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Articles, Behavioral/Cognitive

Subthalamic Nucleus Local Field Potential Activity during the Eriksen Flanker Task Reveals a Novel Role for Theta Phase during Conflict Monitoring

Baltazar Zavala, John-Stuart Brittain, Ned Jenkinson, Keyoumars Ashkan, Thomas Foltynie, Patricia Limousin, Ludvic Zrinzo, Alexander L. Green, Tipu Aziz, Kareem Zaghloul and Peter Brown
Journal of Neuroscience 11 September 2013, 33 (37) 14758-14766; https://doi.org/10.1523/JNEUROSCI.1036-13.2013
Baltazar Zavala
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
2Surgical Neurology Branch, National Institutes of Health, Bethesda, Maryland 20814,
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John-Stuart Brittain
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
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Ned Jenkinson
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
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Keyoumars Ashkan
3Department of Neurosurgery, King's College Hospital, Kings College, London SE5 9RS, United Kingdom, and
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Thomas Foltynie
4Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London WC1 3BG, United Kingdom
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Patricia Limousin
4Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London WC1 3BG, United Kingdom
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Ludvic Zrinzo
4Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London WC1 3BG, United Kingdom
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Alexander L. Green
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
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Tipu Aziz
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
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Kareem Zaghloul
2Surgical Neurology Branch, National Institutes of Health, Bethesda, Maryland 20814,
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Peter Brown
1Functional Neurosurgery-Experimental Neurology Group, Nuffield Department of Clinical Neurology, University of Oxford John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,
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    Figure 1.

    Flanker task. A, Task. Each trial began with a warning cue with onset 500 ms before arrows were shown. Arrows were shown for 200 ms, and subjects had 2.2 s to respond before the next warning cue. A 2:1 ratio of incongruent to congruent trials was used. B, Behavioral responses across subjects. To the left are reaction times for all 13 subjects for congruent and incongruent trials. There was a significant difference between mean congruent (green bar with SEM) and incongruent (purple) reaction times. When the incongruent trials were median split into the fastest half (blue) and the slowest half (red), there was no difference in reaction time between the fastest incongruent trials and the congruent trials. The slowest incongruent trials, however, had reaction times that were significantly slower than the congruent trials. C, Average reaction time histograms normalized to each subject's mean incongruent trial reaction time. Incongruent trial histogram reveals two peaks. Color denotes whether trials in a given bin were put in the fast-incongruent (blue) or slow-incongruent (red) groups for further analysis.

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    Figure 2.

    Effects of congruency on LFP across all subjects. A–D, Imperative cue-aligned (t = 0) averages of induced spectral change. Both congruent (A) and incongruent (B) trials showed an increase in cue-aligned theta power, a decrease in beta power followed by a postresponse rebound, and an increase in gamma power. C, Difference between trial types masked at a 0.05 significance level corrected for multiple comparisons, showing the theta band difference. D, Cue-aligned theta (3–8 Hz) band average time series (mean ± SEM) for congruent (green) and incongruent (purple) trials. Significant difference between the two conditions is marked by black bar (p < 0. 05 corrected for multiple comparisons). E–H, Same as A–D but aligned to the response. Theta difference is weaker and only significant in the theta band average time series (H). Note that here and in ensuing time–frequency plots that frequency is given on a log axis.

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    Figure 3.

    Differences between slow and fast trials following incongruent cues across all subjects. A–D, Imperative cue-aligned (t = 0) averages of induced spectral change. A, No power differences between the fast-incongruent trials and congruent trials (masked at p < 0.05 significance level after correcting for multiple comparisons). B, C, Slow-incongruent trials showed higher cue-aligned theta power than congruent trials (B) and fast-incongruent trials (C). D, Theta (3–8 Hz) band average time series for slow-incongruent (red), fast-incongruent (blue), and congruent (green) trials. Note that mean ± SEM values are shown except for congruent trials (where ±SEM values were shown in Fig. 2). Significant difference between trial types is marked by horizontal bars (p < 0.05, corrected for multiple comparisons). E–H, Same as A–D but aligned to the response. Fast-incongruent trials showed no significant difference from the congruent. Preresponse theta power was higher in slow-incongruent trials. Cong, Congruent.

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    Figure 4.

