NoGo task

International Journal of Psychophysiology 86 (2012) 251–261

Contents lists available at SciVerse ScienceDirect

International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho

EEG–ERP phase dynamics of children in the auditory Go/NoGo task Robert J. Barry ⁎, Frances M. De Blasio Centre for Psychophysics, Psychophysiology, and Psychopharmacology, Brain & Behaviour Research Institute, and School of Psychology, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia

a r t i c l e

i n f o

Article history: Received 11 July 2012 Received in revised form 1 September 2012 Accepted 2 October 2012 Available online 7 October 2012 Keywords: Brain dynamics Event-related potentials Orthogonal phase effects Phase synchronisation Auditory Go/NoGo task Children

a b s t r a c t Using a child sample, we examined the effects of the phase of narrow-band electroencephalographic (EEG) activity at stimulus onset on the resultant event-related potentials (ERPs) in an equiprobable auditory Go/NoGo task with a fixed stimulus-onset asynchrony. We used FFT decomposition of the EEG at Cz to assess prestimulus narrow-band EEG activity (in 1 Hz bands from 1 to 13 Hz) for each trial. From the cycle at stimulus onset, trials were sorted into four phases for each of the 13 frequencies. ERPs were derived for each of these from the raw EEG activity at the midline sites. ERP responses were analysed in the context of a simple conceptualisation of orthogonal phase effects (cortical negativity vs. positivity, negative driving vs. positive driving, waxing vs. waning). At a number of frequencies, crossing the traditional frequency bands, the predicted non-random occurrence of phase-defined brain states was confirmed. The preferred states of negativity and negative driving were each associated with more efficient stimulus processing, as reflected in latency and amplitude differences of the N1 and P3 ERP components. The present results confirm the existence of preferred brain states and their impact on the efficiency of brain dynamics involved in perceptual and cognitive processing, and extend their occurrence from adults to children. © 2012 Elsevier B.V. All rights reserved.

1. Introduction It is generally accepted that the processing of individual stimuli in cognitive/perceptual activities is dependent on the current state of the electroencephalogram (EEG) at stimulus onset (Başar, 1980; Makeig et al., 2004; Barry, 2009). Başar and Stampfer (1985) began an important line of brain-dynamics research focused on the phase of the ongoing EEG. They found that regularly-presented stimuli modified the phase of the ongoing EEG, producing a “preferred phase angle” in delta and alpha frequency bands, such that cortical negativity at stimulus onset was enhanced. This effect is complemented by earlier work reporting that presenting stimuli at negative peaks of the alpha cycle produces shorter reaction times (Callaway and Yeager, 1960; Trimble and Potts, 1975). Also, Rémond and Lesèvre (1967) had reported phase-related enhancements around 80 ms in their visualevoked ERPs, particularly for stimuli presented at the negative peak of alpha activity. They considered this to be an indirect effect of a non-specific mechanism increasing the state of alertness. Together these suggest that Başar and Stampfer's (1985) phase reordering is important in perceptual/cognitive functioning. Other evidence of similar dynamic phase adjustment has also been noted (Başar et al., 1984; Rockstroh et al., 1989; Pleydell-Pearce, 1994). In relation to the current models of ERP genesis (e.g., Barry, 2009), this line of research is most relevant to the phase-reset model. ⁎ Corresponding author. Tel./fax: +61 2 4221 4421. E-mail address: [email protected] (R.J. Barry). 0167-8760/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijpsycho.2012.10.001

To simplify working with comparative phase angles in the EEG context, Barry et al. (2003) introduced more-intuitive phase groupings, using the physical dimensions of phase, and based on the quartile divisions shown in Fig. 1. Addressing the phase phenomena described above, cortical negativity/positivity compares the effects of phase divisions (A+ B) versus (C+ D). Negative/positive driving, comparing (A+ D) versus (B+ C), assesses the change in cortical negativity (increasing vs. decreasing). This dimension accommodates other ERP effects reported when stimuli are presented at the positive-going zero crossing of alpha activity (Rémond and Lesèvre, 1967; Jansen and Brandt, 1991). A third dimension, waxing (A+ C) versus waning (B+ D), was introduced by Barry et al. (2004b) in their study of alpha phase effects, and refers to the change in amplitude (increasing vs. decreasing), regardless of the polarity. Together these three dimensions represent a set of orthogonal (statistically independent) comparisons among the means of the four divisions of phase activity defined in Fig. 1. In order to assist communication, throughout this paper, we will use italics to label one extreme of each of these orthogonal dimensions of EEG phase: negativity, negative driving, and waxing. Our research group has been interested in systematically exploring the effects of EEG phase at stimulus onset. Our initial studies examined the effects on ERPs in auditory oddball tasks, and as subdividing ERPs in terms of phase requires many responses, we were able to examine phase effects only in the ERPs to standards. In our first study we used a fixed stimulus-onset asynchrony (SOA) 15% target auditory oddball task which required a button-press target response. We found that narrow (1 Hz wide) EEG bands were dynamically adjusted to provide

252

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

Fig. 1. A schematic representation of the narrow-band EEG phase definitions. Phases (A + B) define cortical negativity, (A + D) define negative driving, and (A + C) define waxing. For each pair defining a dimension (e.g., A+ D), the remaining two phases (e.g., B + C) define the other extreme of that dimension. These three orthogonal dimensions are easier to conceptualise than traditional phase measures (degrees or radians).

“preferred brain states” at stimulus onset (Barry et al., 2003), compatible with Başar and Stampfer's (1985) earlier description of band effects. As expected, preferential occurrence of some of the phase states (e.g. negativity c.f. positivity) was found in various frequencies, at up to double the rate expected by chance. These effects were not confined to the traditional EEG bands, lending support to our narrow-band approach. The preferred states were also associated with large effects in the ERPs to standards, demonstrating their facilitation of the cortical processing involved. Hence we continued our narrow-band exploration of preferred phase effects using auditory oddball tasks. Barry et al. (2006) reported a preliminary study using data from a passive paradigm in which deviant and standard stimuli differed in intensity, comparing groups of subjects with interchanged deviant/standard intensities. The parameters were broadly comparable to those used by Barry et al. (2003), although the fixed ISI was changed to a slightly-varying ISI. Importantly, and as predicted, the occurrence of preferred brain states was reduced by this change in ISI. In this passive oddball paradigm, the preferred states were found to be functionally effective, leading to more efficient processing of the standards. A second preliminary study of these phenomena (Barry et al., 2007) compared the passive low-intensity standards group from Barry et al. (2006) with data from a group that had to button-press in response to the deviants in the identical auditory sequence. This change in task produced differences in prestimulus preparatory processes, preferred brain states, and ERPs to the standards. Preferred brain states (~ 20% more frequent than expected by chance) again produced more-efficient processing. We then extended and integrated these exploratory oddball studies with additional subjects to form a full factorial design (Barry et al., 2009). A fourth group was added (active task with High intensity standards) to the three groups assessed in the preliminary studies: passive task with High and Low intensity standards in Barry et al. (2006); and active and passive tasks with Low intensity standards in Barry et al. (2007). This enabled testing of interactions between stimulus intensity and task. Barry et al. (2009) confirmed the existence of preferred phase-defined brain states, found clear phase effects in each of the ERP components measured, and confirmed that the preferred brain states were functionally efficient and enhanced stimulus processing. Compatible with the role of oscillatory phase-amplitude modulations reviewed by Schroeder and Lakatos (2009), the preferred brain states appeared to be reflexive in nature, with little evidence of variation between the four groups, suggesting that their determination was largely due to the timing of stimulus presentation.

