Elsevier

NeuroImage

Volume 83, December 2013, Pages 912-920
NeuroImage

Lower theta inter-trial phase coherence during performance monitoring is related to higher reaction time variability: A lifespan study

https://doi.org/10.1016/j.neuroimage.2013.07.032Get rights and content

Highlights

  • Study on theta inter-trial phase coherence (ITPC) during performance monitoring

  • Theta ITPC increases from childhood to adulthood and decreases in older age.

  • Lower theta ITPC is related to higher reaction time (RT) variability.

  • Noisier control signals may contribute to greater RT variability across the lifespan.

Abstract

Trial-to-trial reaction time (RT) variability is consistently higher in children and older adults than in younger adults. Converging evidence also indicates that higher RT variability is (a) associated with lower behavioral performance on complex cognitive tasks, (b) distinguishes patients with neurological deficits from healthy individuals, and also (c) predicts longitudinal cognitive decline in older adults. However, so far the processes underlying increased RT variability are poorly understood. Previous evidence suggests that control signals in the medial frontal cortex (MFC) are reflected in theta band activity and may implicate the coordination of distinct brain areas during performance monitoring. We hypothesized that greater trial-to-trial variability in theta power during performance monitoring may be associated with greater behavioral variability in response latencies. We analyzed event-related theta oscillations assessed during a cued-Go/NoGo task in a lifespan sample covering the age range from middle childhood to old age. Our results show that theta inter-trial coherence during NoGo trials increases from childhood to early adulthood, and decreases from early adulthood to old age. Moreover, in all age groups, individuals with higher variability in medial frontal stimulus-locked theta oscillations showed higher trial-to-trial RT variability behaviorally. Importantly, this effect was strongest at high performance monitoring demands and independent of motor response execution as well as theta power. Taken together, our findings reveal that lower theta inter-trial coherence is related to greater behavioral variability within and across age groups. These results hint at the possibility that more variable MFC control may be associated with greater performance fluctuations.

Introduction

Cross-sectional studies have repeatedly reported that within-person trial-to-trial reaction time (RT) variability decreases from childhood to adolescence and increases again from young adulthood to old age (e.g., Dykiert et al., 2012, Li et al., 2004, Li et al., 2009, Williams et al., 2005, Williams et al., 2007). Intra-individual variability in reaction times is generally considered to be an index of central nervous system functioning (for a recent review, see Dykiert et al., 2012). Previous research has shown that elevated RT variability reflects the efficacy of higher level cognitive functioning above and beyond motor executive processes. For instance, RT variability in older adults has been attributed to the decision rather than the motor component of a task (e.g., Bunce et al., 2004). Moreover, higher trial-to-trial RT variability is associated with lower behavioral performance in a variety of complex cognitive tasks (e.g., Hultsch et al., 2002) and has been shown to predict longitudinal cognitive decline in late adulthood, such as in executive functioning (Lövdén et al., 2007) and episodic memory (MacDonald et al., 2003).

In clinical research, deficiency in frontal lobe functioning has been related to higher processing fluctuations. Adult patients with lesions in the frontal lobes usually show more variable RTs in comparison to healthy controls (Murtha et al., 2002, Picton et al., 2007, Stuss et al., 2003, Walker et al., 2000). In healthy adult samples, age differences are particularly pronounced on tasks assessing frontal lobe functioning, such as inhibition (Strauss et al., 2007) and working memory (West et al., 2002; Dixon et al., 2007). Similarly, children with frontal-lobe mediated executive control deficits, such as patients with attention deficit hyperactivity disorder, show higher RT variability than healthy controls (for review, see Kuntsi and Klein, 2012). Indeed, structural, functional and neurochemical declines in the frontal lobes in old age (for reviews, see MacDonald et al., 2006, MacDonald et al., 2009) have been associated with higher within-person variability. However, the functional processes underlying the contribution of the frontal lobe to higher RT fluctuations remain poorly understood.

Three decades of cognitive neuroscience research have established the role of the medial frontal cortex (MFC) in performance monitoring and cognitive control (for review, see Ridderinkhof et al., 2004). More recent investigations on cognitive control suggest that the MFC exerts control by interacting with other task relevant brain regions through neural oscillations in the theta (4–7 Hz) band (e.g., Cavanagh et al., 2009, Cohen et al., 2011, Hanslmayr et al., 2008, Nigbur et al., 2012). Direct intracranial recordings confirm the MFC as a generator of theta band oscillations in humans (Cohen et al., 2008, Wang et al., 2005). Specifically, Cohen and colleagues found that performance during a modified Flanker task was associated with an enhancement of theta power following the response suggesting post-response performance monitoring. In addition, theta oscillations in the MFC and fronto-central scalp electrodes were coupled, indicating that scalp electrodes indeed reflect activity from intracranial sources. In line with the suggested role in cognitive control and monitoring, increases in medial frontal theta band power have been observed in more demanding performance monitoring conditions, such as during Go/NoGo tasks (e.g., Nigbur et al., 2011, Schmiedt-Fehr and Basar-Eroglu, 2011). Furthermore, medial frontal theta activity has been consistently observed to be higher during situations requiring more cognitive control, such as during errors or prior to performance adaptations (e.g., Cavanagh et al., 2012, Cohen et al., 2008, Cohen et al., 2009, Luu and Tucker, 2002, Mazaheri et al., 2009).

