Showed that mice can rapidly generalize a spatial discrimination task between visual and tactile modalities1

Evidenced how task-related prior knowledge makes congruent-contingency transfers easy and incongruent hard1

Showed an extensive overlap of visual and tactile representations of space across the associative cortices1

Documented how multimodal neurons in these areas display nonlinear multisensory modulations supporting an amodal representation of sensory space1

Demonstrated the critical role of a highly multimodal dorsal cortical region in enabling cross-modal generalization1

Identified the key cortical pathways responsible for the sensorimotor transformation underlying a whisker discrimination task in mice1

Found that allostatic motivation levels deeply impact sensory encoding and task performance1

Showed that performance improvement across days reflect two distinct processes: the rapid formation of a sensorimotor association and slow improvements in motivational control1

Identified the neural correlates of a Yerkes-Dodson-like phenomenon in mice1

Identified neurons that encode motion direction regardless of the nature of the moving pattern2 

Showed that these pattern-invariant neurons are motion detectors similar to the ones in the primate brain2 

Demonstrated that rats perceive motion consistently with the properties of these pattern-invariant neurons1 

Found similar neurons in a self-supervised neural network model of the primate dorsal stream2 

Highlighted rats as promising model to study circuit mechanisms of motion perception1,2 

Developed a setup for carrying out controlled rearing experiments in rats that enables tight control of post-natal visual experience1 

Showed that rats raised in environments with disrupted temporal continuity of visual experiences exhibit decreased position-tolerant encoding of visual features in primary visual cortex1

Showed that the same experience doesn't affect the development of feature selectivity per se1

Provided the first direct neural evidence that early experience with smooth object transformation is key for the unsupervised learning of transformation tolerance1

Showed that the complexity of features encoded by neurons increase from primary to lateral visual cortex1

Showed that the position tolerance in the feature encoding increase in the same pathway1

Conducted a meta-analysis evidencing the same trend in the primate brain1

Identified the same trend across the layers of a computational model representing the primate ventral stream and in an artificial neural network trained for image classification1

Corroborated the functional homology of rat lateral extrastriate cortex and primate ventral stream1

1. Matteucci, G., Marotti, R. B., Riggi, M., Rosselli, F. B., & Zoccolan, D. (2019). Nonlinear processing of shape information in rat lateral extrastriate cortex. Journal of Neuroscience, 39(9), 1649-1670. 

Developed an automated method for laminar identification of cortical recording sites based on the temporal dynamics of evoked response potentials1

Validated the accuracy of the method in determining the cortical depth and laminar location of recording sites by comparing with ground-truth histological data1

Provided a fast and automated solution, alternative to manual annotation of histologies, to infer the laminar distribution of units recorded with multichannel silicon probes1

1. Matteucci G.*, Riggi M.*, Zoccolan D. A template-matching algorithm for laminar identification of cortical recording sites from evoked response potentials. J Neurophysiol. 2020 Jun 3;124(1):102–14.