Frontal theta predicts specific cognitive control-induced behavioural changes beyond general reaction time slowing

Cooper, Patrick S.; Karayanidis, Frini; McKewen, Montana; McLellan-Hall, Samuel; Wong, Anthony; Skippen, Patrick; Cavanagh, James F.

doi:10.1016/j.neuroimage.2019.01.022

Cited by 116 publications

(109 citation statements)

References 64 publications

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“…Based on visual inspection of the switch and mixing effects, two electrodes were selected: FCz and Pz for further analyses. These electrodes are in line with our previous work with this paradigm showing strongest effects at midline frontal to parietal sites (Cooper et al, , ; Wong et al, ). For each power type (i.e., total, phase‐locked, and nonphase‐locked), and for each electrode, switch cost was calculated by subtracting the average power for mixed‐repeat from switch trials and mixing cost by subtracting the average power for all‐repeat trials from the mixed‐repeat .…”

Section: Methodssupporting

confidence: 91%

“…The switch and mixing effects in ERPs and time–frequency power occur over similar time intervals, have similar frontoparietal topography, and are often interpreted as reflecting similar processes (e.g., Cooper et al, ). Furthermore, both measures have been associated with task‐switching performance: Faster response time (RT) is associated with a larger switch positivity (Jost et al, ; Karayanidis, Provost, Brown, Paton, & Heathcote, ), larger mixing positivity (Karayanidis, Provost, et al, ), larger target‐locked P3b (Provost, Jamadar, Heathcote, Brown, & Karayanidis, ), smaller target‐locked N2 (Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, ; Provost et al, ), and lower posttarget mid‐frontal theta power (Cooper et al, ). Moreover, higher theta power and lower theta phase variability during the CTI have been associated with low behavioral variability, suggesting more efficient performance (Cooper et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we seek to examine whether the nonphase‐locked signal provides insight into task‐switching effects that are not evident in the ERP (i.e., only phase‐locked EEG activity) or in total time–frequency power (i.e., both phase‐locked and nonphase‐locked activity). Based on our previous work with this paradigm, we hypothesize that time–frequency effects will be most prominent in the theta band (Cooper et al, , , ). Phase‐locked power is expected to show mixing and switch theta band effects that mirror cue‐locked and target‐locked ERP effects.…”

Section: Introductionmentioning

confidence: 99%

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Task‐switching costs have distinct phase‐locked and nonphase‐locked EEG power effects

et al. 2020

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Event‐related potentials (ERPs) and total time–frequency power analyses have shown that performance costs during task switching are related to differential preparation to switch tasks (switch cost) and repeat the same task (mixing cost) during both proactive control (cue‐to‐target interval; CTI) and reactive control (post‐target). The time–frequency EEG signal is comprised of both phase‐locked activity (associated with stimulus‐specific processes) and nonphase‐locked activity (represents processes thought to persist over longer timeframes and do not contribute to the average ERP). In the present study, we used a cued task‐switching paradigm to examine whether phase‐locked and nonphase‐locked power are differentially modulated by switch and mixing effects in intervals associated with the need for proactive control (CTI) and reactive control (post‐target interval). Phase‐locked activity was observed in the theta and alpha bands, closely resembled that seen for total power, and was consistent with switch and mixing ERP positivities. Nonphase‐locked analyses showed theta and alpha power effects for both switch and mixing effects early in the CTI and as well as more sustained alpha and beta activity around cue onset, and extending from mid‐CTI into the post‐target interval. Nonphase‐locked activity in pretarget alpha and posttarget theta power were both correlated with response time mixing cost. These findings provide novel insight into phase‐locked and nonphase‐locked activity associated with switch and mixing costs that are not evident with ERP or total time–frequency analyses.