Other than amplitude-related measures, the temporal synchronicity of theta oscillations has recently gained more attention in the research on cognitive control. It has been suggested that variability in the stimulus-locked theta phase across trials at single electrodes or between electrodes presumably reflects the temporal coordination of cortical processes (Klimesch et al., 2007, Sauseng and Klimesch, 2008). Given that the theta oscillation is a promising neural correlate for frontally coordinated cognitive control processes, the phase of the oscillation might provide a means for coordinating interactions between distant brain areas (e.g., Cavanagh et al., 2009, Cohen et al., 2011). Of specific relevance for the current study, increasing evidence shows that lower theta inter-trial phase locking at single electrodes is related to behavioral performance (e.g., Klimesch et al., 2004, Groom et al., 2010; Müller et al., 2009, Rutishauser et al., 2010). Specifically, higher RT variability in a Go/NoGo task has been found to be associated with lower inter-trial phase coherence in the theta band in adolescents (Groom et al., 2010), indicating that increased intraindividual variability may be related to more variable electroencephalographic signals in the theta range. However, participants in the Groom et al. (2010) study motorically responded during the condition of interest; therefore, lower coherence in this case may not necessarily reflect variability in higher-level control processes, as lower theta coherence could also have reflected neural variability associated with motor execution processes. To summarize, interindividual differences in RT variability may be due to deficient frontal cognitive control processing. Initial evidence suggests that temporal variability in performance monitoring in the MFC might be a suitable candidate process for studying lifespan developmental and individual differences in behavioral RT variability.

Given the involvement of the MFC in performance monitoring and motor control that is well-established in functional brain imaging studies (for review, see Ridderinkhof et al., 2004), we aimed at investigating whether more variable performance monitoring signals, which are not confounded with motor responses, would be associated with greater variability in response latencies of behavior and brain electrophysiological responses. In addition, we aimed at investigating whether lifespan age differences in RT variability are also reflected in lifespan age differences in the temporal variability of performance monitoring processes.

We analyzed event-related theta oscillations assessed during a cued Go/NoGo task in a lifespan sample (children, adolescents, younger adults, older adults) with a specific focus on inter-trial phase coherence (ITPC). Based on initial evidence relating lower theta ITPC to higher RT variability (Groom et al., 2010) and the well-established lifespan patterns of RT variability (e.g., Li et al., 2004, Williams et al., 2005), we expected an increase in theta NoGo ITPC with maturation and a decrease in old age. Here, we focus particularly on the NoGo condition, as performance monitoring demands are highest in this condition and Go trials may be confounded with response-related activity. Further, we expected that within age groups variability of performance monitoring signals would predict individual differences in behavioral variability. Specifically, we expected that individuals with higher theta inter-trial phase synchrony during the NoGo condition show higher behavioral RT variability. In addition, it remains an open question whether theta power would also predict RT variability. Thus, we further tested whether the magnitude of the theta response would also be predictive of interindividual differences in RT variability or whether the link to behavioral variability is specific to the coherence measure.

Section snippets

Participants

The sample included 182 participants, with 35 children (aged 9 to 11 years; 21 girls), 43 adolescents (aged 12 to 16 years; 22 girls), 46 younger (aged 20 to 28 years; 22 women), and 47 older adults (aged 65 to 75 years; 24 women). Data from 10 children and 1 adolescent were excluded due to an insufficient number of available trials after artifact rejections for time–frequency analyses (i.e., fewer than 25 trials per condition). All participants were right-handed, as indexed by the Edinburgh

Lifespan differences in trial-to-trial RT variability

RT variability during the Go condition is presented in Fig. 1 for the four age groups. The omnibus test yielded a main effect of age group, F(3,76.2) = 35.2, p < .05, ICC = 0.76 (explaining 58% of the total variance in the data). Planned contrasts confirmed a linear, t = 8.84, p < .05, d = 1.76, and curvilinear pattern, t = 8.31, p < .05, d = 1.35, across the lifespan. In line with the curvilinear pattern, pairwise comparisons indicated that adolescents were less variable in their RTs than children, t = 2.43, p < 

Discussion

Here, we investigated whether EEG correlates of more variable performance monitoring signals in the MFC may be related to higher RT variability in a lifespan sample. We found that variability in stimulus-locked EEG signals during performance monitoring is higher at both ends of the lifespan, as indicated by theta ITPC during NoGo trials. This pattern was paralleled by lifespan differences in behavioral variability, with decreasing RT variability from childhood to young adulthood and increasing