Subsequently, Barry et al. (2010) examined preferred brain states in an equiprobable auditory Go/NoGo paradigm (sometimes called a 50% oddball task; Barry et al., 2000) with fixed SOA. This task was chosen as it provides large numbers of stimuli (necessary for phase grouping) involving two different processing chains: Go and NoGo. Note that this paradigm differs from the usual Go/NoGo task (which has a high proportion of Go trials) and requires minimal inhibition in the NoGo response. In essence, Go responses require effortful processing; NoGo responses do not (Barry and Rushby, 2006). All previous studies in this research stream from our laboratory had used digital filtering, but Barry et al. (2010) instead used the Fast Fourier Transformation (FFT) to decompose the ongoing EEG into narrow bands. It was of substantial interest whether comparable phaserelated results would be obtained in this different paradigm with such a difference in the narrow-band separation technique. Differential phase occurrence at stimulus onset again occurred across the 1–13 Hz narrow frequency bands. These preferred phase states were associated with more efficient processing of the stimuli, as reflected in differences in latency and amplitude of the N1 and P3 ERP components examined. These phase effects differed between Go and NoGo stimuli, emphasising their contribution to the different cortical processing involved. The results confirmed the existence of preferred brain states and their impact on the efficiency of brain dynamics involved in perceptual and cognitive processing, generalising to both a new paradigm, and a new narrow-band extraction process. All our previous phase studies discussed above explored the phenomenon in adults. In order to extend knowledge on the pervasiveness of preferred phase states in these types of paradigms, and their effects on cortical processing, here we repeat the Barry et al. (2010) study with a group of children, aged 8 to 13 years. As children differ from adults in both their EEG spectrum (Barry and Clarke, 2009) and ERP morphology in the Go/NoGo task (Johnstone et al., 2005), this change in age group was expected to impact substantially on numerous aspects of the previous results. Details of the nature of this impact cannot be predicted, as this is the first study of the preferred phase phenomenon in children. Nevertheless, it was expected that the preferential occurrence of different phase states at stimulus onset would be confirmed across our frequency range (1–13 Hz). In line with many developmental markers of cognitive processing, it was expected that the occurrence of preferred phase states would be less developed in children than in adults, providing a generally-weaker picture of preferred phase occurrence and their effects on the ERP markers of stimulus processing in the Go/NoGo task. To facilitate such comparisons, relevant adult data are supplied from Barry et al. (2010). 2. Materials and methods 2.1. Participants Twenty-four children (16 males and 8 females), aged between 8 and 13 (M = 10.2, SD = 1.4 years), participated in this study. Children were recruited from local schools and community groups, and screened for neurological diseases, head injuries, learning disabilities and psychiatric conditions. Children were required to abstain from caffeine and other psychoactive substances for at least 4 h prior to the study. Participation was voluntary and written informed consent from the parent/guardian was obtained following a protocol approved by the joint University of Wollongong/South East Sydney and Illawarra Area Health Service Human Research Ethics Committee, in accordance with the Declaration of Helsinki. 2.2. Procedure EEG was recorded from 19 scalp sites using an electrode cap with tin electrodes, referenced to linked ears. Vertical electro-oculogram

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

(EOG) was recorded from electrodes above and below one eye, and horizontal EOG from electrodes beyond the outer canthi. All impedances were below 5 kΩ. Data were continuously sampled with an AMLAB II system (Associative Measurement) at a rate of 512 Hz, a time constant of 5 s, and an upper-cut-off frequency of 35 Hz, and data were stored for off-line analysis. EEG was recorded with a gain of 20 000, and EOG with a gain of 5000. Subjects were seated in a comfortable chair within an airconditioned sound-reduced room located adjacent to the room housing the recording equipment. Four blocks of an auditory Go/NoGo task were presented to each subject via circumaural headphones. Each presentation block consisted of 150 tones of 60 dB SPL, 50 ms duration and 5 ms rise/fall times, presented with a fixed SOA of 1100 ms. Half the tones were 1000 Hz and half were 1500 Hz, with these delivered in a randomised order. The participants were required to button-press to one of the tones, with the target frequency alternated between participants; they were asked to remain fixated on a small cross displayed on a computer monitor (CRT) 1 m in front of them, and also to refrain from blinking. Note that, because children make more errors and have more movement-related artefacts than adults, the total number of stimuli presented was doubled from our previous adult study, by increasing the number of blocks from two to four. 2.3. EEG post-processing EEG post-processing was carried out within MATLAB® (R14SP3, The MathWorks, Natic, MA) and EEGLAB (Version 6.01b; Delorme and Makeig, 2004). The recorded EEG from Cz for the whole of each block (171 s in duration) was treated as one epoch, and decomposed by FFT separately for each subject. Frequencies within ±0.5 Hz of each narrow band's centre frequency were selected and recombined via separate inverse-FFTs to form 13 bands of 1 Hz bandwidth centred from 1 to 13 Hz. This process is equivalent to realising ideal acausal filters. Barry et al. (2010) illustrated the characteristics of our high-resolution frequency decomposition, using a white noise sample derived from epochs of the same size as our real EEG block, which showed no suggestion of “ringing” in the narrow-band data. The following quantification protocol was individually applied to each of the 1 Hz narrow EEG bands, for each of the Go and NoGo stimulus conditions separately. First, 1 s epochs were derived (±500 ms relative to stimulus onset) and baselined across their duration. Those trials containing muscular or other artefact, ocular activity >100 μV, or incorrect responses (commission errors to NoGo trials, or Go RTs > 500 ms) were identified and excluded from further analysis. For each accepted trial, the phase at stimulus onset was determined at Cz using a 1-cycle sinusoidal wavelet, and this was used to categorise the epochs into four groups (labelled A, B, C and D), corresponding to the four phase ranges shown in Fig. 1: 0–π/2, π/2–π, π–3π/2, and 3π/2–2π. The proportion of trials, and both the pre- and poststimulus root mean square (RMS) narrow-band amplitudes were computed for each phase range, and these were recorded for later analysis. ERPs were derived from the sub-divided narrow-band trials, and from the corresponding wide-band epochs, each at three midline sites (Fz, Cz, and Pz). For each subject, this produced four averaged 1 Hz narrow-band and four averaged wide-band ERPs at each site, differing in narrow-band phase at stimulus onset at Cz, for each of the 13 narrow frequency bands and stimulus types. All ERP epochs commenced 500 ms prestimulus, included 1000 ms of data, and were baselined across the 100 ms period immediately prestimulus. The CNV, defined as the difference between mean amplitudes in the (−500 to −250 ms) and (−100 to 0 ms) prestimulus ranges, was computed from the wide-band ERP data and recorded for later analysis. The ERP data were converted to Neuroscan format (Version 4.3, Compumedics Ltd., Abbotsford, Australia) and an automated function was used to identify the component peaks within set latency ranges. ERP amplitudes and latencies were obtained for the N1 (in the

