Neural circuits

Brain networks or circuits that are active in the resting state and their temporal profile

The brain consists of neural networks or circuits (macrocircuits and microcircuits), which are groups of neurons that are connected and fire in a coordinated manner to perform specific functions. By firing we mean that they generate action potentials which correspond to peaks of electric voltage and to associated electric currents. These are propagated along the neuron and from one neuron to the other.

Below is featured the publication by Vidaurre et al (2017) https://www.pnas.org/doi/10.1073/pnas.1705120114 and specifically Figure 1.

First of all, how many different networks are there in the resting state? Or more generally, how many components or states can we distinguish? If we acquire brain activity data, we will notice that there is activation of different brain areas in different time points. Is there some kind of pattern? A model is used to find if there is a hidden pattern in the activation. In other words, the model will try to distinguish hidden components or states. The model used is termed a Hidden Markov Model or HMM, named after the mathematician that postulated it.

In the cited study, the model determined that there are 12 different components or states that repeat themselves in time.

A time course of 60 seconds is presented in Figure 1.

It is noted that the y axis is the probability of activation provided by the model. 

The scientists then analyzed which networks are associated with the activated areas.

They found for instance that state 6 corresponds to the default-mode network, state 9 to the language network and state 4 to the visual network.

By examining the figure, we may determine at which time point each network is activated. (E.g. approximately 15 seconds for the default-mode network).