1) Modeling study of the cardiovascular, cerebrovascular and
respiratory systems. The control mechanisms and their reciprocal
interactions are analyzed by means of interpretative mathematical
models.
2) Compartment models. Compartment models are developed to
describe solute kinetics and fluid volume changes during renal
dialysis, and toxin removal during liver dialysis.
3) Neural networks of sensory and cognitive functions. Neural
network models are developed to study the integration among
different sensory modalities (visual-acustic, visual-tactile), that
takes place in some cortical regions. Neural oscillators models are
realized to investigate the problems of object representation,
learning, memorization, language, attention.
4) Advancede processing techniques applied
to biomedical signals (time-scale analysis, principal
component analysis, indipendent component analysis) for feature
extraction, artifacts removal, source separation.
1) The cardiorespiratory and cerebrovascular systems are
controlled by sophisticated regulation mechanisms that maintain
arterial pressure, blood flows to tissues, oxygenation, etc. within
tight limits despite the perturbations that daily affect these
systems. The control mechanisms are generally studied separately in
the literature and under experimental conditions that greatly
differ from the actual ones (e.g, under artificial ventilation). A
clear comprehension of the overall system and the interactions
among the involved mechanisms is still lacking; moreover, because
of the complexity of the relationships, the role of each single
component within the overall integration cannot be identified using
only clinical and experimental results. The proposed models aim at
improving the knowledge of the cardiovascular and ventilatory
regulation in different physio-pathological conditions: alteration
of the inspired gas concentrations, anaemia, altitude, exercise,
hypotension, cerebral ischemia, etc. These models, besides
enhancing the physiological knowledge, may also be used as the core
of didactic software for the education of technicians and
physicians.
2) Complications during renal dialysis (such as hypovolemia and
hypotension) still represent important clinical problems.
Developing models of solute kinetics and fluid volume changes
during kidney dialysis has important clinical implications. These
model may be used i) in a predictive modality, to predict solute
removal and blood volume changes during the dialysis session,
starting from the initial patient state, thus foreseeing possible
critical phases for the subject; ii) in a project modality, to set
rationally the dialysate composition, in order to reach the
end-dialysis targets minimizing the intradialitic risks.
The MARS (Molecular Adsorbent Recirculating System) technique is
a clinically effective procedure for the temporary substitution of
the liver function. This therapy is applied to patients with acute
or chronic liver failure until the native liver function recovers
or as a bridge treatment to liver transplantation. However, the
exact mechanisms underlying the clinical effects of MARS therapy
are poorly understood; this deficiency avoids the full exploitation
of the MARS therapeutic potentialities and precludes the
possibility of planning the optimal treatment on the basis of the
specific conditions of the single patients. The research activity
aims at developing models able to predict toxin removal during MARS
session and to interpret the depurative mechanisms, identifying
their specific role and temporal dynamics.
3) Neurons able to respond to stimuli of different modalities
(visual, acoustic, tactile) have been identified in several
cortical regions. Such integration seems to play a fundamental role
both in orienting the behaviour (e.g., the gaze and movements) on
the basis of the environmental information and to create a unitary
and coherent perception of the external world. However, the neural
mechanisms underlying this process are still largely unknown. The
research activity is focused on the development of neural network
models able to explain neurophysiological and psychophysical
results related to multisensory integration, in order to achieve a
deeper comprehension of the underlying neural mechanisms. Moreover,
the realized models may be of value to investigate how the
properties of the multisensory integration modify with development
and experience.
Several cognitive functions result from the parallel activation
of large populations of neurons, distributed among multiple and
separated cortical regions. Hence, the comprehension of the
mechanisms underlying the functional link among such distributed
activity is of fundamental importance. A recent influential
hypothesis sustains that this link is realized via the
synchronization of the neural oscillatory activity (especially in
gamma band, that is 30-100 Hz), that dynamically connect neurons
into “functional webs”. Models of neural oscillators, based on
physiologically plausible mechanisms, are of value to investigate
and understand the synchronization and desynchronization mechanisms
that occur in several cognitive processes such as object
recognition, memory, learning, language, attention.
4) Interpretation of biomedical signals and extraction of
information from them are highly complex tasks, both because of the
presence of disturbances and noise contaminating the useful
sifgnal, both because of the multiple components that that
contribute to the signal origin. Advanced processing techniques
(such as, discrete wavelet trasnform, principal component analysis,
indipendent component analysis) are applied to biomedical
signals in different conditions, in order to remove artefacts and
noise, to extract specific events and features, to reconstrut
signal sources. Specifically, these techniques are applied i) to
scalp EEG tracings acquired in epileptic patients, in order to
obtain information on the complex spatio-temporal dynamics of the
seizure; ii) to signals, such as the EEG and the
electro-oculogram, acquired during poligraphic recordings, in order
to identify specific events during the various phases of sleep and
wakefulness, and analyze their relationships.
