We propose to use a Gibbs free energy function as a measure of the human brain development. We adopt this approach to the development of the human brain over the human lifespan: from a prenatal stage to advanced age. We used proteomic expression data with the Gibbs free energy to quantify human brain's protein-protein interaction networks. The data, obtained from BioGRID, comprised tissue samples from the 16 main brain areas, at different ages, of 57 post-mortem human brains. We found a consistent functional dependence of the Gibbs free energies on age for most of the areas and both sexes. A significant upward trend in the Gibbs function was found during the fetal stages, which is followed by a sharp drop at birth with a subsequent period of relative stability and a final upward trend toward advanced age. We interpret these data in terms of structure formation followed by its stabilization and eventual deterioration. Furthermore, gender data analysis has uncovered the existence of functional differences, showing male Gibbs function values lower than female at prenatal and neonatal ages, which become higher at ages 8 to 40 and finally converging at late adulthood with the corresponding female Gibbs functions.

microRNA-9 (miR-9) is one of the most abundant microRNAs in the mammalian brain, essential for its development and normal function. In neurons, it regulates the expression of several key molecules, ranging from ion channels to enzymes, to transcription factors broadly affecting the expression of many genes. The neuronal effects of alcohol, one of the most abused drugs in the world, seem to be at least partially dependent on regulating the expression of miR-9. We previously observed that molecular mechanisms of the development of alcohol tolerance are miR-9 dependent. Since a critical feature of alcohol action is temporal exposure to the drug, we decided to better understand the time dependence of alcohol regulation of miR-9 biogenesis and expression. We measured the effect of intoxicating concentration of alcohol (20 mM ethanol) on the expression of all major elements of miR-9 biogenesis: three pri-precursors (pri-mir-9-1, pri-mir-9-2, pri-mir-9-3), three pre-precursors (pre-mir-9-1, pre-mir-9-2, pre-mir-9-3), and two mature microRNAs: miR-9-5p and miR-9-3p, using digital PCR and RT-qPCR, and murine primary medium spiny neurons (MSN) cultures. We subjected the neurons to alcohol based on an exposure/withdrawal matrix of different exposure times (from 15 min to 24 h) followed by different withdrawal times (from 0 h to 24 h). We observed that a short exposure increased mature miR-9-5p expression, which was followed by a gradual decrease and subsequent increase of the expression, returning to pre-exposure levels within 24 h. Temporal changes of miR-9-3p expression were complementing miR-9-5p changes. Interestingly, an extended, continuous presence of the drug caused a similar pattern. These results suggest the presence of the adaptive mechanisms of miR-9 expression in the presence and absence of alcohol. Measurement of miR-9 pre- and pri-precursors showed further that the primary effect of alcohol on miR-9 is through the mir-9-2 precursor pathway with a smaller contribution of mir-9-1 and mir-9-3 precursors. Our results provide new insight into the adaptive mechanisms of neurons to alcohol exposure. It would be of interest to determine next which microRNA-based mechanisms are involved in a transition from the acute, intoxicating effects of alcohol to the chronic, addictive effects of the drug.

A unique delayed self-inhibitory pathway mediated by layer 5 Martinotti Cells was studied in a biologically inspired neural network simulation. Inclusion of this pathway along with layer 5 basket cell lateral inhibition caused balanced competitive learning, which led to the formation of neuronal clusters as were indeed reported in the same region. Martinotti pathway proves to act as a learning "conscience," causing overly successful regions in the network to restrict themselves and let others fire. It thus spreads connectivity more evenly throughout the net and solves the "dead unit" problem of clustering algorithms in a local and biologically plausible manner.