253

60–160 ms range) and P3 (230–490 ms) components, and all identified peaks were visually inspected by an experienced ERP researcher who manually adjusted inappropriate selections. 2.4. Statistical analyses To assess the occurrence of preferred brain states, the proportion of trials identified in each phase range was obtained for each frequency band and analysed with a two-way repeated-measures multivariate analysis of variance (MANOVA). Three orthogonal Phase contrasts were examined, representing the novel conceptualisation described earlier (negativity vs. positivity, negative driving vs. positive driving, waxing vs. waning), as was a contrast examining the effect of stimulus Type (Go vs. NoGo), and their interaction. Phase effects in Go reaction time (RT) were examined in a one-way ANOVA over Phase, using the above orthogonal phase contrasts. Prestimulus differences in RMS amplitude, RMS changes associated with stimulus onset, and CNV amplitudes, were examined in separate three-way MANOVAs, with the within-subjects factors of Topography, Phase, and stimulus Type (Go vs. NoGo), for each 1 Hz separated data stream (1, 2, 3, …. 13 Hz) individually. Within Topography, sagittal effects were examined with planned orthogonal contrasts comparing Fz vs. Pz, and Cz vs. the mean of Fz and Pz values. Within Phase, the three orthogonal contrasts described above were examined. N1 and P3 amplitude and latency data were analysed in separate MANOVAs as a function of Topography and Phase, using the contrasts outlined above, independently for Go and NoGo responses. The problems of multiple testing were carefully considered given the extensive statistical analyses involved in this study. For each single frequency, the contrasts in each analysis of a particular measure were planned, and there were fewer of them than the degrees of freedom for effect; hence Bonferroni-type adjustments to α were unnecessary (Tabachnick and Fidell, 1989). However, as the effects in a particular measure were assessed via repeated testing at 13 narrow-band frequencies, a Bonferroni correction was applied for all reported probabilities. This means that, for any specific dependent variable (e.g., N1 amplitude), the probabilities of all results reported are conservatively protected via the Bonferroni correction. An individual test required p b .00385 to achieve a corrected p b .05, so values approaching significance (corrected p b .10) are reported to encourage further exploration, although these are not discussed. We also assess phase effects in a number of variables, each of which may be considered to constitute a separate experiment. The increased number of variables/experiments increases the frequency, but not the probability, of Type I errors. This cannot be ‘controlled’ by adjusting alpha levels (Howell, 1997). For example, within 20 significant results for any one variable, the corrected Type I error rate of .05 means that 1 is likely to be a false positive. This likelihood of 1 error in each 20 significant tests remains if we assess two variables (e.g., N1 and P3 latency) — although considering the second set of (say) 20 significant tests increases the expected frequency of Type I errors to 2, the probability is unchanged (2 in 40 tests = .05). All F tests reported here had (1, 23) degrees of freedom. The problems of non-sphericity often encountered with repeated-measures analyses of physiological variables are precluded by our single degree of freedom contrasts, and hence there is no need for their control using Greenhouse–Geisser type epsilon adjustments (O'Brien and Kaiser, 1985). In order to save space, only phase-related effects are reported at length, as these were of primary interest. 3. Results 3.1. Grand mean ERPs Across the 24 subjects, the number of accepted epochs ranged from 68 to 261 (M = 153.4, SD = 50.3) for the Go stimuli, and from

254

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

103 to 278 (M = 189.5, SD = 47.4) for the NoGo stimuli (more Go trials were lost through non-responses [misses]). Fig. 2 illustrates the mean Go and NoGo ERPs at the midline sites for this child sample (solid lines). The prestimulus period shows evidence of a CNV, and poststimulus, a P1 is visible at around 60 ms (not examined further), as are a frontocentral N1 at approx. 100 ms, and a large P3 between 300 and 400 ms. The typical adult P3 distribution in this task, a parietally distributed Go P3b and the anteriorisation of the NoGo P3a (Barry and Rushby, 2006), is clearly evident in the child data. P2 (~ 140 ms) and N2 (~220 ms) peaks are also apparent between N1 and P3, but these were not examined further. The frontal components are embedded in a large negativity over most of the epoch, reflecting the Nc commonly found in child ERPs (Courchesne, 1977). Overlaid on Fig. 2 (dashed lines) are the corresponding ERPs from our previous adult study (Barry et al., 2010). It can be seen that children have an N1 latency and amplitude broadly similar to adults, but P3 is smaller and less defined. Also, the greatest Go/NoGo difference is markedly more posterior in children than adults.

Fig. 2. Grand mean ERPs for each condition are shown at each analysed site. Children are indicated by unbroken lines; adults by dashed lines. Note the large Go/NoGo difference in the P3. The Go response (black line) shows a markedly posterior dominance; the NoGo response (grey line) is dominant at the vertex. The unique broad frontal negativity in children, Nc, is readily apparent at Fz.

3.2. RMS amplitudes of narrow-band EEG activity in the pre- and post-stimulus epochs Prestimulus RMS amplitudes are shown as a function of narrowband frequency in Fig. 3 for the analysed sites. There was no main effect of Go vs. NoGo (all p > .359), and no difference in prestimulus topography between the conditions (all p > .152). Across stimuli, amplitudes were greater parietally at 10 Hz (p = .001) and 11 Hz (p = .013), and somewhat so at 9 Hz (p = .069). They were reduced at Cz compared with Fz/Pz at 1 Hz (p = .013) and 13 Hz (p = .004), and greater at Cz at 4 and 5 Hz (p b .001). Overlaid on Fig. 3 are the prestimulus RMS amplitudes from our previous adult study (Barry et al., 2010). Compared with adults, it can be seen that children have globally-increased slow wave activity

Fig. 3. Prestimulus RMS amplitudes are shown as a function of frequency band at each analysed site, for the present child sample, and also our previous adult study. There are no Go/NoGo differences.

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

and reduced alpha activity (particularly parietally) of lower peak frequency. There was little overall change in RMS amplitudes at stimulus onset, and again there was no main effect of stimulus condition (all p > .144). At 6 Hz, RMS amplitudes showed a significant increase at Cz compared with Fz/Pz in NoGo compared with Go (p = .035). 3.3. Preferential occurrence of EEG phases at stimulus onset The preferential occurrence of the different phases at stimulus onset is illustrated in Fig. 4 for a single participant's Go data at Cz. The amplitudes for each successful Go trial are displayed as a function

255

of time in the top section of panels a and d, with the resultant mean ERP across the trials illustrated below each. Panel a presents the raw EEG for all accepted trials, in order of stimulus presentation. Panel b presents the corresponding 9 Hz data-stream, with the trials ordered according to their phase at stimulus onset, while panel d shows the raw EEG trial data (as in panel a) presented in terms of the 9 Hz phase at stimulus onset (i.e., trials ordered as in panel b). The trial divisions for phases A, B, C, and D at stimulus onset are also indicated in panels b and d. The non-random distribution of the trials across the four phases is apparent and, in this participant, the preferential occurrence of phases A and B (negativity) at 9 Hz is clearly evident. The mean ERPs derived from the phase sorted trials

Fig. 4. Example of the occurrence of preferred brain states at stimulus onset in Go data from a single child subject. Panel a shows EEG at Cz for all accepted Go trials in order of stimulus presentation, with one horizontal line per trial showing the amplitude at each time point. The mean across trials is shown below as the traditional ERP. Panel b shows the corresponding 9 Hz data stream sorted by the phase at stimulus onset, with the four phases defined in Fig. 1 indicated. Panel c shows the mean narrow-band ERP from each phase. Panel d shows the raw trials from panel a rearranged in the phase order of panel b. The mean ERP from each phase division is shown in panel e.

256

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

3.4. Phase effects

for each of the four phase ranges are displayed in panel c for the 9 Hz data (compare phase at time 0 with Fig. 1 phase definitions). The mean ERPs for each phase derived from the corresponding raw EEG data are shown in panel e, where the N1 activity is noticeably predominant in phases A and B (negativity). Across all subjects, in terms of preferred brain states, negativity occurred significantly more often than positivity at 1 Hz (p = .004), 8 Hz (p = .012), and 9 Hz (p = .001), and less often at 6 Hz (p = .006). These and all other negativity vs. positivity effects are shown in Table 1. Negative driving occurred significantly more often than positive driving phases at 5 Hz (p b .001) and 10 Hz (p = .022), and less often at 7 Hz (p b .001) and 8 Hz (p = .004). At 1 Hz, negative driving occurred less frequently than positive driving for Go stimuli, and this was reversed for NoGo (p = .018) (see Table 2 for these and all other negative driving vs. positive driving effects). Waxing did not occur significantly more often than waning phases at any frequency. However, at 5 Hz, waxing occurred more frequently than waning for Go stimuli, and this was reversed for NoGo (p b .001) (see Table 3 for all waxing vs. waning effects). The occurrence of these preferred phases (main effects as listed above) was substantial, with the preferred phases occurring some 13–38% more often than the non-preferred phases. Note that the phase effects found in our adult study (Barry et al., 2010) are indicated with shaded cells in each of the three tables; dark grey identifies an increase in the preferred brain states, and light grey a decrease.

