Combination of deep learning models trained on tissue-specific genomic data and fine-mapping approaches supports efforts to identify causal variants and mechanisms at GWAS loci.

Systematic quantification of abdominal organ health parameters using deep learning generates new insights into the genetic architecture of cardiometabolic health traits.

Using sequence-determined functional genomic features instead of original genotypes can partially overcome challenges in genetic association studies, such as rare variant exclusion and population structure.

Drosophila flies infer value to olfactory stimuli based on the previously repeatedly presented associative structure between two odorants.

Applying computational modeling to quantify threat learning processes uncovers how variations in these conserved learning processes relate to anxiety severity and the neuroanatomical substrates moderating these associations.

In monkeys, the integrity of the magnocellular subdivision of mediodorsal thalamus is important when using recent rewarded choices to promote persistence with a recently sampled choice during changing or uncertain reward guided-learning and decision-making tasks.

Rats learn to interpret cues predicting rewards delivered to social partners as valuable, but only if social information exchange is possible.

Cross-modal stimuli are represented in the primary gustatory cortex according to their sensory identity, associability and predictive value.

The role of CaMKII-GluA1 in the cortex in maintaining a given taste memory trace for an aversive association has been elucidated.

Taking advantage of awell-established learning paradigm, conditioned taste aversion (CTA), change of hedonic value of a palatable tastant revealed the neural mechanisms encoding this learning process.