Neuro-cognitive activity during a self-paced visuospatial task: comparative EEG profiles in marksmen and novice shooters

Short-term learning of a visually guided power-grip task is associated with dynamic changes in EEG oscillatory activity

“…The present results suggest that with increasing task practice larger neuronal networks were activated in preparation for the task or that activity within existing networks is amplified to subserve improved performance. In support of this suggestion linking pre-task ERD and motor task performance, good or expert performance in nonmotor tasks (e.g., [Ergenoglu et al, 2004], [Hanslmayr et al, 2005] and ) and in the aiming period of a target shooting task (Haufler et al, 2000) has been variously related to reduced pre-task alpha power. For the late preparatory time range (LP) we found a widespread reduction in coherence with task practice in the beta frequency range, particularly involving frontal and parietal ROIs.…”

Signal Processing for Non-Invasive Brain Biomarkers of Sensorimotor Performance and Brain Monitoring

“…As previously mentioned, although several methods can be used to isolate some specific frequency bands; one of the main problems of the EEG/MEG spectral analysis is the definition of the upper and lower bounds of the bands (Pfurtscheller & Lopes da Silva, 1999). Although the definition of the frequency band limits can slightly differ from one study to another, a possible approach for partitioning the frequency bands related to human motor performance for healthy adults is to consider the theta ([4-7 Hz]), alpha (8)(9)(10)(11)(12)(13)), beta ) and gamma (36)(37)(38)(39)(40)(41)(42)(43)(44)) frequency bands (e.g., Hatfield et al, 2004;Haufler et al, 2000;Tombini et al, 2009). Sometimes, the frequency range spread from 8 to 15 Hz (Blankertz & Vidaurre, 2009) or from 9 to 13Hz Pfurtscheller & Neuper, 1997) are also named alpha frequency (or mu rhythm under certain conditions).…”

“…These studies revealed changes in EEG activity with skill learning as well as differences in EEG power between novice and expert sport performers (Del Percio et al, 2008;Hatfield et al, 1984Hatfield et al, , 2004Haufler et al, 2000;Kerick et al, 2004;Landers et al, 1994;Slobounov et al, 2007). Specifically, the power computed for the alpha and theta frequency bands were positively related to the level of motor performance (Del Percio et al, 2008;Hatfield et al, 2004;Haufler et al, 2000;Kerick et al, 2004). For instance, Haufler et al, (2000) showed that, compared to novices, experts revealed an overall increase in EEG alpha power in the left temporal lobe (i.e., T3) while the same comparison between novices and experts performing cognitive tasks that were equally familiar to them did not provide any differences.…”

“…Many different methods (e.g., parametric, non-parametric, and subspace methods) are available to compute the EEG/MEG spectral power (Kay, 1988;Sanei & Chambers, 2007;Shumway & Stoffer, 2000). For instance, some of these methods that have been applied are the classical fast Fourier transform (e.g., Hatfield et al, 1984;Haufler et al, 2000) and more sophisticated procedures such as the multitaper (e.g., Conteras-Vidal & Kerick, 2004) or wavelet (e.g., Mu et al, 2008) techniques. While some of these approaches have been applied with success in EEG/MEG studies that focus on sensorimotor performance and/or Brain Computer Interface (BCI) systems (McFarland et al, 2006;Pfurtscheller & Lopes da Silva, 1999), two methods are particularly popular to compute the EEG/MEG spectral power.…”

“…Such assessment in ecological situations requires non-invasive recording of the dynamic brain activity with a high temporal resolution (e.g., millisecond), which is well suited for EEG. Although some research efforts are underway (e.g., Deeny et al, 2003Deeny et al, , 2009Gentili et al, 2008Gentili et al, , 2009aHatfield et al, 2004;Haufler et al, 2000;Kerick et al, 2004) to develop methods to provide non-invasive functional brain biomarkers able to track the brain status during sensorimotor performance; some questions and problems remain. For example, how accurately and efficiently can a cognitive-motor or sensorimotor state be inferred?…”