3.4.1. RT At 2 Hz, RT was significantly reduced (p = .045) in negative driving phases (M = 333.9, SD = 28.8 ms) compared with positive driving phases (M = 347.6, SD = 28.2 ms). There were no other phase effects on RT.

3.4.2. RMS amplitudes Prestimulus RMS amplitudes were larger in negativity phases at 1 Hz (p = .001), particularly parietally (p b .001); at 4 Hz parietally (p = .006); at 8 Hz (p b .001); and somewhat so at 9 Hz centrally (N.B. p values for near-significant phase effects are shown in the relevant table). Amplitudes were smaller in negativity at 3 Hz (p = .022), particularly frontally (p b .001). In negative driving, RMS amplitudes were enhanced at 1 Hz frontally (p b .001); at 2 Hz (p = .010), particularly frontally (p = .017); and at 11 Hz there was some overall increase. Prestimulus amplitudes were reduced at 3 Hz centrally (p = .006); at 4 Hz (p = .025) and 5 Hz (p = .027), each particularly frontally (4 Hz: p b .001; 5 Hz: p = .010); and at 6 Hz (p = .038), somewhat more so centrally. The 1 Hz frontal enhancement was greater for Go than NoGo (p = .002), while the frontal activity at 3 Hz was enhanced in NoGo (p = .028). Waxing phases were associated with significant reductions at 2 Hz (p b .001), particularly centrally (p b .001),

Table 1 Significant phase effects obtained in the dependent variables as a function of negativity vs. positivity.

Dependent variable

Effect

Number Prestimulus RMS amplitude

Phase Phase Phase × F < P Phase × C > F/P Phase Phase × F > P Phase × C > F/P Phase × Go > NoGo F > P Phase Phase × F < P Phase × C > F/P Phase × Go> NoGo Go responses Phase Phase × C > F/P NoGo responses Phase Phase × F < P Phase × C > F/P Go responses Phase Phase × C > F/P NoGo responses Phase Phase × F < P Phase × C > F/P Go responses Phase Phase × F < P Phase × C > F/P NoGo responses Phase Phase × F < P Phase × C > F/P Go responses Phase NoGo responses Phase

Poststim. increase in RMS amplitude

CNV amplitude

N1 amplitude

N1 latency

P3 amplitude

P3 latency

1 ↑*** ↑*** ↑***

2

3

4

↓* ↑*

↑**

↑.077

↑*** ↑***

5

6 ↓**

Frequency (Hz) 7 8 ↑* ↑***

9 ↑***

10

11

12

13

↑.076 ↓*

↓*** ↑.083 ↓*

↓** ↑*** ↑*** ↑***

↑***

↑***

↑***

↑***

↑**

↓.061

↓*

↑* ↓.064

↓* ↓**

↓***

↓*** ↓***

↓*** ↓***

↓*** ↓***

↓***

↓***

↓***

↓***

↓***

↓*

↓***

↓***

↓.064

↓*

↓***

↑.081

↑**

↑*** ↑.077

↑***

↑*** ↑.054

↓**

↓* ↓**

↑*** ↑*** ↑*** ↑*** ↑*** ↑***

↑*** ↑.085

↑***

↑***

↑* ↑* ↑*

↑***

↑***

↑*

↓** ↓*

↓***

↓***

↓***

↓***

↓***

↑*** ↑*** ↑***

↑*

↑***

↑*

↓***

↑*

↓***

↑***

↓***

↓***

↑.060

↑ larger for negativity; ↓ smaller for negativity; *significant at p b .05; **significant at p b .01; ***significant at p b .005; probability is indicated for the effects approaching significance. Shading indicates the effects found in adults: dark grey ↑ negativity; light grey ↓ negativity.

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

257

Table 2 Significant phase effects obtained in the dependent variables as a function of negative driving vs. positive driving.

Dependent variable

Effect

Number

Phase Phase × Go < NoGo Phase Phase Phase × F > P Phase × C > F/P Phase × Go > NoGo × F > P Phase Phase × F > P Phase × C > F/P Phase × Go P Phase Phase × C > F/P Go responses Phase Phase × F < P Phase × C > F/P NoGo responses Phase Phase × C > F/P Go responses Phase NoGo responses Phase Phase × C > F/P Go responses Phase Phase × C > F/P NoGo responses Phase Phase × C > F/P Go responses Phase NoGo responses Phase

Reaction time (Go) Prestimulus RMS amplitude

Poststim. increase in RMS amplitude

CNV amplitude N1 amplitude

N1 latency

P3 amplitude

P3 latency

1

2

3

4

5 ↑***

↓* ↓***

↓* ↓**

6

Frequency (Hz) 7 8 ↓*** ↓***

9

10 ↑*

11

12

13

↑*

↑***

↓* ↑** ↑*

↓** ↓**

↑.087

↓.093

↓** ↓*

↑***

↓*

↑**

↑*

↓**

↑*

↑***

↓**

↓*** ↓***

↓*** ↓***

↓*

↑* ↑*** ↑***

↓*** ↓***

↓*** ↓***

↓*** ↓***

↑***

↑***

↑***

↑***

↓*

↑***

↑***

↑***

↑***

↓*

↑*** ↑***

↑*** ↑***

↑*** ↑***

↑*** ↑***

↑*** ↑.056

↓***

↓***

↓***

↓***

↓*** ↓*** ↓*** ↓***

↑*

↓***

↓*** ↓***

↓*** ↓.062

↓*** ↓*

↓* ↓*

↓*** ↓***

↓***

↑**

↓**

↓***

↑***

↓**

↓***

↓.096 ↓.055 ↓.071 ↓.089 ↓*

↓**

↑***

↑***

↑***

↑*

↓*

↑.077

↑***

↑***

↑*

↓***

↑*** ↑***

↓.082

↑ larger for negative driving; ↓ smaller for negative driving; *significant at p b .05; **significant at p b .01; ***significant at p b .005; probability is indicated for the effects approaching significance. Shading indicates the effects found in adults: dark grey ↑ negative driving, light grey ↓ negative driving.

and there was also some reduction in prestimulus activity at 3 Hz centrally. The poststimulus increase in RMS amplitude in negativity phases was larger at 4 Hz (p = .002), particularly frontally (p b .001); and there were some frontal increases at 3 Hz, and 5 Hz. The RMS increase was smaller at 1 Hz frontally (p = .034); and at 7 Hz (p = .001), particularly at Cz (p = .010). The frontal decrease at 1 Hz was greater in Go (p = .008). In negative driving phases, poststimulus RMS amplitudes increased at 5 Hz (p = .010) and 6 Hz (p = .031), each particularly centrally (5 Hz: p = .022; 6 Hz: p = .002); and decreased at 2 Hz (p = .008), particularly frontally (p = .007); at 3 Hz frontally (p = .014); and at 8 Hz (p = .006), more so at Cz (p = .006). At 1 Hz, a frontal increase was larger in NoGo (p = .018). In waxing compared with waning phases, poststimulus RMS increases were larger at both 2 Hz and 4 Hz (p b .001), each particularly centrally (p b .001); there was a central increase at 6 Hz (p = .021); some increase at 8 Hz which reached significance at Cz (p = .032); and there was a significant increase at 10 Hz (p = .026). 3.4.3. CNV amplitude Negativity phases were associated with larger CNV amplitudes at 1 Hz (p b .001), particularly centroparietally (p b .001 and p = .001 respectively); at 2 Hz (p b .001) and 3 Hz (p = .004), each more so centrally (p b .001); at 4 Hz centrally (p = .015); and at 5 Hz (p = .009). Negativity was also associated with somewhat smaller CNVs at 6 Hz, and significantly smaller CNVs at 7 Hz (p = .023). The slight reduction in CNV amplitudes in negativity phases at 6 Hz was found for Go, but

