Models for the study of neuronal activity during cognitive tasks

Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this research study is to use neural mass models to assess the effect of various connectivity patterns in cortical EEG power spectral density (PSD), and investigate the possibility to derive connectivity circuits from EEG data. To this end, two different models have been built. In the first model an individual region of interest (ROI) has been built as the parallel arrangement of three populations, each one exhibiting a unimodal spectrum, at low, medium or high frequency. Connectivity among ROIs includes three parameters, which specify the strength of connection in the different frequency bands. Subsequent studies demonstrated that a single population can exhibit many different simultaneous rhythms, provided that some of these come from external sources (for instance, from remote regions). For this reason in the second model an individual ROI is simulated only with a single population. Both models have been validated by comparing the simulated power spectral density with that computed in some cortical regions during cognitive and motor tasks. Another research study is focused on multisensory integration of tactile and visual stimuli in the representation of the near space around the body (peripersonal space). This work describes an original neural network to simulate representation of the peripersonal space around the hands, in basal conditions and after training with a tool used to reach the far space. The model is composed of three areas for each hand, two unimodal areas (visual and tactile) connected to a third bimodal area (visual-tactile), which is activated only when a stimulus falls within the peripersonal space. Results show that the peripersonal space, which includes just a small visual space around the hand in normal conditions, becomes elongated in the direction of the tool after training, thanks to a reinforcement of synapses.

Models for the Study of Cortical Activity During Cognitive ans Motor Tasks

This thesis is mainly devoted to show how EEG data and related phenomena can be reproduced and analyzed using mathematical models of neural masses (NMM). The aim is to describe some of these phenomena, to show in which ways the design of the models architecture is influenced by such phenomena, point out the difficulties of tuning the dozens of parameters of the models in order to reproduce the activity recorded with EEG systems during different kinds of experiments, and suggest some strategies to cope with these problems. In particular the chapters are organized as follows: chapter I gives a brief overview of the aims and issues addressed in the thesis; in chapter II the main characteristics of the cortical column, of the EEG signal and of the neural mass models will be presented, in order to show the relationships that hold between these entities; chapter III describes a study in which a NMM from the literature has been used to assess brain connectivity changes in tetraplegic patients; in chapter IV a modified version of the NMM is presented, which has been developed to overcomes some of the previous version’s intrinsic limitations; chapter V describes a study in which the new NMM has been used to reproduce the electrical activity evoked in the cortex by the transcranial magnetic stimulation (TMS); chapter VI presents some preliminary results obtained in the simulation of the neural rhythms associated with memory recall; finally, some general conclusions are drawn in chapter VII.

Evaluation of Antitumoral activity of bone targeted drugs/conventional chemotherapies and identification of biomarkers for the selection of patients with breast cancer for the bone targeted therapy in adjuvant setting

Bone metastases are responsible for different clinical complications defined as skeletal-related events (SREs) such as pathologic fractures, spinal cord compression, hypercalcaemia, bone marrow infiltration and severe bone pain requiring palliative radiotherapy. The general aim of these three years research period was to improve the management of patients with bone metastases through two different approaches of translational research. Firstly in vitro preclinical tests were conducted on breast cancer cells and on indirect co-colture of cancer cells and osteoclasts to evaluate bone targeted therapy singly and in combination with conventional chemotherapy. The study suggests that zoledronic acid has an antitumor activity in breast cancer cell lines. Its mechanism of action involves the decrease of RAS and RHO, as in osteoclasts. Repeated treatment enhances antitumor activity compared to non-repeated treatment. Furthermore the combination Zoledronic Acid + Cisplatin induced a high antitumoral activity in the two triple-negative lines MDA-MB-231 and BRC-230. The p21, pMAPK and m-TOR pathways were regulated by this combined treatment, particularly at lower Cisplatin doses. A co-colture system to test the activity of bone-targeted molecules on monocytes-breast conditioned by breast cancer cells was also developed. Another important criticism of the treatment of breast cancer patients, is the selection of patients who will benefit of bone targeted therapy in the adjuvant setting. A retrospective case-control study on breast cancer patients to find new predictive markers of bone metastases in the primary tumors was performed. Eight markers were evaluated and TFF1 and CXCR4 were found to discriminate between patients with relapse to bone respect to patients with no evidence of disease. In particular TFF1 was the most accurate marker reaching a sensitivity of 63% and a specificity of 79%. This marker could be a useful tool for clinicians to select patients who could benefit for bone targeted therapy in adjuvant setting.