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Section: Methodssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Task‐switching costs have distinct phase‐locked and nonphase‐locked EEG power effects

et al. 2020

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“…Although few studies have attempted to deepen the understanding on the temporal dynamics of FMθ activity, most of them agree that its time profile could reflect different mechanisms of cognitive control and the different PFC areas involved for it (Cooper et al, 2019;Sauseng, Tschentscher, & Biel, 2019). Here, we characterize FMθ activity time profile for the planning condition as more demanding and therefore requiring a higher extent of cognitive control.…”

Section: Discussionmentioning

confidence: 94%

Frontal Midline Theta Reflects Cognitive Control During Planning

Domic-Siede

Irani

Valdés

et al. 2019

Preprint

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Neural correlates of cognitive planning are not understood well at present. Behavioral paradigms targeting this function are a current challenge in cognitive neuroscience. We recorded EEG activity while subjects were performing a novel behavioral paradigm that evaluates cognitive planning function. Participants showed longer reaction times and decreased accuracy during the planning condition compared to the control condition, suggesting that the planning condition is more time consuming, therefore reflecting higher cognitive demand. Moreover, cognitive planning induced a frontal midline theta (FMθ) frequency band originating in prefrontal cortex (PFC) as shown in previous cognitive control studies. When subjects began planning, there was a progressive and sustained increase in FMθ starting after 500 milliseconds (ms) of planning. Hence, we characterized for first time, both spatial and temporal FMθ dynamics of cognitive planning as a marker of cognitive control function.

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“…In situations where a planned action should not be immediately performed, proactive control ensures the flexible and cost-efficient updating of relevant information that ensures that the appropriate action will take place at the right time (Pezzullo & Ognibene, 2012). Indeed, recent evidence (Cooper et al, 2015; suggests that proactive control can be further divided in two stage-preparation processes: an early component, which ensure the preparation and the updating of relevant information to face a change, and a later component, that reflects motor readiness (Cooper et al, 2015(Cooper et al, , 2017(Cooper et al, , 2019. Our findings are a close fit with such a dual model account, as the brain dynamics in our study reveal a dissociation demonstrating that ambulatory avoidance of a partially unexpected obstacle relies on the earlier of the two stages of preparation processes.…”

Section: Discussionmentioning

confidence: 99%

Mobile EEG reveals functionally dissociable dynamic processes supporting real-world ambulatory obstacle avoidance: Evidence for early proactive control

Mustile

Kourtis

Ladouce

et al. 2020

Preprint

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The ability to safely negotiate the world on foot takes years to develop in human infants, reflecting the huge cognitive demands associated with real-time dynamic planning and control of walking. Despite the importance of walking, surprisingly little is known about the neural and cognitive processes that support ambulatory motor control in humans. In particular, methodological limitations have, to date, largely prevented study of the neural processes involved in detecting and avoiding obstacles during walking. Here, using mobile EEG during real-world ambulatory obstacle avoidance, we captured the dynamic oscillatory response to changes in the environment. Time-frequency analysis of EEG data revealed clear neural markers of proactive and reactive forms of movement control (occurring before and after crossing an obstacle), visible as increases in frontal theta and centro-parietal beta power respectively. Critically, the temporal profile of changes in frontal theta allowed us to arbitrate between early selection and late correction mechanisms of proactive control: our data show that motor plans are updated as soon as an upcoming obstacle appears, rather than when the obstacle is reached, as previously thought. In addition, regardless of whether motor plans required updating, a clear beta rebound was present after obstacles were crossed, reflecting the resetting of the motor system. Overall, our use of mobile EEG during real-world walking provides novel insight into the cognitive and neural basis of dynamic motor control in humans, suggesting new routes to the monitoring and rehabilitation of motor disorders such as dyspraxia and Parkinson’s disease.

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Frontal theta predicts specific cognitive control-induced behavioural changes beyond general reaction time slowing

Cited by 116 publications

References 64 publications

Task‐switching costs have distinct phase‐locked and nonphase‐locked EEG power effects

Task‐switching costs have distinct phase‐locked and nonphase‐locked EEG power effects

Frontal Midline Theta Reflects Cognitive Control During Planning

Mobile EEG reveals functionally dissociable dynamic processes supporting real-world ambulatory obstacle avoidance: Evidence for early proactive control

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