The research activity of Cristiano Cuppini mainly concerns the study of high-level cognitive processes through mathematical models, with the following aims:
- the study of the neural structures involved in these processes and their mechanisms;
- the formulation of predictions through the models, which can guide future experiments carried out to increase neurophysiological knowledge and validate the proposed mechanisms;
- the study of learning mechanisms that guide the maturation of cognitive abilities during the development of brain structures after birth, both in normotypical subjects and in subjects affected by cognitive disorders;
- the improvement of rehabilitation practices, through the development of trainings previously studied through computer simulations.
The research activity is carried out in collaboration with several research centers, as detailed in this document.
Below is a brief summary of the main research activities:
Neural networks for the study of sensory perception
In agreement with neurophysiological and psychophysical data, neural networks are developed to simulate and study how the brain perceives and analyzes sensory stimuli of different nature (visual, acoustic, tactile). In particular, neurocomputational models are realized to reproduce the brain mechanisms responsible both for the perception of the different sensory modalities (at the level of primary sensory areas), and for their interaction and integration, processes performed in different regions of the brain. The aim is to attain a theoretical understanding of the underlying neural mechanisms and to investigate how the properties of multisensory integration can be acquired and mature during the post-natal development and how they are strongly influenced by the sensory experience the subject is exposed to. Finally, these models are used to analyze the role of the multisensory perception in decision-making processes, such as the causal inference, and in rehabilitation, with trainings developed to compensate for the loss of specific perceptive capabilities (eg hemianopia). (Partnerships: Department of Neurobiology and Anatomy - Wake Forest University, Department of Pediatrics and Department of Neuroscience - Albert Einstein College of Medicine, UCLA Psychology Department, Center for Studies and Research in Cognitive Neuroscience - University of Bologna, Department of Psychology - University of Milan-Bicocca).
Neural mass models for the study of semantic, linguistic and decisional processes
Recent studies have highlighted how brain networks, distributed in different cortical areas, perform cognitive functions, such as object recognition, semantic memory, learning and language, and decision-making processes. In this context, the importance of the g-band oscillation activity (30-100 Hz) was highlighted during these processes. Through mathematical models, it is possible to understand the synchronization and desynchronization mechanisms that are established between groups of neural oscillators, the role played by such mechanisms in the recognition of objects and the link with the semantic and lexical memory. (Collaborations with the University of Rome "La Sapienza", IUSS).
Neural networks for the study of cognitive deficits
The knowledge obtained through simulations of perceptive (unisensory and multisensory) and cognitive processes (acquisition of semantic memory, linguistic and lexical abilities) in normotypical subjects are applied to the study of subjects with cognitive deficits (eg autism spectrum disorders, Alzheimer's and dementia semantics). The aim is to identify mechanisms responsible for the different process of acquiring these skills and to develop specific rehabilitation trainings for the each individual subject. (Collaborations with Department of Pediatrics and Department of Neuroscience - Albert Einstein College of Medicine, UCLA Psychology Department, University of Rome "La Sapienza", IUSS).
Models of the primary visual cortex
Models of the primary visual cortex are developed to reproduce the response to the orientation, speed and direction of the movement, according to the results present in the literature. These models are used to investigate the possible neural mechanisms underlying illusory sensory phenomena (temporal and spatial ventriloquism). (Collaboration with UCLA Psychology Department).
Analysis of electroencephalographic signals in epileptic patients
Specific Matlab software has been realized to analyze the EEG signal acquired in epileptic patients. The modulation of the blinking rate in the previous and subsequent instants of epileptic seizures is analyzed to identify the onset of the crisis. (Collaboration with the Department of Neurological Sciences - Bellaria Hospital).