    Cue-locked theta phase realignment is disrupted in slow-incongruent trials. A–E, Imperative cue-aligned (t = 0) averages of phase locking across trials. A, Mean wavelet PLV for all fast-incongruent trials averaged across all 26 STNs. B, Same as A for slow-incongruent trials. C, There is a significant reduction in cue-locked theta PLV when the slow-incongruent trials are compared with fast-incongruent trials (masked at p < 0.05 significance level after correcting for multiple comparisons). D, Theta band filtered Hilbert PLV also showed impaired cue-locked phase alignment in the slow-incongruent trials. Slow-incongruent (red), fast-incongruent (blue), and congruent (green) mean PLV time series are shown ±SEM. Significant differences are denoted by horizontal bars. E, Theta bandpass-filtered Hilbert phase for all trials in all subjects sorted by reaction time (smoothed across each 100 trials and 40 ms). Prominent phase alignment is stimulus locked and independent of reaction time. Dotted black track indicates stimulus onset, and solid black trace indicates trial reaction time. F–J, Same as A–D but aligned to response. Comparison of D and I suggests that there are two phase alignment periods: just after but time locked to stimulus onset (D, arrow pointing to large peak) and periresponse (I, arrow pointing to second peak centered on response at t = 0). Both peaks can be seen in the response-aligned Hilbert PLV of the fast-incongruent trials, which showed the least variable reaction time (I). Cue-locked phase alignment (D) is greater than response-aligned phase alignment (I) for all trial types except slow-incongruent trials, which show impaired cue-locked phase alignment. K, Cue-locked phase alignment (calculated across all correct congruent and incongruent trials) correlated with subject reaction time (r = −0.58, p < 0.05). L, Response-locked phase alignment did not correlate with subject reaction time (r = −0.11). Correlations show the results of linear regression and corresponding 95% confidence limits. Cong, Congruent.

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    Figure 5.

    LFP in error trials across all subjects. A, Incorrect incongruent trials had a group mean reaction time (±SEM) that was faster than slow-incongruent trials but was not different from fast-incongruent trials. B, Induced LFP power changes during incorrect incongruent trials aligned to an imperative cue. C, Differences between incorrect and correct incongruent trials across subjects masked at p < 0.05 (corrected for multiple comparisons). D, E, Same as B and C but aligned to the response. Increases in postresponse delta (2–4 Hz) and low beta (10–20 Hz) power can be seen. Incong, Incongruent.

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    Table 1.

    Clinical details

    CaseAge (years)Disease duration (years)UPDRS off (III)UPDRS on (III)First symptomReasons for surgeryDaily medication (mg/d)
    148125633Leg stiffnessOff state immobilityLevodopa 400, ropinirole 3
    26632722TremorTremor
    36294717RigidityImmobility, stiffness, tremorLevodopa 150, pramipexole 2.1, pramipexole 1.1, levodopa 750
    45292911Weakness in left wristGait difficultiesEntacapone 600, levodopa 600, pramipexole 1.05
    5545286Tremor and leg stiffnessGait difficultiesLevodopa 600, pramipexole 0.35
    66415318Slowness and tremor in right handDyskinesias, unpredictable on/off fluctuationsApomorphine 12, levodopa 450, amantadine 200, rotigotine 16, selegiline 10
    76384310Slowing swallowing, stiffness, painOff-freezingRasagiline 1, levodopa 300, apomorphine 100
    86314336Frozen shoulder and arm stiffnessOff-state gait difficultiesRasagiline 1, pergolide 3, entacapone 400, levodopa 500
    95665219Left-side tremorTremorEntacapone 800, levodopa 400, rotigotine 8
    1073143515Right-side tremorMotor fluctuationsLevodopa 700, rotigotine 16, selegeline 10
    1163143524Right-side tremorTremorLevodopa 150, ropinorole 2, ropinerole 21
    1258104220Leg crampTremorTrihexyphenidyl 3, levodopa 600, rasagline 1, amantadine 100
    136210208Left-side tremor and bradykinesiaOn/off fluctuations, tremor and impulse control disorderLevodopa 1000, trihexyphenidyl 6
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The Journal of Neuroscience: 33 (37)
Journal of Neuroscience
Vol. 33, Issue 37
11 Sep 2013
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Subthalamic Nucleus Local Field Potential Activity during the Eriksen Flanker Task Reveals a Novel Role for Theta Phase during Conflict Monitoring
Baltazar Zavala, John-Stuart Brittain, Ned Jenkinson, Keyoumars Ashkan, Thomas Foltynie, Patricia Limousin, Ludvic Zrinzo, Alexander L. Green, Tipu Aziz, Kareem Zaghloul, Peter Brown
Journal of Neuroscience 11 September 2013, 33 (37) 14758-14766; DOI: 10.1523/JNEUROSCI.1036-13.2013

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Subthalamic Nucleus Local Field Potential Activity during the Eriksen Flanker Task Reveals a Novel Role for Theta Phase during Conflict Monitoring
Baltazar Zavala, John-Stuart Brittain, Ned Jenkinson, Keyoumars Ashkan, Thomas Foltynie, Patricia Limousin, Ludvic Zrinzo, Alexander L. Green, Tipu Aziz, Kareem Zaghloul, Peter Brown
Journal of Neuroscience 11 September 2013, 33 (37) 14758-14766; DOI: 10.1523/JNEUROSCI.1036-13.2013
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  • STN and cognition: two perspectives on conflict
    Alberto Priori
    Published on: 02 January 2014
  • Published on: (2 January 2014)
    Page navigation anchor for STN and cognition: two perspectives on conflict
    STN and cognition: two perspectives on conflict
    • Alberto Priori, Professor
    • Other Contributors:
      • Manuela Fumagalli, Manuela Rosa, Sara Marceglia

    Studies conducted over the past three years by recording local field potentials (LFPs) from the subthalamic nucleus (STN) show that this brain structure has a role in human conflict processing. Although these findings have raised worldwide research interest and produced some new data, no study has yet reached definitive conclusions mainly because current literature offers two different ways of interpreting conflict.

