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Our brain has the ability to dynamically reconfigure its neural circuitry to correctly process incoming stimulation and promote correct responses to it. In this way, the brain can function both in a localized and integrated way, as the case may be.
In addition, this mechanism prevents the development and continued destruction of physical connections, thereby promoting efficiency and optimizing energy expenditure. This mechanism, up to now, was a mystery to science; However, recently, a team of researchers has designed neural circuits in vitro from what has been done to reproduce these complex brain functions. In short, this advance promotes understanding of the process of dynamic brain reconfiguration.
The neural circuits can operate in an integrated or separate manner, depending on the case.
The dynamic integration of neural circuits is associated with the rapid exchange of information between neural networks that can be located in very far and different places from each other. On the other hand, neuronal segregation involves the processing of information in localized neural networks; our brain can work both ways, that is to say that it can go from a state of segregation to an integrated state depending on the nature and the intensity of the perceived stimuli. This mechanism prevents the creation and continuous destruction of physical connections, optimizing the use of energy and increasing the efficiency of operation.
Thus, for example, the stimuli we perceive through sight, hearing and smell are treated separately in different areas of the brain and then integrated in one way or another. Another, if necessary.
By way of illustration, when we watch television, visual and auditory stimuli are integrated, to the detriment of the olfactory; However, when we perceive the smell of something burning, our brain goes into alertness, integrating and analyzing as much information as possible to make the best decisions.
Until now, the biophysical bases of the mechanisms of integration and segregation were not fully understood; in the same vein, it was unclear to what extent the dynamic reconfiguration of neural circuits depended on the amount of physical connections between different brain structures.
Connections between modules determine the dynamic reconfiguration of neural circuits
In order to study the process of reconfiguration of brain dynamics, a team of scientists developed an in vitro brain model consisting of four modules connected to each other. each module represents a specialized neural circuit. In addition, the modules are coated with adhesive proteins, in addition to nutrients, to promote neuronal development and cell-to-cell connections, both in each module and between modules. In the video below, we can see the model in full operation:
To control the neural connections between the modules, the researchers used precision neuroengineering techniques. In this way, it was possible to control the physical coupling between the modules. On the other hand, neuronal activation was assessed on the basis of fluorescence microscopy techniques of calcium. In this way, it was possible to study the ability of the circuit to integrate or segregate spontaneously depending on several factors.
In this way, it has been discovered that the neural circuits can be integrated or permanently separated, depending on the magnitude and the number of connections between the modules. Specifically, an optimal circuit is a circuit in which the four modules have connectivity below the minimum necessary for integration; this means that the impulses of neuronal activity are sufficient to punctually strengthen the connections and complete the integration.
In this way, the neural circuits operate in a regime of coexistence between segregation and integration. However, researchers suggest that this dynamic is excessively simple compared to what is expected of a real brain; nevertheless, the results open the way to understanding the dynamics of brain function.
Reference: Impact of modular organization on dynamic richness in cortical networks (2018). https://www.doi.org/10.1126/sciadv.aau4914
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