Summary:Purpose: To characterize seizures after intracerebral hemorrhage (ICH), evaluating the risk of occurrence and relapse, predisposing factors, and prognostic significance, and to assess the utility of antiepileptic drug (AED) therapy as used in clinical practice.Methods: The study sample consisted of 761 patients with spontaneous, nonaneurysmal, supratentorial ICH. Seizures were classified as immediate (within 24 h of ICH) and early (within 30 days of ICH). Baseline variables and clinical events were compared in the seizure and nonseizure group by using a multivariate regression model of failure time data.Results: Fifty-seven patients had one or more seizures. The 30-day actuarial risk of a post-ICH seizure was 8.1%. Lobar location and small volume of ICH were independent predictors of immediate seizures. Early seizures were associated with lobar location and neurologic complications, mainly rebleeding.In patients with lobar ICH, the risk of early seizures was reduced by prophylactic AED therapy. Among seizure patients, history of alcohol abuse increased the risk of status epilepticus. Immediate and early seizures were not independent predictors of in-hospital mortality.Conclusions: Patients with ICH are exposed to a substantial risk of seizures; however, short-term mortality was not affected, and the risk of epilepsy was lower than previously thought. The likelihood of immediate seizures is influenced by factors that are inherent characteristics of ICH, whereas the chance of developing early seizures is influenced not only by certain characteristics of ICH, but also by unpredictable events. A brief period of therapy soon after ICH onset may reduce the risk of early seizures in patients with lobar hemorrhage. Key Words: Intracerebral hemorrhage-Stroke-Seizures-Status epilepticus-Epilepsy.Seizures as a clinical feature of intracerebral hemorrhage (ICH) have not been fully investigated. Little is known about the frequency, temporal distribution, and characteristics of seizures, and even less about factors predisposing to seizures and their prognostic significance for short-term mortality and risk of epilepsy. Major aspects have often been ignored, including the fact that delayed post-ICH seizures may have different predisposing factors from onset seizures, that the number of patients at risk for seizure varies in time, and that many predisposing factors may act synergistically in time to cause seizures.In this study the occurrence of seizures in patients with computed tomography (CT)-proven supratentorial nontraumatic nonaneurysmal ICH was analyzed by using multivariate analyses to determine the risk of developing initial and recurrent seizures, to identify predisposing factors for onset and delayed seizures, to evaluate the impact of seizures on outcome, and to assess the value of prophylactic antiepileptic drug (AED) therapy as used in clinical practice. PATIENTS AND METHODSThe study sample consisted of 761 consecutive patients with nontraumatic, nonaneurysmal ICH. The sample was part of a prospective, obs...

Summary:Purpose: To assess the effectiveness of slow repetitive transcranial magnetic stimulation (rTMS) as an adjunctive treatment for drug-resistant epilepsy.Methods: Forty-three patients with drug-resistant epilepsy from eight Italian Centers underwent a randomized, doubleblind, sham-controlled, crossover study on the clinical and EEG effects of slow rTMS. The stimulus frequency was 0.3 Hz. One thousand stimuli per day were given at the resting motor threshold intensity for 5 consecutive days, with a round coil at the vertex.Results: "Active" rTMS was no better than placebo for seizure reduction. However, it decreased interictal EEG epileptiform abnormalities significantly (p < 0.05) in one-third of the patients, which supports a detectable biologic effect. No correlation linked the rTMS effects on seizure frequency to syndrome or anatomic classification, seizure type, EEG changes, or resting motor threshold (an index of motor cortex excitability).Conclusions: Although the antiepileptic action was not significant (p > 0.05), the individual EEG reactivity to "active" rTMS may be encouraging for the development of more-powerful, noninvasive neuromodulatory strategies.

Several cross-sectional studies have documented neuroanatomical changes in individuals with a long history of meditation, while a few evidences are available about the interaction between neuroanatomical and psychological changes even during brief exposure to meditation. Here we analyzed several morphometric indexes at both cortical and subcortical brain level, as well as multiple psychological dimensions, before and after a brief -8 weeks- Mindfulness Based Stress Reduction (MBSR) training program, in a group of 23 meditation naïve-subjects compared to age-gender matched subjects. We found a significant cortical thickness increase in the right insula and the somatosensory cortex of MBSR trainees, coupled with a significant reduction of several psychological indices related to worry, state anxiety, depression and alexithymia. Most importantly, an interesting correlation between the increase in right insula thickness and the decrease in alexithymia levels during the MBSR training were observed. Moreover, a multivariate pattern classification approach allowed to identify a cluster of regions more responsive to MBSR training across subjects. Taken together, these findings documented the significant impact of a brief MBSR training on brain structures, as well as stressing the idea of MBSR as a valuable tool for alexithymia modulation, also originally providing a plausible neurobiological evidence of a major role of right insula into mediating the observed psychological changes.

