**9. Final conclusions**

In this chapter, studies at the microcircuit histological level are remarked. There are many problems when jumping from the cellular/molecular level to the systems level without knowing what happens at microcircuit level when trying to understand how the brain works. The output seen at the systems level is the product of the microcircuits specific to each area, not of particular neurons or synapses; assumed in the cellular/molecular paradigm. To bridge the gap, analysis and perspectives from the microcircuit level are necessary [43, 69].

Using network analysis at the microcircuit level, it is observed that the striatal microcircuit has a set of highly connected hub neurons, which communicate efficiently with different neural groups. These groups underlie the neural states that alternate and reverberate. The structure of the striatal connectome has "small-world" properties, is scale-free and has a hierarchical modular organization, as other complex networks seen in nature. The cortical commands use the hub neurons to organize the dynamics of the circuit and given the distances between the neurons that conform a neuronal ensemble, it can be inferred that hub neurons should be long axon neurons, that is, interneurons. After striatal decortication or during the 6-OHDA model of Parkinson's disease hub neurons decrease significantly and as a consequence, the transitions between ensembles and circuit dynamics decrease, reflecting metaphorically hypokinesia and rigidity, and supporting previous studies that show a breakdown of corticostriatal communication in Parkinsonian subjects. In L-DOPA-induced dyskinesia, the opposite happens: the number of hub neurons and the transitions between ensembles increase. However, this occurs together with a loss of the hierarchical architecture. This also is reminiscent of the signs seen in dyskinetic subjects: uncoordinated involuntary movements. Finally, we conclude that the pathophysiology and pharmacology of the nervous system can be studied in living tissue at histological scale by using simultaneous recording and network analysis.
