In this work, the neural correlates of emotional processing in Colombian ex-combatants with different empathy profiles were compared to normal controls matched for age, gender and educational level. Forty ex-combatants and 20 non ex-combatants were recruited for this study. Empathy levels as well as executive functions were measured. Empathy level was used to create three groups. Group 1 (G1) included ex-combatants with normal empathy scores, and Group 2 included ex-combatants with low scores on at least one empathy sub-scales. In control group (Ctrl), participants with no antecedents of being combatants and with normal scores in empathy were included. Age, gender, educational and intelligence quotients level were controlled among groups. event-related potentials (ERPs) were recorded while individuals performed an affective picture processing task that included positive, neutral and negative emotional stimuli, which elicit an early modulation of emotion categorization (Early Posterior Negativity (EPN)) and late evaluative process (LPP). EPN differences were found among affective categories, but no group effects were observed at this component. LPP showed a main effect of category and group (higher amplitudes in ex-combatants). There was an inverse correlation between empathy and executive functions scores and ERPs. Results are discussed according to the impact of emotional processing on empathy profile.

Background: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer’s disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG.Objective: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach.Methods: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis.Results: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity.Conclusion: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD.

Background: Presenilin-1 (PSEN1) mutations are the most common cause of familial early onset Alzheimer's Disease (AD). The PSEN1 E280A (E280A) mutation has an autosomal dominant inheritance and is involved in the production of amyloid-β. In Antioquia, Colombia, there is the largest family group of carriers with E280A mutation. The study of mutation carriers provides an unique opportunity to identify brain changes in stages previous to AD. Electroencephalography (EEG) is a low cost and minimally invasiveness technique that enables the following of brain changes in AD.Objective: To examine how previous reported differences in EEG for Theta and Alpha-2 rhythms in E280A subjects are related to specific regions in cortex and could be tracked across different ages. Methods: EEG signals were acquired during resting state from non-carriers and carriers, asymptomatic and symptomatic, subjects from E280A kindred from Antioquia, Colombia. Independent Component Analysis and inverse solution methods were used to locate brain regions related to differences in Theta and Alpha-2 bands.Results: Independent Component Analysis helps to identify two components, mainly related to the Precuneus, were the differences in Theta and Alpha-2 exist simultaneously at asymptomatic and symptomatic stage. When a ratio between Theta and Alpha-2 is used significant correlations exist with age and a composite cognitive scale. Conclusion:Theta and Alpha-2 rhythms are altered in E280A subjects. The alterations are possible to track at Precuneus regions using EEG, ICA and inverse solution methods.

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Alzheimer's disease is the most prevalent cause of dementia. Mild Cognitive Impairment (MCI) is defined as a grey area between intact cognitive functioning and clinical dementia. Electroencephalography (EEG) has been used to identify biomarkers in dementia. Currently, there is a great interest in translating the study from raw signals to signal generators, trying to keep the relationship with neurophysiology. In the current study, EEG recordings during an encoding task were acquired in MCI subjects and healthy controls. Data was decomposed using group Independent Component Analysis (gICA) and the most neuronal components were analyzed using Phase Intertrial Coherence (PIC) and Phase shift Intertrial Coherence (PsIC). MCI subjects exhibited an increase of PIC in the theta band, while controls showed increase in PsIC in the alpha band. Correlation between PIC and PsIC and clinical scales were also found. Those findings indicate that the methodology proposed based in gICA can help to extract information from EEG recordings with neurophysiological meaning.