the Brain in Frankfurt.
The research is the result of an interdisciplinary collaboration between Prof.
Busse and Prof.
Tchumatchenko's labs, who work closely together and build on
the computational and experimental expertise of their labs.

In vivo extracellular recordings of thalamic and cortical visual responses reveal V1 connectivity rules