We found that both groups performed better at the task at time 2 versus 1. These generic practice effects were reflected in faster mean reaction times (main effect of Time, repeated measures analysis of variance (ANOVA), F(1,29)=5.9, p<0.05, ) and increased target detection rates, as indexed by d′ (main effect of Time, F(1,29)= 7.3, p<0.01, ). The overall increase in d′ was produced by an increase in hit rates at time 2 (main effect of Time, F(1,29)= 8.6, p<0.01). For experts, the mean hit rates were 80% (SD 20%) at time 1 and 91% (SD 10%) at time 2. For novices, the mean hit rates were 81% (SD 18%) at time 1 and 84% (SD 17%) at time 2. There was no significant change in false alarm rates over time in either group (paired t-test, t(1,13)=−1.7, p=0.1, for practitioner group, t(1,16)=0.1, p=0.9, for novice group). In addition, next to these generic practice effects, and in line with our prediction, we found that intensive mental training reduced behavioural response time variability. Thus, the practitioners showed a significantly greater reduction in RT variability (SDs) than the novices at time 2 versus time 1 (Group by Time interaction, repeated measures ANOVA, F(1,29)=10.2, p<0.005, ). This effect was driven by the practitioner group only (paired t-test on the difference in SD at time 2 versus time 1, t(1,13)=3.1, p<0.01; novices: t(1,16)=−1.3, p=0.2). Mental training did not affect mean RT (Group by Time interaction effect, F(1,29)=1.8, p=0.18) or target tone detection rates (Group by Time interaction effect, F(1,29)=1.97, p=0.17). Of importance, there were no differences between groups in performance at time 1 (RT, SD, or d′ measures: no main effect of Group, all p’s>0.28).
Intensive mental training reduces intra-individual variability of behavioral performance
Phase-Locking Factor and Event-Related Potentials
We next predicted that the observed FA meditation-related reduction in reaction time variability would be associated with reduced variability of target-evoked brain responses, as indexed by the Phase-Locking Factor (PLF;(Palva, Palva and Kaila, 2005
)). PLF is an amplitude-independent measure (i.e. PLF depends on the phase but not on the amplitude of the spectral representation of the signal; see Methods) adapted specifically to measure trial-to-trial stability of stimulus-evoked brain responses. To describe mental training-related effects on neural response variability, we first ran a repeated measures ANOVA for selected electrodes and time windows separately, using the average normalized PLF (nPLF) across frequency bands from 1 to 30Hz as the dependent measure (see Methods). The analysis of stimulus locking of broadband phase allows the evaluation of the precise time course of the phase-locked events, but does not disclose the spectral characteristics of the underlying activities. Therefore, we examined, in addition, stimulus locking within standard narrow-band frequency bands (δ(1–3Hz), θ (4–7Hz), α (8–13Hz) and β (13–30Hz)). To correct for multiple comparisons, we used a nonparametric single threshold test (Nichols and Holmes, 2002
). To reduce the number of tests, statistical examination of effects of FA meditation focused on three spatial regions (anterior, central and posterior electrodes), three temporal intervals (50–150ms, 150–300ms, and 300–500ms) and four frequency bands. This selection was based on visual inspection of the data and the topography and chronomometry of standard evoked brain responses (N100, P200, and P300, respectively) (see Methods).
To test our hypothesis that intensive FA meditation would enhance attentional stability at the neural level, we examined whether FA meditation affected the phase relationship between the recorded signals at a given latency and the presented stimuli across the trials, using the PLF. Mental-training related increases in phase locking of broadband (1–30Hz) neural activity to attended deviant tones did not survive correction for multiple comparisons. Yet, narrow-band frequency analyses showed that, in line with our prediction, mental training was associated with decreased cross-trial variability in the phase of oscillatory activity in the theta band between 300–500ms after attended deviant tones over frontal scalp regions, as indicated by a significant 3-way interaction (Group by Time by Condition (attended, unattended deviant); F(1,29)=5.7, corrected p<0.05; see Methods). This effect peaked around 400ms over frontal scalp regions (), and was only found for the practitioner group (; paired t-test for practitioners on the difference t2 versus t1 attended versus unattended, between 300–500ms over anterior electrodes t(1,13)=3.1, p<0.01; for the novices t(1,16)=−1.7, p=0.1). Importantly, and further in line with our hypothesis that mental training would reduce sustained attention task performance variability by enhancing the stability of cortical signal processing, these training-related changes in theta PLF predicted the observed training-related reduction in trial-to-trial reaction time variability (). Specifically, between 300–500ms (see ), over anterior scalp regions, a negative cross-subject correlation was observed between the increase across sessions in the consistency with which the brain responded to attended versus unattended deviant tones and the decrease in RT variability to attended deviant tones across sessions (, r=−0.40, p<0.05 for practitioners and novices). Such relationship was not seen with mean reaction time (r=−0.14, p=0.46) or d′ (r=0.13, p=0.45). To summarize, mental training reduced variability in attentional responses to task-relevant stimuli, as indicated by increased PLF to target tones and reduced reaction time variability.