    ...
    Show More

    Studies conducted over the past three years by recording local field potentials (LFPs) from the subthalamic nucleus (STN) show that this brain structure has a role in human conflict processing. Although these findings have raised worldwide research interest and produced some new data, no study has yet reached definitive conclusions mainly because current literature offers two different ways of interpreting conflict.

    One interpretation defines conflict as the difficulty in choosing from among a set of equally permissible responses (Botvinick et al., 2004; Frank, 2006) and the STN "dynamically controls the threshold for executing a response allowing all information to be integrated before making decisions" (Frank 2006). In line with this idea, some studies investigated the STN's role in conflictuality by using decision-making tasks: economic task (Rosa et al., 2013), forced choice task (Cavanagh et al., 2011) and socio-moral task (Fumagalli et al., 2011).

    An alternative view regards conflict as the competition between the correct response and the response being overridden (Botvinick et al., 2004). Overcoming conflict means inhibiting the prepotent and automatic response so as to give the correct one. According to this definition, some studies tested conflict with the Stroop task (Brittain et al., 2012), Stop signal task (Alegre et al., 2013) and Flanker task (Zavala et al., 2013).

    STN LFPs recorded during tasks of both kinds showed similar power modulations failing to differentiate between these two perspectives on conflict. Similarly, the anterior cingulate cortex (ACC), the major brain region involved in conflict, has a role both in conflictual decision- making and in conflict monitoring. An attempt to reconcile these two different functions is done in order to have an integrated and coherent account of ACC function: conflict is considered as part of an avoidance learning mechanism and functions as an aversive or negatively reinforcing event (Botvinick, 2007).

    Although ACC has an influence on midbrain dopaminergic neurons and on STN (Botvinick, 2007; Frank et al., 2007), to hypothesize that the integration of the two conflict perspectives is also adaptable to STN is too early. Future studies could contribute to this issue by clearly distinguishing between these two perspectives at both a cognitive and a neurophysiological level.

    References

    Alegre M, Lopez-Azcarate J, Obeso I, Wilkinson L, Rodriguez-Oroz MC, Valencia M, Garcia-Garcia D, Guridi J, Artieda J, Jahanshahi M, Obeso JA (2013) The subthalamic nucleus is involved in successful inhibition in the stop-signal task: a local field potential study in Parkinson's disease. Exp Neurol 239:1-12.

    Botvinick MM (2007) Conflict monitoring and decision making: reconciling two perspectives on anterior cingulate function. Cogn Affect Behav Neurosci 7:356-366.

    Botvinick MM, Cohen JD, Carter CS (2004) Conflict monitoring and anterior cingulate cortex: an update. Trends Cogn Sci 8:539-546.

    Brittain JS, Watkins KE, Joundi RA, Ray NJ, Holland P, Green AL, Aziz TZ, Jenkinson N (2012) A role for the subthalamic nucleus in response inhibition during conflict. J Neurosci 32:13396-13401.

    Cavanagh JF, Wiecki TV, Cohen MX, Figueroa CM, Samanta J, Sherman SJ, Frank MJ (2011) Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold. Nat Neurosci 14:1462-1467.

    Frank MJ (2006) Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making. Neural Netw 19:1120-1136.

    Frank MJ, Samanta J, Moustafa AA, Sherman SJ (2007) Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism. Science 318:1309-1312.

    Fumagalli M, Giannicola G, Rosa M, Marceglia S, Lucchiari C, Mrakic- Sposta S, Servello D, Pacchetti C, Porta M, Sassi M, Zangaglia R, Franzini A, Albanese A, Romito L, Piacentini S, Zago S, Pravettoni G, Barbieri S, Priori A (2011) Conflict-dependent dynamic of subthalamic nucleus oscillations during moral decisions. Soc Neurosci 6:243-256.

    Rosa M, Fumagalli M, Giannicola G, Marceglia S, Lucchiari C, Servello D, Franzini A, Pacchetti C, Romito L, Albanese A, Porta M, Pravettoni G, Priori A (2013) Pathological gambling in Parkinson's disease: subthalamic oscillations during economics decisions. Mov Disord 28:1644-1652.

    Zavala B, Brittain JS, Jenkinson N, Ashkan K, Foltynie T, Limousin P, Zrinzo L, Green AL, Aziz T, Zaghloul K, Brown P (2013) Subthalamic nucleus local field potential activity during the Eriksen flanker task reveals a novel role for theta phase during conflict monitoring. J Neurosci 33:14758 -14766.

    Conflict of Interest:

    None declared

    Show Less
    Competing Interests: None declared.

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