No abstract

We present FGES-Merge, a new method for learning the structure of gene regulatory networks via merging locally learned Bayesian networks, based on the fast greedy equivalent search algorithm. The method is competitive with the state of the art in terms of the recall of the true structure while also improving upon it in terms of speed, scaling up to the tens of thousands of variables and being able to use empirical knowledge about the topological structure of gene regulatory networks. We apply this method to learning the gene regulatory network for the full human genome using data from samples of different brain structures (from the Allen Human Brain Atlas). Our goal is to develop a Bayesian network model that predicts interactions between genes in a way that is clear to experts, following the current trends in interpretable artificial intelligence. To achieve this, we also present a new open-access visualization tool that facilitates the exploration of massive networks and can aid in finding nodes of interest for experimental tests.

The dorsolateral striatum plays a major role in stimulus-response habits that are learned in the experimental laboratory. Here, we use meta-analytic procedures to identify the neural circuits activated during the execution of stimulus-response behaviours acquired in everyday-life and those activated by habits acquired in the laboratory. In the case of everyday-life habits we dissociated motor and associative components. We found that motor-dominant stimulus-response associations developed outside the laboratory engaged posterior dorsal putamen, supplementary motor area (SMA) and cerebellum. Associative components were also represented in the posterior putamen. Meanwhile, newly learned habits relied more on the anterior putamen with activation expanding to caudate and nucleus accumbens. Importantly, common neural representations for both naturalistic and laboratory based habits were found in posterior left and anterior right putamen. Our findings suggest a common striatal substrate for behaviours with significant stimulus-response associations, independently of whether they were acquired in the laboratory or everyday-life.