Binding site affinity and transcription factor levels are finely tuned in nature to regulate stochastic expression, setting the ratio of alternative photoreceptor fates and determining color preference.
Stochasticity introduced computationally into a gene expression oscillator creates heterogeneity in the time of differentiation of identical cells and offers robustness to the progenitor state and the outcome of cell division.
The survival of Drosophila amacrine neurons is controlled by neurotrophic signaling mediated by interactions between the cell surface protein DIP-γ and its partner Dpr11, which is expressed on presynaptic photoreceptors.
Leave-One-Trial-Out (LOTO) is a general, efficient and easily implementable approach for inferring trial-by-trial measures of computational model parameters in order to link these measures to neural mechanisms.
Using iPSCs as a model to study neurodevelopmental differences between human and nonhuman primates lays the groundwork for understanding aspects of human brain evolution and neurological disease susceptibility.