A novel spatiotemporal tool for the automatic classification of fMRI noise based on Independent Component Analysis.

In this study, a semi-automatic, easy-to-use classification method for the identification and removal of fMRI noise is proposed and tested. The method relies on subject-level spatial independent component analysis (ICA) of fMRI data. Starting from a reference set of labeled independent components (ICs), novel ICs are classified as physiological/artefactual by combining a spatial correlation (SC) analysis with the reference ICs and relative power spectral (PS) analysis. Here, ICs from a task-based fMRI dataset were used as reference. SC and SP thresholds were set using a test dataset (5 subjects, same fMRI protocol) based on Receiving Operating Characteristic curves. The tool performance and versatility were measured on a resting-state fMRI dataset (5 subjects). Our results show that the method can automatically identify noise-related ICs with accuracy, specificity and sensitivity higher than 80% across different fMRI protocols. These findings also suggest that the reference set provided in the present study might be used to mark ICs coming from independent taskrelated or resting-state fMRI datasets.Clinical relevance- The new method will be included in a userfriendly, open-source tool for removal of noisy contributions from fMRI datasets to be used in clinical and research practices.

Functional Clustering approach for the analysis of Stereo-EEG activity patterns in correspondence of epileptic seizures.

In this study, a functional clustering approach is proposed and tested for the identification of brain functional networks emerging during sleep-related seizures. Stereo-EEG signals recorded in patients with Type II Focal Cortical Dysplasia (FCD type II), were analyzed. This novel approach is able to identify the network configuration changes in pre-ictal and early ictal periods, by grouping Stereo-EEG signals on the basis of the Cluster Index, after wavelet multiscale decomposition. Results showed that the proposed method is able to detect clusters of interacting leads, mainly overlapped on the Epileptogenic Zone (EZ) identified by a clinical expert, with distinctive configurations related to analyzed frequency ranges. This suggested the presence of coupling activities between the elements of the epileptic system at different frequency scales.

Exploring the neuroanatomical bases of psychotic features in bipolar disorder.

Although bipolar disorder (BD) is traditionally conceptualised as one diagnostic entity, the heterogeneity of pathophysiological manifestations in BD suggests the need to classify the subtypes of the illness based on neural markers. Specifically, the presence of psychotic symptoms seems to be relevant for the clinical outcome and may have specific neuroanatomical bases. The main objective of the present review was to assess whether the distinction between psychotic BD (PBD) and non-psychotic BD (NPBD) can improve the identification of the neurobiological markers of this complex illness. To this end, we summarised the findings from the magnetic resonance imaging studies that explored the cerebral correlates of psychosis in BD in terms of grey matter volume (GMV). Overall, the results suggest the presence of peculiar GMV differences between PBD and NPBD. Specifically, psychosis in BD seems to be associated with cortical GMV deficits compared with both healthy controls and NPBD, mainly in the frontal region. Conversely, NPBD patients showed GMV deficits in selective regions of the basal ganglia when compared with the other groups. Taken together, this evidence confirms the importance to classify BD based on the psychotic dimension, which may have a specific neurobiological architecture that partially overlaps across multiple psychotic disorders.

The putative role of neuronal network synchronization as a potential biomarker for bipolar disorder: A review of EEG studies.

Impaired intra-hemispheric and inter-hemispheric communication play a major role in the pathophysiology and cognitive disturbances of bipolar disorder (BD). Brain connectivity in BD has been largely investigated using magnetic resonance imaging (MRI) techniques, which have found alterations in prefronto-limbic coupling. In contrast, evidence for functional neural circuitry abnormalities in BD is less consistent. Indeed, just a few studies employing the electroencephalographic (EEG) technique, enabling the exploration of oscillatory brain dynamics, addressed this issue. Therefore, in the present review we summarize the results from EEG studies examining connectivity in patients with BD, to further clarify the putative role of neuronal network synchronization as a potential biomarker of this disabling mental illness.

Neuroanatomical voxel-based profile of schizophrenia and bipolar disorder.

