A fascinating property of the brain is that a large number of parameters, ranging from the size of synapses to the power of extracellular currents, follow right-skewed and heavy-tailed distributions. Understanding whether this organization is hard-wired or it progressively emerges throughout ontogeny is of great importance. Does developmental learning fundamentally alter the structure of the brain? Or does it match pre-existing structure, initially devoid of any meaning, with a motor output or a sensory sensation? Here, we combine analytical approaches and spiking neural network modeling to provide converging evidence in support of the notion that functional and structural parameters are right-skewed and heavy-tailed from the very first days of life. This data thus suggest that this aspect of the brain architecture is preconfigured and not fundamentally altered by experience-dependent processes, as it is often assumed. These results provide a new perspective on how “nature over nurture” shapes brain development, a topic that has recently garnered a lot of attention in the field of biological and artificial intelligence alike.
Preconfigured Architecture of the developing mouse brain. Chini M, Hnida M, Kostka JK, Chen YN, Hanganu-Opatz IL. (2024). Cell Reports
