Reasearch Areas

Automatic and Deliberate control of action (electrophysiology)

Some actions are taken volitionally while many others are controlled by automatic routines. How does the human brain orchestrate these two modes? I attempt to answer this question by applying statistical and machine learning methods to neural time series recorded from human subjects implanted with intracortical electrodes and use these insights to classify and predict behavior.

For more info: Maffei, G., Puigbo, J., Santos-Pata, D., Zucca, R., Principe, A., Tauste-Campo, A., Rocamora, R., Conesa, G., Verschure, P. (2018). Theta phase modulates deliberate action switch in human Supplementary Motor Areas (in preparation) pre-print soon

Sensory-motor learning and motor adaptation (computational)

When playing sports, such as football, acting in anticipation is key. What are the learning mechanisms underlying this ability? I design predictive control algorithms that implement neural networks based on the anatomy and physiology of the animal cerebellum and basal ganglia. Through the analysis of their learning dynamics and performance within motor adaptation tasks, I attempt to extrapolate the computational principles underlying the control of anticipatory actions.

For more info: Maffei, G., Herreros, I., Sanchez-Fibla, M., Friston, K. J., & Verschure, P. F. (2017). The perceptual shaping of anticipatory actions. In Proc. R. Soc. B. The Royal Society. article here

Newspaper article covering the project

Cognitive architectures and Neuromorphic control (neuro-robotics)

In order to really understand the brain, we should be able to replicate its fundamental control and learning principles in artificial systems, such as robots. I contribute to this fascinating challenge by studying the system level interactions across brain areas with the goal to implement cognitive architectures that overcome current limitations in artificial intelligence systems and to equip machines with real-world adaptive abilities.

For more info: Maffei, G., Santos-Pata, D., Marcos, E., Sánchez-Fibla, M., & Verschure, P. (2015). An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X. Neural Networks, 72, 88-108. article here

Newspaper article covering the project

Clinical diagnitic tools (behavioral)

The knowledge of the computational principles underlying behavior can find concrete applications in clinical setups. I apply the key insights on decision making, predictive control and motor adaptation to diagnostic tools that can detect the disruption of learning mechanisms in syndromes such as autism, or medical conditions such as addiction.

For more info: Maffei, G., Blancas, M., Vouloutsi, V., Verschure, P. “Measuring collaboration in a predictive game task: a comparison between autistic and neurotypical individuals using the Point of Social Subjective Equality” (in preparation) pre-print soon

European Union founded projects


CC Giovanni Maffei (2018) - Original design by Ankit Sultana