Michele Bezzi

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In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infectious virus and cytotoxic T lymphocytes (cellular response). The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host’s ability to eliminate the virus. We find two basins of attraction in(More)
Information theory - in particular mutual information- has been widely used to investigate neural processing in various brain areas. Shannon mutual information quantifies how much information is, on average, contained in a set of neural activities about a set of stimuli. To extend a similar approach to single stimulus encoding, we need to introduce a(More)
Multielectrode arrays allow recording of the activity of many single neurons, from which correlations can be calculated. The functional roles of correlations can be revealed by measures of the information conveyed by neuronal activity; a simple formula has been shown to discriminate the information transmitted by individual spikes from the positive or(More)
A nerve cell receives multiple inputs from upstream neurons by way of its synapses. Neuron processing functions are thus influenced by changes in the biophysical properties of the synapse, such as long-term potentiation (LTP) or depression (LTD). This observation has opened new perspectives on the biophysical basis of learning and memory, but its(More)
A novel definition of the stimulus-specific information is presented, which is particularly useful when the stimuli constitute a continuous and metric set, as, for example, position in space. The approach allows one to build the spatial information distribution of a given neural response. The method is applied to the investigation of putative differences in(More)
Neurons communicate through spikes; their arrangement in different sequences generates the neural code. Spikes are transmitted between neurons via synapses; the mechanism underlying synaptic transmission involves numerous processes including neurotransmitter release and diffusion, postsynaptic receptor activation, and intrinsic electroresponsiveness. Based(More)
  • Michele Bezzi
  • 2007 Third International Conference on Security…
  • 2007
Data holders use data masking techniques for limiting disclosure risk in releasing sensitive datasets. Disclosure risk is often expressed in terms of rareness or of probability of re-identification. We propose a novel measure of disclosure risk, based on Shannon entropy, which combines together these two approaches. This measure represents the uncertainty(More)
Organizations often need to release microdata without revealing sensitive information. To this scope, data are anonymized and, to assess the quality of the process, various privacy metrics have been proposed, such as k-anonymity, `-diversity, and t-closeness. These metrics are able to capture different aspects of the disclosure risk, imposing minimal(More)
We present a simple spiking model that extends the classical integrate-and-"re neuron to reproduce the di6erent dynamical behaviors observed in cerebellar granule cells. The model is two dimensional: in addition to the membrane potential V , we consider a gating variable that models a slow K current. This current plays a major role in generating the(More)
Mobile devices consume significant amounts of information, from different sources. Thus they often deal also with sensitive or confidential data, in places or situations that could be not appropriate, or not compliant with a corporate policy: context-aware access/usage control solutions can counter such situations. We propose a prototype, called ProtectMe,(More)