not for NoGo responses. Negative driving phases were associated with increased CNVs at 1 Hz (p b .001); and with reduced CNVs at 2, 3, 4, 5, and 6 Hz (each p b .001). Each of these negative driving effects were greatest at Cz (1 Hz: p = .001; 2–3 Hz: p b .001; 4–5 Hz: p = .004; 6 Hz: p b .001). CNV amplitudes were not affected by waxing vs. waning phases. 3.4.4. N1 3.4.4.1. Go responses. Go N1 amplitudes in negativity compared with positivity phases were significantly larger at 9 Hz (p = .009), and at 10 Hz (p = .002), somewhat more so centrally; and were smaller at 1 Hz (p = .018), particularly centrally (p = .007); at 2 Hz (p = .004); and at 3, 4, and 5 Hz (each p b .001), each more so centrally (3–4 Hz: p = .001; 5 Hz: p b .001). Amplitudes for Go N1 in negative driving compared with positive driving phases were larger at 1, 2, 3, and 4 Hz (each p b .001), and these increases were greater centrally (each p b .001). Go N1 amplitudes were smaller in negative driving at 7 Hz (p = .013), more so centrally (p = .023); and were somewhat smaller overall and centroparietally at 8 Hz. Waxing vs. waning phases did not produce any Go N1 amplitude effects. Go N1 latency in negativity compared with positivity phases was increased at 6 Hz (p = .005), somewhat more so centrally; and at 7 Hz (p = .004) and 8 Hz (p = .002); but was reduced somewhat at 3 Hz; and significantly reduced at 4 Hz (p = .039), 11 Hz (p = .001), and 12 Hz (p b .001). In negative driving compared with positive driving phases, Go N1 latencies were significantly increased at 8, 9, and

258

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

Table 3 Significant phase effects obtained in the dependent variables as a function of waxing vs. waning.

Dependent variable

Effect

Number

Phase Phase × Go < NoGo Phase Phase × C > F/P Phase Phase × C > F/P

Prestimulus RMS amplitude Poststim. increase in RMS amplitude

1

2

3

4

5

6

Frequency (Hz) 7 8

9

10

11

12

13

↓*** ↓*** ↓*** ↑*** ↑***

↓.058 ↑*** ↑***

↑*

↑.093 ↑*

↑*

↑ larger for waxing; ↓ smaller for waxing; *significant at p b .05; **significant at p b .01; ***significant at p b .005; probability is indicated for the effects approaching significance. Shading indicates the effects found in adults: dark grey ↑ waxing; light grey ↓ waxing.

10 Hz (p b .001), and also at 11 Hz (p = .036); and they were decreased at 4 Hz (p = .001), 5 Hz (p b .001), and 13 Hz (p = .017). There were no Go N1 latency differences in waxing compared with waning phases. 3.4.4.2. NoGo responses. NoGo N1 amplitudes in negativity compared with positivity phases were somewhat larger at 8 Hz; were significantly larger at 9 Hz (p = .002) and 10 Hz (p b .001); and were somewhat increased parietally at 11 Hz. There were NoGo N1 amplitude decreases in negativity at 2, 3, 4, and 5 Hz (each p b .001), each more so centrally (2 Hz: p = .004; 3 Hz: p = .015; 4 Hz: p b .001; 5 Hz: p = .001); and an overall reduction at 6 Hz (p b .001). Amplitudes for NoGo N1 in negative driving compared with positive driving phases were larger at 1, 2, 3, and 4 Hz (each p b .001), and each were greater centrally (each p b .001); at 5 Hz (p = .005), somewhat more so centrally; at 11 Hz (p = .002); and also centrally at 13 Hz (p = .002). NoGo N1 amplitudes were decreased in negative driving phases at 7 Hz (p = .002); somewhat so at 8 Hz; and were significantly decreased centrally at both 8 Hz (p = .025) and 9 Hz (p = .009). NoGo N1 amplitudes did not differ between waxing vs. waning phases. NoGo N1 latency in negativity compared with positivity phases was increased at 6 Hz (p = .013), more so centroparietally (p = .046 and p = .017 respectively); and at 7 Hz (p = .004), 8 Hz (p b .001), and 9 Hz (p = .027); but was significantly decreased at 2 Hz (p = .008); at 3 Hz (p = .026), more so centrally (p = .006); at 10 Hz (p = .007), more so parietally (p = .017); and at 11 and 12 Hz (each p b .001), and 13 Hz (p = .001). In negative driving compared with positive driving phases, N1 latencies were increased somewhat at 8 Hz, and were significantly increased at 9 and 10 Hz (each p b .001), and 11 Hz (p = .012); but were significantly decreased at 4 and 5 Hz (each p b .001); at 6 Hz (p = .001), more so centrally (p = .004); and at 13 Hz (p b .001). There were no latency differences in waxing compared with waning phases. 3.4.5. P3 3.4.5.1. Go responses. Go P3 amplitudes in negativity compared with positivity phases were significantly increased at 1 Hz (p b .001), more so centroparietally (p b .001 and p = .001 respectively); and also at 2 Hz (p b .001), more so centrally (p = .003). Go P3 amplitudes in negative driving were decreased compared with positive driving phases at 1 Hz (p b .001), 3 Hz (p = .001), and 4 Hz (p b .001), each particularly centrally (significant at 1 Hz [p = .001] and 4 Hz [p = .029]; near-significant at 3 Hz). Waxing phases were not associated with effects in the Go P3 amplitude. Go P3 latencies in negativity compared with positivity phases were significantly increased at 4 Hz (p = .017); but decreased at 2 Hz (p b .001) and 5 Hz (p = .003). In negative driving compared with positive driving phases, Go P3 latencies were increased at 4 Hz (p = .008), and decreased at 3 Hz (p b .001) and 6 Hz (p = .006). There were no waxing effects.

3.4.5.2. NoGo responses. NoGo P3 amplitudes in negativity compared with positivity phases were significantly increased at 1 Hz (p b .001), more so centroparietally (p b .001 and p = .004 respectively); and at 2 Hz (p b .001) and 4 Hz (p = .014), each particularly centrally (2 Hz: p b .001; 4 Hz: p = .021). P3 amplitudes in negative driving were increased compared with positive driving phases at 2 Hz centrally (p = .029); but were decreased at 1 Hz (p b .001), 3 Hz (p = .027), and 4 Hz (p b .001), each more so centrally (1 Hz: p b .001; 3 Hz: p = .014; 4 Hz: p b .001); and also at 5 Hz (p = .004); and somewhat so at 7 Hz. NoGo P3 amplitudes did not differ in waxing phases. NoGo P3 latencies in negativity compared with positivity phases were somewhat increased at 3 Hz, and significantly increased at 4 Hz (p b .001); and were significantly decreased at 2 Hz (p = .003) and 5 Hz (p b .001). In negative driving compared with positive driving phases, NoGo P3 latencies were increased at 4 Hz (p b .001), but decreased at 3 Hz (p b .001) and 6 Hz (p = .006). There were no waxing effects. 3.4.6. Illustrative phase effects on grand average Go ERPs The broad-band child Go ERPs for each of the phase ranges, derived using the phase divisions obtained from the narrow-band 1 Hz activity, are presented in the top panel of Fig. 5, for the across-participant grand average. These ERPs provide an approximation of the 1 Hz phase effects reported above. For instance, the prestimulus increase in CNV amplitude in negativity phases (A + B) is clearly evident; the N1 amplitude reduction in negativity (A + B) is apparent, particularly in phase B; and the increased N1 amplitude in negative driving (A + D), and P3 amplitude in negativity (A + B), are each prominent. It is important to note that although these grand mean broad-band ERPs reflect the reported phase effects in 1 Hz, they are not informed by the differences in the occurrences of preferred phase at stimulus onset, and accordingly, the results do not represent the full extent of the narrow-band phase effects assessed here. The broad-band grand mean Go ERPs for the 1 Hz phases at stimulus onset from our adult study (Barry et al., 2010) are presented in the lower panel of Fig. 5, allowing a visual comparison of the phase effects in this frequency. Interestingly, the early prestimulus patterning of the phase effects appears to be opposite in the child and adult samples. Despite this, the poststimulus patterns of the child and adult phase ERPs appear somewhat similar within the N1 latency range, before they differ again in the P3 window. 4. Discussion The present results are extensive and complex, with sets of results from each of our thirteen 1 Hz bands. The obtained narrow-band effects cross the traditional delta/theta/alpha bands, confirming the need to retain our narrow-band approach. Overall, the present findings reinforce the importance of EEG phase at stimulus onset, and future work needs to consider how such effects might lead to excitatory/inhibitory changes in the cortical regions underpinning