In the dichotic listening paradigm, discrimination between target and non-target stimuli usually produces an event-related potential in response to target stimuli (called the P3a), that is sensitive to demands of attention ((Polich, 2007
)). The P3a is thought to reflect stimulus-driven disruption of frontal attention engagement (Polich, 2007
). Notably, this component has a similar latency and scalp topography as the observed mental training-related increase in phase consistency to target tones, and we therefore explored effects of FA meditation on the amplitude of the P3a. In our data, replicating prior studies (for review (Polich, 2007
)).), we also observed a greater P3a to attended vs. unattended deviant tones over frontal scalp regions between 300–500 ms (main effect of Condition at electrode Fz, t(1,29)=4.3, p<0.0002, for all participants across sessions, ). Yet, mental training did not affect P3a amplitude (Group by Time by Condition interaction, F(1,29)=0.41, p=0.53 at Fz, and F(1,29)=2.1, p=0.16 at Cz. For practitioners paired t-tests on P3a amplitude comparing time 2 versus time 1 at Cz and Fz, p>0.5). This is likely due to the fact that the ERP is more susceptible to trial-to-trial amplitude variability than PLF for relatively small numbers of trials and/or that this finding is specific to theta-band frequencies. In summary, mental training increased theta-band phase locking to target tones only and this effect was not reflected in an event-related potential measures of selective attention (P3a).
In addition, we explored the possibility that FA meditation - given that it is also assumed to affect the processing of distractions and task-unrelated thought - may affect stimulus processing in general (see Methods and (Lutz et al., 2008b
)). Specifically, we examined whether FA meditation may modulate both distracter and target processing, as indicated by changes in PLF to deviant tones regardless of whether they were presented in the attended or unattended ear channel. Indeed, we found a robust meditation-related increase in broadband phase locking of neural activity at frontal electrodes between 150–300ms to any deviant tone (Group by Time interaction; on average F(1,29)=8.4, p<0.01, corrected for multiple comparisons at p<0.05, see ). The effect was driven by stronger phase locking to deviant tones at time 2 in the practitioner group (paired t-test on the different t2 versus t1 for unattended deviant tones t(1,13)=2.4, p<0.05, and, attended deviant tones t(1,13)=5.8, p<0.0001), an effect that was not observed for the novice group (t(1,16)=−1.1, p=0.27 and t(1,16)=−0.42, p=0.68, respectively). The observed meditation-related increase in broadband phase locking PLF effects to attended deviant tones also predicted corresponding changes in intra-individual variability in reaction time (r=−0.50, p< 0.005, ), d′ (r=0.48, p<0.01) and reaction time (r=−0.35, p=0.06). This early mental training-related PLF effect remained significant over anterior electrodes between 300–500ms, although the effect was weaker (corrected p<0.05, F(1,29)=5.9, p<0.05).
Intensive mental training increases trial-to-trial consistency of brain responses to any deviant tones
Notably, the scalp topography and latency of the early mental training-related, attention-independent PLF effect corresponds to the scalp topography and latency of the P200 (), as confirmed by an additional ERP analysis: the topography of the P200 (averaged between 150–300ms) positively correlated with the topography of the broadband PLF between 150–300ms (r= 0.48, p<0.0001 for practitioners and r= 0.26, p<0.05 for controls). For the practitioners only, the topography of the P200 variations between time 1 and time 2 correlated with the topography of the PLF variations between time 1 and time 2 (r=0.72, p<0.0001). The amplitude of the P200 increased for the practitioners at time 2 (paired t-test on time 2 versus time 1 at Fz, t(1,13)=2.8, p<0.05 and at Cz, t(1,13)=2.7, p<0.05) but not for novices (paired t-test, time 2 versus time 1 for novices, at Fz, t(1,16)=0.7, p=0.49 and at Cz, t(1,13)=0.5, p=0.66). These results suggest that mental training may have also affected processes reflected by the P200. The P200 is typically associated with the beginning of an executive process responsible for stimulus identification and the initiation of decision making, and is also modulated by attention (Lindholm and Koriath, 1985
). In line with previous studies, a smaller P200 (averaged between 150–300ms) was observed to attended vs. unattended deviant tones (paired t-test for all participants attended vs. unattended deviant tones averaged across time 1 and time2, p<0.000001, t(1,30)>6.4 above Fz and Cz). As the PLF frontal effect remained significant during the interval 300–500ms, we also explored possible mental training-related changes in ERPs in this later interval at electrodes Fz and Cz. Indeed, we found an increase in P3 amplitude for the practitioners only at time 2 (repeated ANOVAs, Group by Time interaction on average ERP between 300–500ms, F(1,29)=4.5, p<0.05 at Fz and F(1,29)=5.4, p<0.05 at Cz. Paired t-test for time 2 versus time 1 for all deviants tones for practitioners t(1,13)=2.3, p<0.05 at Fz and t(1,13)=2.1, p=0.06 at Cz, and for novices t(1,16)=−1.0, p=0.33 at Fz and t(1,16)=−0.15, p=0.88 at Cz. ).