Epilepsy is often associated with modifications in autonomic nervous system, which usually precede the onset of seizures of several minutes. Thus, there is a great interest in identifying these modifications enough time in advance to prevent a dangerous effect and to intervene. In addition, these changes can be a risk factor for epileptic patients and can increase the possibility of death. Notably autonomic changes associated to seizures are highly depended of seizure type, localization and lateralization. The aim of this study was to develop a patient-specific approach to predict seizures using electrocardiogram (ECG) features. Specifically, from the RR series, both time and frequency variables and features obtained by the recurrence quantification analysis were used. The algorithm was applied in a dataset of 15 patients with 38 different types of seizures. A feature selection step, was used to identify those features that were more significant in discriminating preictal and interictal phases. A preictal interval of 15 minutes was selected. A support vector machine (SVM) classifier was then built to classify preictal and interictal phases. First, a classifier was set up to classify preictal and interictal segments of each patient and an average sensibility of 89.06% was obtained, with a number of false positive per hour (FP/h) of 0.41. Then, in those patients who had at least 3 seizures, a double-cross-validation approach was used to predict unseen seizures on the basis of a training on previous ones. The results were quite variable according to seizure type, achieving the best performance in patients with more stereotypical seizure. The results of the proposed approach show that it is feasible to predict seizure in advance, considering patient-specific, and possible seizure specific, characteristics.

SUMMARYObstructive sleep apnea (OSA) syndrome is the most common sleeprelated breathing disorder, characterized by excessive snoring and repetitive apneas and arousals, which leads to fragmented sleep and, most importantly, to intermittent nocturnal hypoxaemia during apneas. Considering previous studies about morphovolumetric alterations in sleep apnea, in this study we aimed to investigate for the first time the functional connectivity profile of OSA patients and age-gender-matched healthy controls, using resting-state functional magnetic resonance imaging (fMRI). Twenty severe OSA patients (mean age 43.2 ± 8 years; mean apnea-hypopnea index, 36.3 h À1 ) and 20 non-apneic age-gender-body mass index (BMI)-matched controls underwent fMRI and polysomnographic (PSG) registration, as well as mood and sleepiness evaluation. Cerebro-cerebellar regional homogeneity (ReHo) values were calculated from fMRI acquisition, in order to identify pathology-related alterations in the local coherence of low-frequency signal (<0.1 Hz). Multivariate pattern classification was also performed using ReHo values as features. We found a significant pattern of cortical and subcortical abnormal local connectivity in OSA patients, suggesting an overall rearrangement of hemispheric connectivity balance, with a decrease of local coherence observed in right temporal, parietal and frontal lobe regions. Moreover, an increase in bilateral thalamic and somatosensory/motor cortices coherence have been found, a finding due possibly to an aberrant adaptation to incomplete sleep-wake transitions during nocturnal apneic episodes, induced by repetitive choke sensation and physical efforts attempting to restore breathing. Different hemispheric roles into sleep processes and a possible thalamus key role in OSA neurophysiopathology are intriguing issues that future studies should attempt to clarify. IN TROD UCTI ONObstructive sleep apnea syndrome (OSA) is a very common sleep disorder, the neuropathophysiology of which remains controversial (Horner, 2008) . It is characterized by excessive snoring and repetitive nocturnal apneas and arousals, which leads to fragmented sleep and, most importantly, intermittent nocturnal hypoxaemia during apneas. These result in a complex and disabling condition composed by daytime sleepiness, neurocognitive problems such as deficits in memory, attention and visuoconstructive abilities (Bruin and Bagnato, 2010), reduced work performance and a worsening of overall quality of life (Bulcun et al., 2012). During the last 15 years several brain alterations have also been documented. The majority of studies, performed through voxel-based morphometry (VBM) or surface-based parcellation approaches, have highlighted grey matter concentration differences in both cortical and subcortical brain regions, with hippocampus,