OBJECTIVE: To evaluate the evolution of interhemispheric coherences (ICo) in background and spindle frequency bands during childhood and use it to identify individuals with corpus callosum dysgenesis (CCd).
METHODS: A monocentric cohort of children aged from 0.25 to 15 years old, consisting of 13 children with CCd and 164 without, was analyzed. The ICo of background activity (ICOBckgrdA), sleep spindles (ICOspindles), and their sum (sICO) were calculated. The impact of age, gender, and CC status on the ICo was evaluated, and the sICO was used to discriminate children with or without CCd.
RESULTS: ICOBckgrdA, ICOspindles and sICO increased significantly with age without any effect of gender (p < 10-4), in both groups. The regression equations of the different ICo were stronger, with adjusted R2 values of 0.54, 0.35, and 0.57, respectively. The ICo was lower in children with CCd compared to those without CCd (p < 10-4 for all comparisons). The area under the precision recall curves for predicting CCd using sICO was 0.992 with 98.9 % sensitivity and 87.5 % specificity.
CONCLUSIONS: ICo of spindles and background activity evolve in parallel to brain maturation and depends on the integrity of the corpus callosum. sICO could be an effective diagnostic biomarker for screening children with interhemispheric dysfunction.

Electroencephalography (EEG) background activity is associated with neurological outcome in neonates with hypoxic-ischemic encephalopathy. There is uncertainty about the prognostic value of EEG background activity after hypothermia was introduced.
Searches were made on Pubmed, Embase, and the Cochrane Library, from inception to March 1, 2018. Pooled sensitivities and specificities were calculated to assess the diagnostic power of burst suppression, low voltage, and flat trace background activities in the prediction of an adverse neurological outcome in the follow-up period in hypothermia-treated neonates with hypoxic-ischemic encephalopathy. I2 was used to assess heterogeneity, and meta-regression was done to explore the source of heterogeneity.
Eighteen studies with 940 neonates were included. Pooled sensitivities and specificities in predicting the combination of death and neurodevelopmental impairment were burst suppression (sensitivity 0.87 [95% confidence interval (CI) 0.79 to 0.93], specificity 0.60 [95% CI 0.44 to 0.74]), low voltage (sensitivity 0.84 [0.75 to 0.90], specificity 0.80 [0.58 to 0.92]), and flat trace (sensitivity 0.85 [0.75 to 0.92], specificity 0.94 [0.77 to 0.99]). Subgroup analysis revealed the sensitivities of background patterns obtained after 24 hours of life were higher than those within age 24 hours, whereas the specificities were just the reverse. Flat trace performed best on sensitivity 0.93 (0.60 to 0.99) and specificity 0.90 (0.64 to 0.98) in predicting death. Burst suppression demonstrated the highest sensitivity 0.87 (0.58 to 0.97) and flat trace performed best on specificity 0.85 (0.60 to 0.96) in predicting neurodevelopmental impairment.
EEG background activity is predictive of long-term neurological outcome in hypothermia-treated neonates with hypoxic-ischemic encephalopathy. Burst suppression, low voltage, and flat trace are potential predictors of death or neurodevelopmental impairment.

Therapeutic doses of antiepileptic drugs (AEDs) may alter EEG background activity, which is considered an index of the functional state of the brain. Quantitative analysis (qEEG) of EEG background activity is a valid instrument to assess the effects of many centrally active drugs on the central nervous system, including AEDs. Lacosamide (LCM) is a new AED that could be a valid therapeutic choice in patients with brain tumor-related epilepsy (BTRE).
We used qEEG to analyze the possible effect of LCM as an add-on, on background EEG activity after 4 months in patients with BTRE.
We consecutively recruited sixteen patients with BTRE: Five dropped out for disease progression, five for scarce compliance, and six completed the study. For these reasons qEEG was performed at first visit and after 4 months only in six patients. For all frequency bands, LCM revealed no changes of mean relative power during rest with eyes closed, hyperpnoea (HP), and mental arithmetic task (MA); significant increment was found only in the theta mean relative power during opening and closing eyes (BR). After four months of therapy with LCM, one patient was seizure free, four had a seizure reduction ≥50%, and one showed a worsening in seizure frequency <50%.
Despite the limitation of a small series, these findings suggest that LCM seems to have only a mild interference on EEG background activity and confirm that LCM has a good efficacy on seizure control in patients with BTRE. This is the first study that evaluates the effect of LCM on background EEG activity, using qEEG in BTRE patients. Future research in this area could include prospective studies with qEEG for a longer follow-up period to assess the impact of AEDs on brain functions in this particular fragile patient population.

