EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.     

Prediction of Long-Term Treatment Response to Selective Serotonin Reuptake Inhibitors (SSRIs) Using Scalp and Source Loudness Dependence of Auditory Evoked Potentials (LDAEP) Analysis in Patients with Major Depressive Disorder

Background: Animal and clinical studies have demonstrated that the loudness dependence of auditory evoked potentials (LDAEP) is inversely related to central serotonergic activity, with a high LDAEP reflecting weak serotonergic neurotransmission and vice versa, though the findings in humans have been less consistent. In addition, a high pretreatment LDAEP appears to predict a favorable response to antidepressant treatments that augment the actions of serotonin. The aim of this study was to test whether the baseline LDAEP is correlated with response to long-term maintenance treatment in patients with major depressive disorder (MDD). Methods: Scalp N1, P2 and N1/P2 LDAEP and standardized low resolution brain electromagnetic tomography-localized N1, P2, and N1/P2 LDAEP were evaluated in 41 MDD patients before and after they received antidepressant treatment (escitalopram (n = 32, 10.0 ± 4.0 mg/day), sertraline (n = 7, 78.6 ± 26.7 mg/day), and paroxetine controlled-release formulation (n = 2, 18.8 ± 8.8 mg/day)) for more than 12 weeks. A treatment response was defined as a reduction in the Beck Depression Inventory (BDI) score of >50% between baseline and follow-up. Results: The responders had higher baseline scalp P2 and N1/P2 LDAEP than nonresponders (p = 0.017; p = 0.036). In addition, changes in total BDI score between baseline and follow-up were larger in subjects with a high baseline N1/P2 LDAEP than those with a low baseline N1/P2 LDAEP (p = 0.009). There were significantly more responders in the high-LDAEP group than in the low-LDAEP group (p = 0.041). Conclusions: The findings of this study reveal that a high baseline LDAEP is associated with a clinical response to long-term antidepressant treatment.     

Impact of 2D and 3D display watching on EEG power spectra: A standardized low-resolution tomography (sLORETA) study

We investigated whether watching two-dimensional television (2DTV) or three-dimensional television (3DTV) resulted in differences in the brain’s processing of sensory information. We divided 25 participants into 2DTV (n = 13) and 3DTV (n = 12) groups. Participants watched 2DTV or 3DTV for 1, 2, or 3 h on different days. Before and at the end of each session, electroencephalography (EEG) was recorded for 10 min. The Simulation Sickness Questionnaire (SSQ) and the Visual Analog Scale (VAS) were used to assess general discomfort before and after watching. Each frequency band of the resting EEG was transformed into a standardized low-resolution electromagnetic tomographic (sLORETA) image. In the 2DTV group, 2 h of watching increased theta power in the central cortex and 3 h of watching increased beta power in the occipital cortex. In the 3DTV group, 3 h of watching increased delta power in the parahippocampal gyrus and middle frontal cortex. Theta power was significantly higher in the insular cortex after 3 h of 3DTV than after 3 h of 2DTV. SSQ scores were significantly higher after 1 h of 2DTV than after 1 h of 3DTV. Watching 2DTV vs. 3DTV triggered different time-dependent activity patterns. Watching 3DTV for 3 h increased slow-wave activity in the prefrontal cortex, while watching 2DTV increased fast-wave activity in the occipitoparietal cortex. Up to 2 h of 3DTV watching did not cause major changes in fatigue or EEG activity compared with 2DTV. Our findings promise to be useful in designing safety guidelines for watching 3DTV.     

Effect of Level of Processing Prior to Response on Cognitive Control： Evidence from ERP

Based on the idea that intentions have different penetrability to perception and thought, four Stroop-like tasks, AA, AW, WA, and WW are used. Event-related brain potentials are recorded as participants completed these tasks, and standardized low resolution brain electromagnetic tomography （sLORETA） is used to localize the sources at specific time points. These results show that there is an interference effect in the AA and WA tasks, but not in the AW or WW tasks. The activated brain areas related to the interference effect in the AA task are the PFC （prefrontal cortex） and ACC （anterior cingulated cortex）, and PFC aetivation takes place prior to ACC activation, but only in WA task. Combined with previous results, a new neural mechanism of cognitive control is proposed.