Topic: connectome-constrained models

The brain of the fruit fly is well suited to study general principles of brain function, because it is small enough to be studied at the single-cell level and its connectivity is well known. This makes it possible to build mechanistic models with the same connectivity as the fruit fly brain, and to train them on tasks in order to constrain the free model parameters. It has recently been shown that such connectome-constrained ‘deep mechanistic network’ models (DMNs), when task-optimized to perform motion detection, can predict the tuning of single-cells in the fruit fly visual system and ca

Research efforts in mapping the connectivity of neural circuits has led to a wealth of connectomic data, including the full nervous system of the fruit fly. The dynamical characteristics of the neurons in these circuits, however, are still largely unknown. Recent work has demonstrated that connectome-constrained models with ethological task constraints generate accurate predictions of single-neuron response properties. Specifically, models with connectivity derived from the fruit fly visual system were trained using deep learning to perform a motion vision task. Resulting models accurately pre