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

Fig. 5. Grand mean Go ERPs at Cz separated by average 1 Hz phase at stimulus onset. Child responses are shown in the upper panel; corresponding adult data from our previous study are in the bottom panel. Substantial impacts of phase on N1 and P3 amplitudes and latencies are apparent. Note that these do not represent the total impact of the narrow-band phase effects, as the effects of preferred phase distributions are not included.

stimulus processing and apparent in specific ERP components. We limit the discussion here to the relative occurrence of preferred brain states, and significant phase effects in behaviour and ERPs. Whether the preferred brain states serve to aid efficient cortical processing is also addressed. Where possible we point to similarities and differences between the present child data and our previous adult findings. Across stimuli, prestimulus EEG amplitudes were greater centrally in the theta band, and parietally in the alpha band, compatible with the expected child EEG topographies (e.g., Barry and Clarke, 2009), and broadly similar in topography to the adult profile from Barry et al. (2010). Compared with our adult study, children showed global elevations in slow wave activity, parietally-reduced alpha activity, and had a lower peak alpha frequency (9 Hz compared with 10 Hz), compatible with Barry et al. (2004a). These amplitude and frequency differences can be expected to impact on the preferred phase occurrences reported previously in adult studies. There were only minimal changes in RMS amplitudes at stimulus onset – i.e. no substantial increases in amplitude reflecting evoked activity – a result strongly supporting the dominance of the phase-reset model of ERP genesis in this child group. At 6 Hz, amplitudes at Fz and Pz showed a relative decrease in NoGo c.f. a relative increase in Go, an interaction compatible with adult theta data reported in Barry (2009). This interaction is worth exploring in future work. 4.1. Preferred brain states The existence of preferred brain states at stimulus onset is apparent from the results shown in the first line of each of Tables 1 to 3. Negativity was more common at 1, 8 and 9 Hz, and less common at 6 Hz, than would be expected if phase at stimulus onset occurred

259

randomly. Negative driving was more common at 5 and 10 Hz, and less common at 7 and 8 Hz. Waxing was not differentially present. Noting that the Bonferroni-corrected probability of a false alarm in regard to this variable is .05, the chance of 8 significant cases of preferential phase randomly occurring is p = .05 8, or ~ 1 in 26 billion. This finding strongly confirms the existence in this paradigm of the preferred brain states of negativity and negative driving at stimulus onset in children. Our previous adult study using this paradigm, Barry et al. (2010), found that negativity occurred preferentially at 1, 2, 10 and 11 Hz, and less often at 4 and 5 Hz. Negative driving occurred preferentially at 2, 3, and 13 Hz, and was reduced at 1, 6, 7, and 9 Hz, while waxing was more common at 2 Hz and less common at 1 Hz. Clearly, the age of the subjects impacts the occurrence of preferred phases. We predicted that these preferred phases would not differ between Go and NoGo stimuli. This prediction was based on expectations from the random presentation of Go vs. NoGo stimuli, and had been confirmed in our previous adult study. Here we found that at 1 Hz, negative driving occurred less frequently than positive driving for Go stimuli, and this was reversed for NoGo; while at 5 Hz, waxing occurred more frequently than waning for Go stimuli, and this was reversed for NoGo. A possible explanation is suggested by the large and late P3s to Go stimuli (Fig. 2). Perhaps recovery from such large Go deflections, with amplitudes moving from positive values towards zero, led to these differential Go/NoGo effects in subsequent prestimulus epochs. This could be tested with longer fixed ISIs, which would allow such responses to fully recover before subsequent stimuli occurred. Most importantly, the existence of preferred brain states has been confirmed here in a different age group, with a different spectral profile in the EEG (Fig. 3), and a different ERP morphology (Fig. 2). This confirms the widespread existence of this brain dynamics phenomenon, and encourages further research into its mechanisms. Whether or not these preferred brain states are functionally efficient in terms of behavioural and ERP responding will be returned to later. 4.2. Phase effects in performance, EEG and ERPs 4.2.1. RT Our previous adult study found no phase effects on RT, but there was weak evidence suggesting longer RTs in negativity phases. In contrast, children here had shorter RTs in negative driving phases at 2 Hz. 4.2.2. RMS amplitudes Prestimulus RMS amplitudes in negativity phases were increased at 1 Hz (particularly parietally), at 4 Hz parietally, and at 8 Hz; and were reduced at 3 Hz, particularly frontally. In negative driving, prestimulus RMS amplitudes were increased at 1–2 Hz frontally; but were reduced at 3 Hz centrally, at 4–5 Hz (particularly frontally), and at 6 Hz. The frontal enhancement was greater for Go at 1 Hz, and greater for NoGo at 3 Hz. Waxing phases were associated with reductions in prestimulus activity at 2 Hz, particularly centrally. The poststimulus increase in RMS amplitude in negativity phases was larger at 4 Hz, particularly frontally; and smaller frontally at 1 Hz; and also at 7 Hz, particularly centrally. The frontal decrease at 1 Hz was greater for Go stimuli. In negative driving phases, poststimulus RMS amplitude increased at 5 and 6 Hz (particularly at Cz); there were decreases at 2 Hz (particularly at Fz), at 3 Hz frontally, and at 8 Hz (particularly at Cz). A 1 Hz parietal decrease was larger for NoGo. Poststimulus increases in waxing compared with waning phases were larger at 2 and 4 Hz (particularly centrally), at 6 and 8 Hz centrally, and at 10 Hz. As predicted, these effects differ somewhat in their frequency distribution from the adult findings of Barry et al. (2010). For example, the prestimulus RMS enhancement in negativity phases found at 8 Hz here occurred centrally at 7 and 9 Hz in adults; and the overall

