Circuit inference biased in strongly recurrent networks and a possible solution

Abhranil’s new paper is out! Congrats Abhranil.

We show that connectivity inference from activity in strongly recurrent networks will be systematically biased regardless of data volume and even given access to every neuron in the network. But measuring activity far-out-of equilibrium after a simple low-dimensional suppressive input could ameliorate the bias.

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