Unknown

Dataset Information

0

Predicting individual neuron responses with anatomically constrained task optimization.


ABSTRACT: Artificial neural networks trained to solve sensory tasks can develop statistical representations that match those in biological circuits. However, it remains unclear whether they can reproduce properties of individual neurons. Here, we investigated how artificial networks predict individual neuron properties in the visual motion circuits of the fruit fly Drosophila. We trained anatomically constrained networks to predict movement in natural scenes, solving the same inference problem as fly motion detectors. Units in the artificial networks adopted many properties of analogous individual neurons, even though they were not explicitly trained to match these properties. Among these properties was the split into ON and OFF motion detectors, which is not predicted by classical motion detection models. The match between model and neurons was closest when models were trained to be robust to noise. These results demonstrate how anatomical, task, and noise constraints can explain properties of individual neurons in a small neural network.

SUBMITTER: Mano O 

PROVIDER: S-EPMC8741219 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Predicting individual neuron responses with anatomically constrained task optimization.

Mano Omer O   Creamer Matthew S MS   Badwan Bara A BA   Clark Damon A DA  

Current biology : CB 20210728 18


Artificial neural networks trained to solve sensory tasks can develop statistical representations that match those in biological circuits. However, it remains unclear whether they can reproduce properties of individual neurons. Here, we investigated how artificial networks predict individual neuron properties in the visual motion circuits of the fruit fly Drosophila. We trained anatomically constrained networks to predict movement in natural scenes, solving the same inference problem as fly moti  ...[more]

Similar Datasets

| S-EPMC1994056 | biostudies-literature
| S-EPMC8288090 | biostudies-literature
| S-EPMC6196076 | biostudies-literature
| S-EPMC4586264 | biostudies-literature
| S-EPMC7116674 | biostudies-literature
| S-EPMC6602545 | biostudies-literature
| S-EPMC10039274 | biostudies-literature
| S-EPMC10123273 | biostudies-literature
| S-EPMC8184210 | biostudies-literature
| S-EPMC6416771 | biostudies-literature