To investigate relationship between treatment efficiency and EEG background activity changes in absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) patients.
EEGs of 31 patients were analysed before treatment and after six months of treatment. Three minutes of artifact-free waking EEG background activity (without epileptiform potentials) were analysed for each patient in both conditions. All the EEG samples were processed to LORETA (Low Resolution Electromagnetic Tomography). Average of all the voxel-wise current source density (CSD) values within the 0.5-8.0Hz frequency range was computed for each EEG. Fischer\'s exact test was used to investigate association between the global CSD changes and the therapeutic outcome.
Tight connection was demonstrated between seizure freedom and decreased CSD, and between persisting seizures and increased CSD (p<0.001).
An EEG-based biomarker that predicts successful drug treatment was described.

OBJECTIVE: To evaluate the prognostic value of single EEG patterns recorded at various time-frames in postanoxic comatose patients.
METHODS: This retrospective study included 30-min EEGs, classified according to the definitions of continuity of background activity given by the American Clinical Neurophysiology Society. Isoelectric pattern was distinguished from other suppressed activities. Epileptiform patterns were considered separately. Outcome was dichotomised based on recovery of consciousness as good (Glasgow Outcome Scale [GOS] 3-5) or poor (GOS 1-2).
RESULTS: We analysed 211 EEGs, categorised according to time since cardiac arrest (within 12h and around 24, 48 and 72h). In each time-frame we observed at least one EEG pattern which was 100% specific to poor or good outcome: at 12h continuous and nearly continuous patterns predicted good outcome and isoelectric pattern poor outcome; at 24h isoelectric and burst-suppression predicted poor outcome; at 48 and 72h isoelectric, burst-suppression and suppression (2-10μV) patterns predicted poor outcome.
CONCLUSIONS: The prognostic value of single EEG patterns, defined according to continuity and voltage of background activity, changes until 48-72h after cardiac arrest and in each time-frame there is at least one pattern which accurately predicts good or poor outcome.
CONCLUSIONS: Standard EEG can provide time-dependent reliable indicators of good and poor outcome throughout the first 48-72h after cardiac arrest.

OBJECTIVE: This cross-sectional study assessed the ability of standard EEG in distinguishing vegetative state (VS) from minimally conscious state plus (MCS+) or MCS minus (MCS-), and to correlate EEG features with aetiology and level of responsiveness assessed by Coma Recovery Scale-Revised (CRS-R).
METHODS: We analyzed background EEG activity and EEG reactivity to eye opening and closing and to tactile, acoustic, nociceptive stimuli and Intermittent Photic Stimulation (IPS) in 73 inpatients (VS=37, MCS-=11, MCS+=25), with traumatic (n=21), vascular (n=25) or anoxic (n=27) aetiology.
RESULTS: All patients, but one, showed abnormal background activity. EEG abnormalities were more severe in VS than in MCS+ or MCS-, and in anoxic than other aetiologies. MCS+ patients with normal or Mildly Abnormal background activity showed higher scores on CRS-R than patients with moderate to severe EEG abnormalities. Reactivity to IPS, and acoustic stimuli was significantly more frequent in MCS+ and MCS- than in VS patients.
CONCLUSIONS: EEG features differ between VS and MCS- or MCS+ patients and can provide evidence of relative sparing of thalamocortical connections in MCS+ patients. In anoxic patients EEG organization is more severely impaired and provides less discriminative diagnostic information.
CONCLUSIONS: Conventional EEG can help clinicians to disentangle VS from MCS patients.