Within the brain, our perception arises from a posh interplay of neurons which might be connected via synapses. However the number and strength of connections between certain sorts of neurons can vary. Researchers from the University Hospital Bonn (UKB), the University Medical Center Mainz and the Ludwig-Maximilians-University Munich (LMU), along with a research team from the Max Planck Institute for Brain Research in Frankfurt, as a part of the DFG-funded Priority Program “Computational Connectomics” (SPP2041), have now discovered that the structure of the seemingly irregular neuronal connection strengths accommodates a hidden order. This is important for the soundness of the neuronal network. The study has now been published within the journal “PNAS”.
Ten years ago, connectomics, that’s the creation of a map of the connections between the roughly 86 billion neurons within the brain, was declared a future milestone of science. It is because in complex neuronal networks, neurons are connected to one another by 1000’s of synapses. Here, the strength of the connections between individual neurons is vital since it is crucial for learning and cognitive performance. “Nonetheless, each synapse is exclusive and its strength can vary over time. Even experiments that measured the identical variety of synapse in the identical brain region yielded different values for synaptic strength. Nonetheless, this experimentally observed variability makes it difficult to seek out general principles underlying the robust function of neuronal networks,” says Prof. Tatjana Tchumatchenko, research group leader on the Institute of Experimental Epileptology and Cognitive Research of the UKB and on the Institute of Physiological Chemistry of the University Medical Center Mainz, explaining the motivation to conduct the study.
Mathematics and laboratory combined purposefully
In the first visual cortex (V1), the visual stimuli transmitted by the attention via the thalamus, a switching point for sensory impressions within the diencephalon, are first recorded. The researchers took a more in-depth take a look at the connections between the neurons which might be energetic during this process. To do that, the researchers measured experimentally the joint response of two classes of neurons to different visual stimuli within the mouse model. At the identical time, they used mathematical models to predict the strength of synaptic connections. To elucidate their lab-recorded activities of such network connections in the first visual cortex, they used the so-called “stabilized supralinear network” (SSN). “It’s one among the few nonlinear mathematical models that gives the unique possibility to match theoretically simulated activity with actually observed activity,” says Prof. Laura Busse, research group leader at LMU Neurobiology. “We were capable of show that combining SSN with experimental recordings of visual responses within the mouse thalamus and cortex allows us to find out different sets of connection strengths that result in the recorded visual responses within the visual cortex.”
Sequence between the connection strengths is the important thing
The researchers found that there was an order behind the observed variability in synapse strength. For instance, the connections from excitatory to inhibitory neurons were all the time the strongest, while the reverse connections within the visual cortex were weaker. It is because absolutely the values of synaptic strengths varied within the modeling – as that they had in the sooner experimental studies – but nevertheless all the time maintained a certain order. Thus, the relative ratios are crucial for the course and strength of the measured activity, relatively than absolutely the values.
It’s remarkable that evaluation of earlier direct measurements of synaptic connections revealed the identical order of synaptic strengths as our model prediction based on measured neuronal responses alone.”
Simon Renner, Ph.D., LMU Neurobiology
Renner’s experimental recordings of cortical and thalamic activity allowed characterization of the connections between cortical neurons. “Our results show that neuronal activity accommodates much information in regards to the underlying structure of neuronal networks that isn’t immediately apparent from direct measurements of synapse strengths. Thus, our method opens a promising perspective for the study of network structures which might be difficult to access experimentally,” explains Nataliya Kraynyukova, Ph.D., from the Institute of Experimental Epileptology and Cognitive Research of the UKB and Max Planck Institute for Brain Research in Frankfurt. This study is the results of an interdisciplinary collaboration between the lab of Prof. Busse and Prof. Tchumatchenko, who worked closely together, constructing on the computational and experimental expertise of their labs.
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Journal reference:
Kraynyukova, N., et al. (2022) In vivo extracellular recordings of thalamic and cortical visual responses reveal V1 connectivity rules. PNAS. doi.org/10.1073/pnas.2207032119.