Visual search performance is predicted by both prestimulus and poststimulus electrical brain activity

Abstract

An individual’s performance on cognitive and perceptual tasks varies considerably across time and circumstances. We investigated neural mechanisms underlying such performance variability using regression-based analyses to examine trial-by-trial relationships between response times (RTs) and different facets of electrical brain activity. Thirteen participants trained five days on a color-popout visual-search task, with EEG recorded on days one and five. The task was to find a color-popout target ellipse in a briefly presented array of ellipses and discriminate its orientation. Later within a session, better preparatory attention (reflected by less prestimulus Alpha-band oscillatory activity) and better poststimulus early visual responses (reflected by larger sensory N1 waves) correlated with faster RTs. However, N1 amplitudes decreased by half throughout each session, suggesting adoption of a more efficient search strategy within a session. Additionally, fast RTs were preceded by earlier and larger lateralized N2pc waves, reflecting faster and stronger attentional orienting to the targets. Finally, SPCN waves associated with target-orientation discrimination were smaller for fast RTs in the first but not the fifth session, suggesting optimization with practice. Collectively, these results delineate variations in visual search processes that change over an experimental session, while also pointing to cortical mechanisms underlying performance in visual search.

Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

“…Static resting state functional connectivity has been linked to a number of general cognitive abilities that include, amongst others, IQ, executive function, episodic memory and reading comprehension (for review, see Vaidya and Gordon, 2013). Thus, rather than simply reflecting invariant structural anatomy, historical co-activation patterns, or internal dynamics of local areas, intrinsic activity predicts subsequent perceptual processing (Hesselmann et al, 2008;van Dijk et al, 2008;Busch et al, 2009;Mathewson et al, 2009;Sadaghiani et al, 2009;Lou et al, 2014;Van Den Berg et al, 2016).…”

Beyond the evoked/intrinsic neural process dichotomy

“…However, most researchers now agree that the same task stimulus can have different neural and psychological effects depending on prestimulus intrinsic activity levels. This is particularly true in studies of the effect of oscillatory prestimulus activity on subsequent sensory experience in EEG and fMRI studies (Busch, Dubois, & VanRullen, 2009 ; Hesselmann, Kell, Eger, et al, 2008 ; Hesselmann, Kell, & Kleinschmidt, 2008 ; Lou, Li, Philiastides, & Sajda, 2014 ; Mathewson, Gratton, Fabiani, Beck, & Ro, 2009 ; Sadaghiani, Hesselmann, & Kleinschmidt, 2009 ; Sapir, d’Avossa, McAvoy, Shulman, & Corbetta, 2005 ; van den Berg, Appelbaum, Clark, Lorist, & Woldorff, 2016 ; van Dijk, Schoffelen, Oostenveld, & Jensen, 2008 ). In these studies, the prestimulus alpha-band level in the case of EEG or BOLD level in the case of fMRI is used to predict whether a randomly presented subliminal auditory or visual stimulus is consciously perceived.…”

Cyborg groups enhance face recognition in crowded environments

“…There is ample evidence that physiological correlates of decision confidence exist. For instance, several brain-activity patterns as recorded via electroencephalography (EEG) are known to provide information about decision confidence (e.g., the P300 event-related potential (ERP) and the error related negativity [31, 32]), and visual search performance (e.g., the N2pc [33] and N1 [34] ERPs). Moreover, it has been known for a long time that response times (RTs) negatively correlate with the confidence in a decision [35–37].…”