This thesis will describe two functional Magnetic Resonance Imaging (fMRI) experiments and one Voxel-Based Morphometry (VBM) study, each investigating how the human brain identifies objects and their associated properties. In particular, we used three different categories of objects – living (animals), nonliving (tools and nontools) and faces (famous and non-famous) – to examine the type of knowledge attribute in question: one perceptual (movement) and two semantic attributes (typical object location and biographic knowledge). We know from neuropsychological literature that the most anterior portions of the temporal cortices critically support human conceptual knowledge. Unfortunately, the Anterior Temporal Lobe (ATL) is a challenging region for fMRI due to susceptibility artifacts, especially at high fields. For these reasons we established an optimized fMRI protocol (described in the second Chapter) by adjusting key acquisition parameters like phase-encoding gradient polarity, slice thickness, echo time, and slice angle. The protocol gave reliable Blood-Oxygen-Level Dependence (BOLD) signal sensitivity in the ATL. Clinical data describe patients with specific semantic impairments at the level of category (living, nonliving) as well as disproportionate deficits for a modality or type of knowledge (e.g., visual/perceptual knowledge or manipulation knowledge). Functional neuroimaging studies on semantic organization with normal subjects found an “action network†specific for tools rather than living items. In the first experiment (Chapter 3) we devised an fMRI paradigm to investigate the processing of movement (action) and place (encyclopedic) features, and their influence on category-specific activations. Within the “movement network†statistical analyses did not show any significant interaction between categories. These findings suggest that the visuomotor “action network†is not specific for tools because it is also activated when the action related knowledge is elicited for other categories, such as animals. The second and the third experiment (Chapter 4) focus on the processing of faces. Neuropsychological literature attributes semantic and lexical retrieval deficits in patients to ATL lesions. In Part I of Chapter 4, we report data from a VBM study on patients with known lesions in the temporal lobe. Unfortunately, as far as we know, data on patients and functional neuroimaging in healthy individuals has not clarified the differential role of this area in the two mental operations because semantic and lexical processes usually occur simultaneously and automatically. In Part II, we devised an event-related fMRI activation paradigm that allowed us to study the identification (i.e., association of semantic biographical information) of celebrities, with and without the ability to retrieve the proper name. While semantic retrieval reliably activated the ATL, only more posterior areas in the left temporal and temporal-parietal junction were significantly modulated by covert lexical retrieval. These results support findings from patients with ATL lesions and suggest that their anomia is due to semantic rather than lexical retrieval impairment.

This thesis stems from the need to implement the existing technology in the rehabilitation. Smartphones, touch screen technology, apps, which are a common part of our daily life don’t find an application in clinical practice. The aim of this work is to verify the effectiveness of using this technology both in the hospital and outside. The exergames we developed can be played on usual touchscreen devices, on personal computers and on the custom device built in our laboratory. The device used during our experimentation is now installed in a medical facility with other latest generation medical devices like the Armeo and two different types of exoskeletons. In the first part of this project we focused on developing some exergames oriented to the rehabilitation of persons affected by strokes and in the characterization of people affected by Parkinson. In the second part, because of the strong correlation between physical activity and neurocognitive functions we decided to use the device since the very beginning of the rehabilitation process, developing some kind of exergames used also to monitor patients during this phase. Thanks to the collaboration with the medical staff we analysed and summarized the macro areas and the neurocognitive functions involved during the rehabilitation process. After that, we analysed some of the usual exercises given to the patients highlighting the neurocognitive functions involved, and for each exercise we defined some indicators, like touch precision and its standard deviation, mean of force and its standard deviation, total time to execute the test, number of errors, etc... To develop the exergames based on what we decided with the medical staff we used the game engine called Unity3D and we wrote the code of the exergames in C#. After a first test phase in which the medical staff tried the exergames and gave us a feedback, we fixed the bugs and decided to integrate all the exergames in a common platform. Then, we defined an official procedure for the rehabilitation program based on this new method in order to submit it to the ethics committee. In a second phase, the medical staff selected the group of patients to be assigned to the test program, and defined some useful indicators about the neurocognitive functions involved. Finally, to validate the efficiency of this protocol, patients need to executed the exergames for a certain time, after which the medical staff measured the indicators. In this way we were able to validate the efficiency of the exergames and of the device installed. By working in the European project NoTremor we developed two different type of test with the aim of characterize a model of people affected by Parkinson.

Quantifying the amount of information communicated between neural population is crucial to understand brain dynamics. To address this question, many tools for the analysis of time series of neural activity, such as Granger causality, Transfer Entropy, Directed Information have been proposed. However, none of these popular model-free measures can reveal what information has been exchanged. Yet, understanding what information is exchanged is key to be able to infer, from brain recordings, the nature and the mechanisms of brain computation. To provide the mathematical tools needed to address this issue, we developed a new measure, exploiting benefits of novel Partial Information Decomposition framework, that determines how much information about each specific stimulus or task feature has been transferred between two neuronal populations. We tested this methodology on simulated neural data and showed that it captures the specific information being transmitted very well, and it is also highly robust to several of the confounds that have proven to be problematic for previous methods. Moreover, the measure was significantly better in detection of the temporal evolution of the information transfer and the directionality of it than the previous measures. We also applied the measure to an EEG dataset acquired during a face detection task that revealed interesting patterns of interhemispheric phase-specific information transfer. We finally analyzed high gamma activity in an MEG dataset of a visuomotor associations. Our measure allowed for tracing of the stimulus information flow and it confirmed the notion that dorsal fronto-parietal network is crucial for the visuomotor computations transforming visual information into motor plans. Altogether our work suggests that our new measure has potential to uncover previously hidden specific information transfer dynamics in neural communication.