Acknowledgments

This research was supported by the German Research Foundation's (DFG) grant for a subproject (Li 515/8-1 to S.-C. L., V. M. and U. L.) in the research group on Conflicts As Signals (DFG FOR778). D. H. was a Ph.D. and postdoctoral fellow supported by this grant. G. P. is a fellow of the International Max Planck Research School, The Life Course: Evolutionary and Ontogenetic Dynamics (LIFE). The manuscript was completed while D. H. was a visiting postdoctoral fellow at the University College

References (62)

  • R. Nigbur et al.

    Theta power as a marker for cognitive interference

    Clin. Neurophysiol.

    (2011)
  • R.C. Oldfield

    The assessment and analysis of handedness: the Edinburgh inventory

    Neuropsychologia

    (1971)
  • J. Onton et al.

    Frontal midline EEG dynamics during working memory

    Neuroimage

    (2005)
  • P. Sauseng et al.

    What does phase information of oscillatory brain activity tell us about cognitive processes?

    Neurosci. Biobehav. Rev.

    (2008)
  • P. Sauseng et al.

    Control mechanisms in working memory: a possible function of EEG theta oscillations

    Neurosci. Biobehav. Rev.

    (2010)
  • C. Schmiedt-Fehr et al.

    Event-related delta and theta brain oscillations reflect age-related changes in both a general and a specific neuronal inhibitory mechanism

    Clin. Neurophysiol.

    (2011)
  • G. Thut et al.

    Rhythmic TMS causes local entrainment of natural oscillatory signatures

    Curr. Biol.

    (2011)
  • R. West et al.

    Lapses of intention and performance variability reveal age-related increases in fluctuations of executive control

    Brain Cogn.

    (2002)
  • B.R. Williams et al.

    Inconsistency in reaction time across the life span

    Neuropsychology

    (2005)
  • L.H. Beck et al.

    A continuous performance test of brain damage

    J. Consult. Clin. Psychol.

    (1956)
  • T.S. Braver et al.

    Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors

    Cereb. Cortex

    (2001)
  • J.F. Cavanagh et al.

    Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring

    J. Neurosci.

    (2009)
  • J.F. Cavanagh et al.

    Theta lingua franca: a common mid-frontal substrate for action monitoring processes

    Psychophysiology

    (2012)
  • M.X. Cohen et al.

    Single-trial regression elucidates the role of prefrontal theta oscillations in response conflict

    Front. Psychol.

    (2011)
  • M.X. Cohen et al.

    Unconscious errors enhance prefrontal–occipital oscillatory synchrony

    Front. Hum. Neurosci.

    (2009)
  • R.A. Dixon et al.

    Neurocognitive resources in cognitive impairment: exploring markers of speed and inconsistency

    Neuropsychology

    (2007)
  • D. Dykiert et al.

    Sex differences in reaction time mean and intraindividual variability across the life span

    Dev. Psychol.

    (2012)
  • E.F. Fern et al.

    Effect-size estimates: issues and problems in interpretation

    J. Consum. Res.

    (1996)
  • M.J. Groom et al.

    Electrophysiological indices of abnormal error-processing in adolescents with attention deficit hyperactivity disorder (ADHD)

    J. Child Psychol. Psychiatry

    (2010)
  • S. Hanslmayr et al.

    The electrophysiological dynamics of interference during the Stroop task

    J. Cogn. Neurosci.

    (2008)
  • D.F. Hultsch et al.

    Variability in reaction time performance of younger and older adults

    J. Gerontol. B Psychol. Sci. Soc. Sci.

    (2002)
  • Cited by (72)

    • Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults

      2022, Brain Stimulation
      Citation Excerpt :

      We developed a novel closed-loop neurostimulation system (see Fig. 1) and used it to test the hypothesis that synchronized application across weeks of rTMS treatment might yield increased entrainment, as observed by the EEG dynamics after stimulation. We assessed entrainment using the inter-trial phase coherence (ITPC) measure, which is a metric to capture how consistent oscillatory phase is across an ensemble of event-locked trials [35,36], and examined how this measure changes over a period of weeks as rTMS is periodically applied either synchronized or unsynchronized to the preferred prefrontal quasi-alpha phase of an individual. We investigated this hypothesis in a group of MDD patients as part of an ongoing double-blind clinical study, where one group receives rTMS synchronized to their quasi-alpha activity (SYNC), while another group receives the same stimulation, but the initial pulse in each train is not synchronized (UNSYNC).

    View all citing articles on Scopus
    1

    Present address: Aging Research Center, Karolinska Institute, S-11330 Stockholm, Sweden.

    2

    Shared first authorship.

    View full text