Francesco Fumarola

"Bayesian anchoring" and the fourfold pattern of risk attitudes

This paper models decision-making under uncertainty using Bayesian anchoring to explain the fourfold pattern of risk attitudes and related effects observed in experiments.

Baseline control of optimal performance in recurrent neural networks

This study investigates how baseline modulations in recurrent neural networks control dynamical phases and achieve optimal performance without fine-tuning recurrent couplings.

Sparse balance: excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights

The paper introduces a new model of excitatory-inhibitory networks that generate asynchronous activity without requiring large bias currents, supported by sparse neuron activity and high-variance synaptic weights.

Predicting perturbation effects from resting state activity using functional causal flow

The paper develops a framework to predict the effects of neural perturbations using functional causal flow inferred from resting state activity in monkeys.

Common rules underlying optogenetic and behavioral modulation of responses in multi-cell-type V1 circuits

The paper investigates how optogenetic and behavioral inputs modulate V1 circuit responses, showing that specific interneurons stabilize the circuit and locomotion affects excitatory cells through direct drive.