260

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

decrease at 3 Hz here was found at 4 Hz in adults. Similar adult/child shifts in frequency effects also occurred across negative driving and waxing phases, and in the RMS changes at stimulus onset (refer to the shaded cells in Tables 1–3). 4.2.3. CNV Negativity was associated with larger CNVs at 1 Hz (particularly centroparietally), 2–3 Hz (particularly centrally), 4 Hz centrally, and at 5 Hz; and with smaller CNVs at 7 Hz. Negative driving was associated with larger CNVs at 1 Hz, (particularly at Cz) and with reduced CNVs at 2–6 Hz (particularly at Cz). None of these effects differed between Go and NoGo stimuli. These phase effects in the CNV are very similar to the adult effects reported in Barry et al. (2010). 4.2.4. N1 Cortical negativity was associated with larger Go N1 amplitudes at 9–10 Hz, and with smaller amplitudes at 1–5 Hz. The negativity reduction at 1 Hz and 3–5 Hz was larger centrally. For NoGo, N1amplitudes were enhanced at 9–10 Hz, but reduced at 2–6 Hz. The negativity reduction at 2–5 Hz was greater centrally. Go N1 latency was reduced at 4, and 11–12 Hz, but increased at 6–8 Hz; NoGo N1 latency was decreased at 2 Hz, 3 Hz (particularly centrally), 10 Hz (particularly parietally), and 11–13 Hz, but increased at 6 Hz (particularly centroparietally), and 7–9 Hz . In negative driving, amplitudes for Go N1 were enhanced at 1–4 Hz (particularly centrally), and reduced at 7 Hz (particularly centrally). Amplitudes for NoGo N1 were enhanced at 1–5 Hz (particularly centrally at 1–4 Hz), at 11 Hz, and centrally at 13 Hz; and were reduced at 7 Hz, and centrally at 8 and 9 Hz. Go N1 latencies were decreased at 4–5 Hz and 13 Hz, but increased at 8–11 Hz; NoGo N1 latencies were decreased at 4–5 Hz, 6 Hz (particularly centrally), and at 13 Hz; but increased at 9–11 Hz. Go and NoGo N1 amplitudes and latencies were not affected by waxing vs. waning phases. Overall, phase effects in N1 are remarkably similar to those reported for adults in Barry et al. (2010). Interestingly, few of the effects noted above differed between Go and NoGo. 4.2.5. P3 In negativity compared with positivity phases, Go P3 amplitudes were increased at 1–2 Hz; the increase at 1 Hz was larger centroparietally; that at 2 Hz was larger centrally. NoGo P3 amplitudes in negativity phases were increased at 1 Hz (particularly centroparietally), and at 2 and 4 Hz (particularly centrally). Go P3 latencies in negativity phases were decreased at 2 and 5 Hz, but increased at 4 Hz; NoGo P3 latencies were also decreased at 2 and 5 Hz, and increased at 4 Hz. Go P3 amplitudes in negative driving were decreased at 1, 3 and 4 Hz, particularly centrally at 1 and 4 Hz; NoGo P3 amplitudes were increased centrally at 2 Hz, but decreased at 1 and 3–4 Hz (particularly centrally), and at 5 Hz. In negative driving phases, Go P3 latencies were increased at 4 Hz, and decreased at 3 and 6 Hz; similarly, NoGo P3 latencies were increased at 4 Hz, and decreased at 3 and 6 Hz. Waxing phases were not associated with effects in P3 amplitude or latency. Again, considered across the three phase dimensions, these phase effects are remarkably similar to those reported for adults in Barry et al. (2010). 4.2.6. Significance of phase effects Differential stimulus presentation as a function of phase has thus had a large range of effects upon performance, EEG and ERP measures. While we have always interpreted these effects as causal – with the phase difference producing the observed effect – this has been based only on the correlation between the two, and their temporal order. Recently, an interesting study by Neuling et al. (2012) used oscillating transcranial direct current stimulation to entrain 10 Hz EEG activity, allowing the direct manipulation of 10 Hz phase at stimulus onset. Their findings confirmed the causal relationship

between phase and perception, greatly strengthening the importance of the present phase effects. The mechanisms underlying such phase effects are unclear, although the “phase coding” notions discussed recently by Jensen et al. (2012) are provocative. These build on the concept that alpha oscillations provide gating of cortical inhibition (Jensen and Mazaheri, 2010), and that release from inhibition within the alpha cycle results in sequential activation of neuronal processing involving gamma. Phase coding of this type – in which the phase of a slow oscillation is coupled with the amplitude of a fast oscillation – might generalise across the frequency-specific effects noted here. 4.3. Functionality of preferred brain states Do the preferred brain states noted above function to improve the efficiency of cortical functioning? This can be examined in the phase effects on RT, and on poststimulus ERP amplitude and latency, obtained at those particular frequencies. Interpretation is complicated by the fact that, if a phase occurs significantly less often than expected by chance (indicated by a downward arrow in the first line of each Table), the direction of the phase effect on a measure must be reversed when considering its functionality. Thus, in the next paragraph, negativity effects at 6 Hz (where negativity phase occurrence was preferentially absent) are reversed from those listed in Table 1. For example, NoGo N1 amplitude is decreased in negativity phases at 6 Hz (Table 1), and hence a preferential absence of negativity phases at 6 Hz supports larger NoGo N1 amplitude, as stated below. First, cortical negativity was preferentially present at 1, 8, and 9 Hz, and preferentially absent at 6 Hz. These preferred states were associated with larger CNVs at 1 Hz. In relation to Go N1 amplitude, preferential negativity states were associated with an increase at 9 Hz, and a decrease at 1 Hz (particularly centrally); and for NoGo amplitude, were associated with increases at 6 and 9 Hz. They were also associated with Go and NoGo N1 latency decreases at 6 Hz and increases at 8 Hz; and also with NoGo N1 latency increases at 9 Hz. These states were associated with increased Go and NoGo P3 amplitude at 1 Hz, particularly centroparietally. Preferred negativity states were not associated with Go and NoGo P3 latency effects. Second, negative driving was preferentially present at 5 and 10 Hz, and preferentially absent at 7 and 8 Hz. These preferred states were associated with a CNV reduction at 5 Hz, particularly centrally. Preferred negative driving states were associated with an increased Go N1 amplitude at 7 Hz; and NoGo N1 amplitude increases at 5 and 7 Hz, and a central increase at 8 Hz. These states were also associated with Go and NoGo N1 latency decreases at 5 Hz, and increases at 10 Hz; and with Go N1 latency decreases at 8 Hz. Preferred negative driving states were associated with a NoGo P3 amplitude decrease at 5 Hz; but they had no impact on P3 latency. There was no link between the observed negative driving effects on RT and the preferred negative driving states, indicating that the preferred phase states did not contribute to behavioural performance in children. It is apparent above that some of the preferred phase associations act to produce contrary effects, requiring consideration of their balance. In the CNV, preferential cortical negativity states at 1 Hz increased amplitudes, while preferred negative driving states at 5 Hz decreased amplitudes. Given the relative RMS amplitudes at 1 and 5 Hz (Fig. 3), it appears that on balance, preferred phase states serve to enhance CNV amplitude. Preferred negativity states appear to balance out in their effects on Go N1 amplitude, but were associated with increases in N1 NoGo amplitude, while Negative driving effects produced enhancement of both Go and (more extensively) NoGo N1 amplitudes. Preferred negativity phases were balanced in their effects on Go N1 latencies, but produced increased NoGo N1 latencies on balance; preferred negative driving states produced (on balance) decreased Go N1 latency, but no NoGo latency effects. In the P3, preferred negativity states were associated largely with Go and NoGo amplitude increases without latency reductions; negative driving was

R.J. Barry, F.M. De Blasio / International Journal of Psychophysiology 86 (2012) 251–261

