Topic: alpha band

EEG-based functional connectivity is a suitable tool to study how different brain regions interact during specific cognitive tasks such as art perception. In this study, we aim to investigate the networks activated during the perception of artistic paintings. Twenty-six university students were presented with a random series of 40 abstract and 40 representational paintings. Each painting was shown for 8 seconds. During the experiment, scalp bioelectric activity was recorded using high-density (128-channel) EEG with a Biosemi ActiveTwo device. We calculated the functional connectivity networks

Phantom limb pain (PLP) is a condition where pain is perceived as arising from a missing limb. Despite the high prevalence of PLP among individuals with amputation, the underlying mechanisms of this painful condition are poorly understood. The aim of the research presented here is to analyse high-resolution EEG data to differentiate oscillatory patterns in amputees who experience PLP from two control groups, amputees without PLP and individuals without amputation, and generate novel insights into the pathophysiology of PLP. This work expands on a previous investigation on the use of common spa

A major challenge in cognitive neuroscience is understanding how the spatiotemporal dynamics of neural activity of the cerebral cortex supports the processing of information about external stimuli and its use in forming accurate perceptual decisions. In particular, it is unclear how activity distributed across cortical areas and frequency bands encodes information synergistically or redundantly, and how these emergent properties of interactions across areas relate to perception. Here, we aim to measure synergy and redundancy during an audiovisual task at the mesoscale level in auditory, visual

The concept of oscillations is fundamental in the field of neural data analysis. Oscillations are thought to reflect brain states in different cognitive or physiological states and are essential to higher-order features of neural dynamics, such as functional connectivity or long-range temporal correlations. Neuronal oscillations are typically measured using power spectral methods that quantify signal amplitude but not the rhythmicity or 'oscillatoriness' per se.Here we present a new method, the phase-autocorrelation function (pACF), for quantifying rhythmicity directly. We applied pACF to data