The spatiotemporal dynamics of early attention processes: a high-resolution electroencephalographic study of N2 subcomponent sources.

The N2 subcomponents of event-related potentials are known to reflect early attentional processes. The anterior N2 may reflect conflict monitoring, whereas the posterior N2 may be involved in target detection. The aim of this study was to identify the brain areas involved in the generation of the N2 subcomponents, in order to define the spatiotemporal dynamics of these attentional processes. We recorded 128-channel electroencephalograms in 15 healthy controls performing a three-stimulus visual oddball task and identified standard-, distracter- and target-elicited N2 components. Individual N2 sources were localized using standardized-weighted-low-resolution-electromagnetic-tomography (swLORETA). Comparative analyses were performed with a non-parametric permutation technique. Common N2 generators were observed in the Brodmann area (BA) 24 of the anterior cingulate cortex (ACC). The posterior cingulate cortex and the central precuneus were more involved in distracter processing, whereas the anterior precuneus and BA 32 of the ACC were target-specific. In accordance with previous demonstration of the frontoparietal cortex's critical role in attentional processes, these new data shed light on the ACC's role in conflict monitoring and its interaction with other median and frontoparietal structures in early attentional processes.

Brain activity modeling in general anesthesia: enhancing local mean-field models using a slow adaptive firing rate.

In this paper, an enhanced local mean-field model that is suitable for simulating the electroencephalogram (EEG) in different depths of anesthesia is presented. The main building elements of the model (e.g., excitatory and inhibitory populations) are taken from Steyn-Ross [M. L. Steyn-Ross, Phys. Rev. E 64, 011917 (2001), D. A. Steyn-Ross, Phys. Rev. E 64, 011918 (2001)] and Bojak and Liley [I. Bojak and D. T. Liley, Phys. Rev. E 71, 041902 (2005)] mean-field models and a new slow ionic mechanism is included in the main model. Generally, in mean-field models, some sigmoid-shape functions determine firing rates of neural populations according to their mean membrane potentials. In the enhanced model, the sigmoid function corresponding to excitatory population is redefined to be also a function of the slow ionic mechanism. This modification adapts the firing rate of neural populations to slow ionic activities of the brain. When an anesthetic drug is administered, the slow mechanism may induce neural cells to alternate between two levels of activity referred to as up and down states. Basically, the frequency of up-down switching is in the delta band (0-4 Hz) and this is the main reason behind high amplitude, low frequency fluctuations of EEG signals in anesthesia. Our analyses show that the enhanced model may have different working states driven by anesthetic drug concentration. The model is settled in the up state in the waking period, it may switch to up and down states in moderate anesthesia while in deep anesthesia it remains in the down state.