associated with NoGo P3 amplitude reduction, again with no latency changes. These findings indicate that the preferential occurrence of particular brain states, as indicated by the non-random patterning of narrow-band EEG phase at stimulus onset, is functionally associated with efficient stimulus processing in this paradigm. In general, CNV amplitude is increased, N1 and P3 amplitudes are increased, and some N1 latencies are decreased. The preferred states also appear to be involved in the differential processing of Go and NoGo stimuli, leading to some of the associated differences in ERP component amplitudes. The range of these effects is less here than reported previously in adults (Barry et al., 2010), supporting our hypothesis that these follow a developmental trajectory as is common in many aspects of neurological functioning. We cannot speculate on whether this phenomenon is innate or emerges at some specific age. Detailed investigation of such developmental effects would be a mammoth task considering that the data processing and analysis reported here is approximately thirteen times that involved in a normal ERP analysis (due to the thirteen 1 Hz narrow bands examined). The basis for extending our phase studies to children – that their EEG spectra and ERP morphology both differ from those of young adults – also applies in normal ageing. Thus we would predict that preferential phase occurrence will be apparent in normal aged participants, but that, as in our children here, the occurrence will be somewhat less pervasive and efficient. Such studies could open a new way to investigate subtle aspects of the brain dynamics involved in mild cognitive impairment and Alzheimer's Disorder. 4.4. Summary and future research We have confirmed the existence, in children, of preferred phasedefined brain states at stimulus onset in an auditory equiprobable Go/ NoGo task. We consider that these originate from the dynamic adjustment of cortical activity underlying various frequencies in the ongoing EEG. The preferred states at particular frequencies have been shown to be differentially associated with elevated prestimulus RMS amplitudes, poststimulus changes in RMS amplitudes, and prestimulus CNV amplitudes; these are expected to be involved in the mechanisms of some of the phase effects observed in the poststimulus ERP amplitudes and latencies. The present study adds to the rich data from this research programme that might illuminate the exploration of these mechanisms in future work. We have not addressed phase effects in the large P2, N2, and Nc apparent in the child ERPs. Work is in progress in our laboratory investigating (non-phase related) developmental effects in these components in the equiprobable auditory Go/NoGo paradigm. When we have a greater understanding of the meaning of these components in this paradigm, it will be interesting to investigate the impact of phase effects upon them, but that is beyond the scope of the present paper. Whether these narrow-band phases have specific and/or unique effects, or if the narrow bands serve to provide examples of broader effects, is not known. We consider it likely that the occurrence of cortical negativity, negative driving, and waxing at stimulus onset, at different frequencies, is of primary importance in how they produce negativity/positivity over the cortex at particular times. That could (respectively) activate/deactivate the cortex, affecting regions associated with task-related stimulus processing. Independently of this, the present phase dimensions are easy to conceptualise in terms of EEG changes. Using this approach, we have confirmed that, in tasks involving consistently timed stimulus presentations, the phase of ongoing EEG activity is reflexively adjusted at a range of frequencies to optimise performance, extending the phase-reset model of ERP genesis. The present results contribute to the generality of these findings across paradigms, EEG-processing approaches, and age groups, and add to our understanding of the dynamic brain processes involved in perceptual and cognitive processing.

261

Acknowledgement This research was funded by a grant from the Australian Research Council Discovery funding scheme (project number DP0772251). References Barry, R.J., 2009. Evoked activity and EEG phase resetting in the genesis of auditory Go/ NoGo ERPs. Biological Psychology 80, 292–299. Barry, R.J., Clarke, A.R., 2009. Spontaneous EEG oscillations in children, adolescents, and adults: typical development, and pathological aspects in relation to AD/HD. Journal of Psychophysiology 23, 157–173. Barry, R.J., Rushby, J.A., 2006. An orienting reflex perspective on anteriorisation of the P3 of the event-related potential. Experimental Brain Research 173, 539–545. Barry, R.J., Kirkakul, S., Hodder, D., 2000. EEG alpha activity and the ERP to target stimuli in an auditory oddball paradigm. International Journal of Psychophysiology 39, 39–50. Barry, R.J., de Pascalis, V., Hodder, D., Clarke, A.R., Johnstone, S.J., 2003. Preferred EEG brain states at stimulus onset in a fixed interstimulus interval auditory oddball task, and their effects on ERP components. International Journal of Psychophysiology 47, 187–198. Barry, R.J., Clarke, A.R., McCarthy, R., Selikowitz, M., Rushby, J.A., Ploskova, E., 2004a. EEG differences in children as a function of resting-state arousal level. Clinical Neurophysiology 115, 402–408. Barry, R.J., Rushby, J.A., Johnstone, S.J., Clarke, A.R., Croft, R.J., Lawrence, C.A., 2004b. Event-related potentials in the auditory oddball as a function of EEG alpha phase at stimulus onset. Clinical Neurophysiology 115, 2593–2601. Barry, R.J., Rushby, J.A., Smith, J.L., Clarke, A.R., Croft, R.J., 2006. Dynamics of narrowband EEG phase effects in the passive auditory oddball task. European Journal of Neuroscience 24, 291–304. Barry, R.J., Rushby, J.A., Smith, J.L., Clarke, A.R., Croft, R.J., Wallace, M.J., 2007. Brain dynamics in the active vs. passive auditory oddball task: exploration of narrow-band EEG phase effects. Clinical Neurophysiology 118, 2234–2247. Barry, R.J., Rushby, J.A., Smith, J.L., Clarke, A.R., Croft, R.J., 2009. Brain dynamics in the auditory oddball task as a function of stimulus intensity and task requirements. International Journal of Psychophysiology 73, 313–325. Barry, R.J., De Blasio, F., Rushby, J.A., Clarke, A.R., 2010. Brain dynamics in the auditory Go/ NoGo task as a function of EEG frequency. International Journal of Psychophysiology 78, 115–128. Başar, E., 1980. EEG Brain Dynamics: Relation between EEG and Brain Evoked Potentials. Elsevier/North Holland Biomedical Press, Amsterdam . 411 pp. Başar, E., Stampfer, H.G., 1985. Important associations among EEG-dynamics, eventrelated potentials, short-term memory and learning. The International Journal of Neuroscience 26, 161–180. Başar, E., Başar-Eroglu, C., Rosen, B., Schütt, A., 1984. A new approach to endogenous event-related potentials in man: relation between EEG and P300-wave. The International Journal of Neuroscience 24, 1–21. Callaway, E., Yeager, C.L., 1960. Relationship between reaction time and electroencephalographic alpha phase. Science 132, 1765–1766. Courchesne, E., 1977. Event-related brain potentials: comparison between children and adults. Science 197, 589–592. Delorme, A., Makeig, S., 2004. EEGLAB: an open source toolbox for analysis of singletrial EEG dynamics including independent component analysis. Journal of Neuroscience Methods 134, 9–21. Howell, D.C., 1997. Statistical Methods for Psychology, 4th edn. Duxbury Press, California. Jansen, B.H., Brandt, M.E., 1991. The effect of the phase of prestimulus alpha activity on the averaged visual evoked response. Electroencephalography and Clinical Neurophysiology 80, 241–250. Jensen, O., Mazaheri, A., 2010. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Frontiers in Human Neuroscience 4, 186. Jensen, O., Bonnefond, M., VanRullen, R., 2012. An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences 16, 200–206. Johnstone, S.J., Pleffer, C.B., Barry, R.J., Clarke, A.R., Smith, J.L., 2005. Development of inhibitory processing during the Go/NoGo task: a behavioural and event-related potential study of children and adults. Journal of Psychophysiology 19, 11–23. Makeig, S., Delorme, A., Westerfield, M., Jung, T.P., Townsend, J., Courchesne, E., Sejnowski, T.J., 2004. Electroencephalographic brain dynamics following manually responded visual targets. PLoS Biology 2, 747–762. Neuling, T., Rach, S., Wagner, S., Wolters, C.H., Herrmann, C.S., 2012. Good vibrations: oscillatory phase shapes perception. NeuroImage 63, 771–778. O'Brien, R.G., Kaiser, M.K., 1985. MANOVA method for analyzing repeated measures designs: an extensive primer. Psychological Bulletin 97, 316–333. Pleydell-Pearce, C.W., 1994. DC potential correlates of attention and cognitive load. Cognitive Neuropsychology 11, 149–166. Rémond, A., Lesèvre, N., 1967. Variations in average visual evoked potentials as a function of the alpha rhythm phase (“autostimulation”). Electroencephalography and Clinical Neurophysiology. Supplement 26, 42–52. Rockstroh, B., Elbert, T., Canavan, A., Lutzenberger, W., Birbaumer, N., 1989. Slow Cortical Potentials and Behaviour, 2nd edn. Urban and Schwarzenberg, Munich . 267 pp. Schroeder, C.E., Lakatos, P., 2009. Low-frequency neuronal oscillations as instruments of sensory selection. Trends in Neurosciences 32, 9–18. Tabachnick, B.G., Fidell, L.S., 1989. Using Multivariate Statistics, 2nd edn. Harper Collins, N.Y . 746 pp. Trimble, J.L., Potts, A.M., 1975. Ongoing occipital rhythms and the VER. I. Stimulation at peaks of the alpha-rhythm. Investigative Ophthalmology and Visual Science 14, 537–546.