Although schizophrenia (SCZ) and bipolar disorder (BD) share elements of pathology (Ellison-Wright and Bullmore, 2009), the neural mechanisms underlying these disorders are still under investigation. Up until now, many neuroimaging studies investigated the brain structural differences of SCZ and BD compared with healthy controls (HC), trying to identify the possible neuroanatomical markers for the two disorders. However, just a few studies focused on the brain structural changes between the two diagnoses. The present review summarises the findings of the voxel-based grey matter (GM) comparisons between SCZ and BD, with the objective to highlight the possible consistent anatomical differences between the two disorders. While the comparisons between patients and HC highlighted overlapping areas of GM reduction in insula and anterior cingulate cortex, the SCZ-BD comparisons suggest the presence of more generalised GM deficits in SCZ compared with BD. Indeed, in a number of studies, SCZ patients showed lower GM volumes than BD patients in fronto-temporal cortex, thalamus, hippocampus and amygdala. Conversely, only a couple of studies reported GM deficits in BD compared with SCZ, both at the level of cerebellum. In summary, the two disorders exhibit both common and specific neuroanatomical characteristics, whose knowledge is mandatory to develop innovative diagnostic and treatment strategies.

Coupling of fMRI and NIRS measurements in the study of negative BOLD response to intermittent photic stimulation.

Functional Magnetic Resonance Imaging (fMRI) in combination with Near Infrared Spectroscopy (NIRS) is finding widespread use in the analysis of brain function. While most of the studies deal with the detection of positive responses, here we focus on negative responses to visual stimulation. In a group fMRI study on Intermittent Photic Stimulation (IPS) we detected a sustained Negative BOLD Response (NBR) in the extrastriate visual cortex. To confirm and better characterize NBR, we repeated the same protocol during NIRS recordings. In this paper we show fMRI results and demonstrate the NBR on the basis of NIRS findings.

A new device for the care of Congenital Central Hypoventilation Syndrome patients during sleep.

Congenital Central Hypoventilation Syndrome (CCHS) is a genetic disease that causes an autonomous nervous system dysregulation. Patients are unable to have a correct ventilation, especially during sleep, facing risk of death. Therefore, most of them are mechanically ventilated during night and their blood oxygenation is monitored, while a supervisor keeps watch over them. If low oxygen levels are detected by the pulse-oximeter, an alarm fires; the supervisor deals with the situation and, if there is neither a technical problem nor a false alarm, wakes the subject, as CCHS patients usually recover from hypoxia when roused from sleep. During a single night multiple alarms may occur, causing fractioned sleep for the subject and a lasting state of anxiety for supervisors.

Can routine surveillance samples from tracheal aspirate predict bacterial flora in cases of ventilator-associated pneumonia?

AIM: The aim of this study was to investigate the hypothesis that periodical sampling of the tracheo-bronchial tree in the absence of clinical suspicion of pneumonia is useful to identify bacteria responsible for subsequent late ventilator associated pneumonia (VAP). This was a retrospective observational human study carried out in two medical-surgical intensive care units of two different hospitals. From January 1999 to December 2000, 559 patients, who received invasive respiratory support for more than 48 hours, were screened. METHODS: Tracheal aspiration (TA) was performed once or twice weekly in all mechanically ventilated patients. The microbiological findings from TA surveillance cultures done in the eight days before suspicion of VAP were compared to those isolated from the positive diagnostic samples done for late onset VAP (after more than four days of mechanical ventilation). The sensitivity, specificity, and positive/negative predictive values of the ability of the surveillance sample to anticipate the VAP pathogen were calculated. RESULTS: Among the microorganisms isolated from TA, 68% were retrieved from diagnostic samples. All VAP pathogens previously isolated were from 43% of the TA samples. If TA was collected 2-4 days before the clinical diagnosis of VAP, pathogens were detected in 58% of samples. In contrast, only 27% were collected more than four days earlier (P<0.05). The positive predictive values for Pseudomonas aeruginosa and methicillin resistant Staphylococcus aureus from routine TA samples were 92% and 90%, respectively. The negative predictive values for Pseudomonas aeruginosa and methicillin resistant Staphylococcus aureus from routine TA samples were 75% and 89%, respectively. CONCLUSIONS: TA cultures in ventilated patients may help to predict pathogens. Early detection may lead to earlier treatment in long term ventilated patients when VAP is suspected.

Paediatric rehabilitation in Italy.

In Italy, paediatric rehabilitation is part of the activity of services for neurological and psychiatric diseases in childhood and adolescence. These services (UONPIA) have an integrated, multi-professional, child- and family-oriented approach to paediatric disabling conditions. At present, inadequate territorial distribution of services, shortage of resources and need of epidemiological monitoring and specific designs of bio-medical research are the main problems.