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Patrizia Fattori

Full Professor

Department of Biomedical and Neuromotor Sciences

Academic discipline: BIO/09 Physiology

Research

Keywords: reaching movements superior parietal lobule eye-hand interaction grasping

 

1) Visuotopic, somatotopic and somatomotor organization: spatial distribution of neurons of posterior parietal cortex of non-human primates under visual, somatic and motor stimulations. Is it a distribution anatomically or functionally organized?
2) Visuo-motor integration in posterior parietal cortex: visual control of grasp action with extracellular recording techniques. Effect on the neuronal discharge of the spatial localization of the target, of ocular and limb movements.
3) Reach an object in the space: reach movement encoding, manipulation and role of posterior parietal cortex in the parieto-frontal circuits for movements encoding and on-line correction of the movements.
4) Digital processing in support of basic research: 2D and 3D reconstructions of brains and programming and simulation models of neural circuits involved in visuo-motor integration.

 

https://site.unibo.it/fattori-lab/en/research-interests-1/neural-circuits

 

 

 

1) Study of visual, somatic and motor representation in the posterior parietal cortex of non-human primates. Starting from the study of the bioelectric activity of neurons of the posterior parietal cortex (PPC) of non-human primates, using microelectrodic recordings, it is evaluated the spatial distribution of neurons studied on two-dimensional brain map. The aim of the research is to check the existence of ordered distributions (anatomic and/or functional) of neurons on the basis of their specific functional properties in order to verify the possible role of different clusters of cells and then of the cortical areas in which are located.


 

2) Visuo-motor integration in posterior parietal cortex. The study regards some areas of the PPC: area V6A and PEc. The aim of this study is to evaluate how this cortical region is involved in the visuo-motor control of superior limb movements to reach an object in peripersonal space. Microelectrodic recordings of bioelectric activity of single cell are executed. During experimental sessions visual and somatosensory stimulations are performed, the modulation of neuronal activity by oculomotor activity and superior limb motor activity, and the influence of different spatial localizations of the reach target are evaluated on the neural activity.

https://site.unibo.it/fattori-lab/en/research-interests-1/neuroscience-of-the-medial-ppc

 

 

 

 

3) Reaching an object in the peripersonal space. Bioelectric neural activity of PPC areas is strongly modulated by different type of movements finalized to reach and grasp objects in the peripersonal space. For example, the neural firing rate consequent reaching and/or grasping of “interesting” object (food) is different with respect a “not interesting” object (pliers). Again, reach and/or grasp objects with a certain shape and dimension requires a different way of grasping (type of opening of hand or rotation of specific joints). The anatomical study follows the functional study in order to outline the cortical circuit that involves the PPC. Injections of neuronal tracers are executed in the cortical areas functionally studied in order to identify the cortical connections and to clarify the cortico-cortical circuits for the coordination of gestures of prehension.

4) Digital processing to support basic research. The digital reconstruction of cerebral structures is a fundamental tool to visualize and therefore to compare results obtained with different methods (functional or anatomical) or by different experimental subjects (monkey or human). Such investigations simulate off-line the experimental sessions in order to obtain an overview of experiments. Together with these two- and three-dimensional brain reconstructions, mathematic and computer programming permit to simulate the neuronal events and the cortical circuits, to provide a neural out-put in response to a specific input decided by the experimenter, to verify “models” of neural network from experimental data acquired. This is a new and exciting horizon of neurophysiology with a great potential of application in the field of development of the artificial intelligence and robots.



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