Simone Blanco Malerba

The paper shows that cortical excitability inversely affects fMRI connectivity, with low-frequency neuronal coupling being the key driver of these changes.

The paper investigates whether cortical neurons projecting to the same target form specialized population codes, finding structured correlations that enhance information transmission during correct behavioral choices.

This study shows that efficient coding principles can explain key properties of excitatory-inhibitory neural networks, including their connectivity and balance of excitation and inhibition.

The paper shows that irregular neural responses can achieve efficient coding without fine-tuning, using a random synaptic network model and monkey motor cortex data.

This paper introduces a framework combining encoding and decoding in neural populations using variational autoencoders, showing that models with broad tuning curves achieve accurate stimulus reconstruction and generalization.

The paper develops bias correction methods for Partial Information Decomposition (PID) in neural data, improving estimates of synergy and redundancy in mouse brain regions.