Beta oscillatory responses in healthy subjects and subjects with mild cognitive impairment

Abstract

The aim of the present study was to investigate the role of beta oscillatory responses upon cognitive load in healthy subjects and in subjects with mild cognitive impairment (MCI). The role of beta oscillations upon cognitive stimulation is least studied in comparison to other frequency bands. The study included 17 consecutive patients with MCI (mean age = 70.8 ± 5.6 years) according to Petersen's criteria, and 17 age- and education-matched normal elderly controls (mean age = 68.5 ± 5.5 years). The experiments used a visual oddball paradigm. EEG was recorded at 30 cortical locations. EEG-evoked power, inter-trial phase synchronization, and event-related beta responses filtered in 15–20 Hz were obtained in response to target and non-target stimuli for both groups of subjects. In healthy subjects, EEG-evoked beta power, inter-trial phase synchronization of beta responses and event-related filtered beta responses were significantly higher in responses to target than non-target stimuli (p < 0.05). In MCI patients, there were no differences in evoked beta power between target and non-target stimuli. Furthermore, upon presentation of visual oddball paradigm, occipital electrodes depict higher beta response in comparison to other electrode sites. The increased beta response upon presentation of target stimuli in healthy subjects implies that beta oscillations could shift the system to an attention state, and had important function in cognitive activity. This may, in future, open the way to consider beta activity as an important operator in brain cognitive processes.

Attentional gain and processing capacity limits predict the propensity to neglect unexpected visual stimuli

“…Following the findings of Capilla et al (2014), Rana et al(2014) and Güntekin et al (2013) this may be the result of early inhibition of irrelevant visual information (i.e., target identification) concomitantly with a heavier allocation of resources at a later stage (>250 ms).…”

“…Analogously to the alpha power, which shows an early increase and later decrease, beta power may be involved in the early selection (N1) and later processing of visual information (approx. in the N2 latency; Capilla et al 2014;Rana et al 2014;Güntekin et al 2013; see also Wróbel, 2000). Overall these results show that the amount of resources deployed during early visual processing (N1) is associated with a tendency to inattention.…”

“…For the ERSPs, peak amplitude/power in the regions of interest (ROIs; see results) were obtained by extracting participants' peak amplitude/power showing the highest response across frequency-time bins (for a justification see : Güntekin, Emek-Savaş, Kurt, Yener, & Başar, 2013). Finally, hierarchical fixed-effects regressions were carried out to assess the predictory power of brain oscillations to elicit ERPs.…”

“…Moreover, alpha, beta, and theta bands during the event-evoked period were also assessed since attentional allocation of resources is thought to play a multi-band (alpha, beta and theta) effect during visual processing (Güntekin, Emek-Savaş, Kurt, Yener, & Başar, 2013;Bastiaansen & Hagoort, 2003;Palva & Palva, 2007;Jensen, Bonnefond, & VanRullen, 2012). ROIs were identified on the basis of previous findings that showed increased alpha power during the period prior the presentation of a stimulus (Yamagishi et al, 2008), but also in the N1 latency and in later processing (>300 ms) in a form of a dissociated alpha band modulation (i.e., early/late alpha enhancement/suppression; Rana & Vaina, 2014;Capilla, Schoffelen, Paterson, Thut, Gross, 2014; see also Palva & Palva, 2007); moreover, modulation in the theta and beta band have also been found to be respectively indicative of good performance (i.e., encoding the location of the target stimulus; Bastiaansen & Hagoort, 2003;Klimesch, 1999) and increased visual attention (Güntekin et al 2013). Hence, the following ROIs were investigated: pre-stimulus alpha Power estimates (in dB) for the bands of interest and the level of saliency (low/high) were submitted to logistic regressions to test whether they were predictive of the level of inattention (similar analyses assessing behavioural performance on the basis of the power estimates of frequency bands can be found in Yamagishi, Callan, Anderson, & Kawato, 2008, for pre-stimulus period; see also Jensen et al 2012, for latency after the on-set of the array).…”

Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome

“…The EEG beta frequency is a desynchronized (arrhythmic), low voltage activity ranging from 13–30 Hz, primarily generated by small feedback loops between thalamic relay cells, the nucleus reticularis and pyramidal cells with small inhibitory neurons positioned closely to the pyramidal neurons (Thatcher, 2012). Significantly reduced beta activity has been associated historically with focal neurological damage and mild cognitive impairment (Guntekin et al, 2013; Ueda et al, 2013), Parkinson’s disease (Fonseca et al, 2013) and is one diagnostic criteria used to detect cognitive impairment immediately after cerebral hemorrhage and during diagnosis of mild cognitive impairment (Ueda et al, 2013; Zeng et al, 2013). Beta activity has been shown to be positively correlated with arousal, increases with improved working memory (Heister et al, 2013; Palva et al, 2005) and decreases during conditions of burnout (van Luijtelaar et al, 2010).…”