Finally, we also examined mental training-related changes in stimulus locking to any deviant tone within standard narrow-band frequency bands for the same electrode sites and time windows for which broadband effects were observed to shed light on the spectral characteristics of this effect. Mental training only affected phase locking to any deviant tone in the delta (1–3Hz) frequency band (frontal electrodes, interval 300–500ms, F(1,29)=8.2, p<0.05 corrected). Notably, recent work suggests that when task-relevant input is regular or “rhythmic”, attention can enforce oscillatory entrainment to the input stream, thereby optimizing performance ((Jones and Boltz, 1989
, Schroeder and Lakatos, 2009
)). As in our task, the stimulus presentation rate fell within the frequency of the delta band (with a mean stimulus onset asynchrony (SOA) of 950ms), an intriguing possibility is thus that the observed mental training-related modulation of general stimulus processing in the delta band reflects a increase in oscillatory entrainment to the task-input rhythmic of the auditory tones. To explore this possibility, we analyzed mental training-related effects of phase locking to any deviant tone separately for a frequency band centred on the task-input rhythmic (estimated to be [0.85–1.3Hz] based on the range of SOAs) and the higher part of the delta band (1.5–3Hz) (for this analysis the EEG signals were band-pass filtered between 0.5–30Hz). Both analyses replicated the above findings for the 1–3Hz band, with mental training enhancing phase locking of oscillatory activity above frontal electrodes in both delta sub-bands (0.85–1.3Hz band: t-test comparing practitioners versus novices at time 2 versus time 1, t(1,29)=3, p<0.01), albeit more strongly so in the higher delta band (1.5Hz–3Hz) than in the task-input rhythmic band (t-test, t(1,29)= 2.4, p<0.05). This effect was driven by the practitioners showing higher PLF amplitude in high delta band than [0.85–1.3Hz] at time 2 compared to time 1 (paired t-test, t(1,13)=5, p<0.005). Nevertheless, the fact that mental training enhanced phase locking of oscillatory activity in a band corresponding to the auditory input frequency suggests that FA meditation may have lead attention to operate more steadily in a “rhythmic” mode of attention.
One could also argue that observed increase in phase locking to unattended deviant tones simply reflects an increase in general arousal level for meditators at time 2 rather than an increase in monitoring of any deviant tone or a reduction in task-unrelated processes. Higher arousal is generally thought to increase the system’s sensitivity to any sensory stimulus, and has typically been associated with a reduction in EEG power in the alpha band (8–12Hz)(Niedermeyer, 1999
). To exclude the possibility that our effects merely reflect differences between groups in changes in arousal over time, we computed the global EEG power in the alpha band. Importantly, we did not find a group by time effect (repeated ANOVA, F(1,28)= 0.02, p=0.88). Rather, for both groups, we observed an increase in global alpha power (main effect of time, F(1,28)=4.6, p<0.05, mean power in a 2 second window for practitioners, 2.9×10^5 μV^2 at time 1 and 4.1×10^5 μV^2 at time 2, and for SC, 2.4×10^5 μV^2 at time 1 and 3.3×10^5 μV^2 at time 2). This finding argues against the possibility that a selective increase in arousal at time 2 in the practitioner group can explain our findings.
To summarize the above findings, mental training enhanced trial-to-trial phase consistency of oscillatory brain responses to attended deviant tones, as well as to deviant tones in general (i.e., independent of selective attention). The mental training-related increase in phase consistency to any deviant tone correlated with a mental training-related increase in the amplitude of the P200 ERP. These meditation-related effects could not simply be explained by a mere change in arousal level at time 2 for the meditators, as global alpha power increased similarly for both groups.
In addition, as we previously found that meditation training affects the distribution of limited brain resources ((Slagter et al., 2007
)), we estimated how FA meditation affects cortical processing during the task. We indexed the extent of cortical engagement required to meet tasks demands by quantifying event-related desynchronization (ERD) to target tones. ERD reflects the blocking of alpha (8–12Hz) and beta (13–30Hz) EEG oscillatory rhythms by stimulus processing, in particular during motor preparation and execution, and is thought to reflect increased cellular excitability in thalamocortical systems during cortical information processing (Pfurtscheller and Lopes da Silva, 1999
). Effort exerted during task performance, task difficulty, advanced age and low IQ are all factors that enhance ERD (for review (Pfurtscheller and Lopes da Silva, 1999
)). By contrast, cognitive task practice has been found to reduce beta ERD (Romero et al., 2008
). In line with the hypothesis that FA practice results in a decreased need for active engagement (Lutz et al., 2008b
), we found that intensive mental training was associated with a reduction in ERD of beta oscillatory activity to attended deviant tones over the three spatial regions of interest as reflected by a Group by Time by Condition interaction between 500–750ms (F(1,29)=4.8, p< 0. 05, F(1,29)=5.2, p<0.05, F(1,29)=4.7, p<0.05, across anterior, middle, and posterior electrodes, respectively, p< 0.05 corrected, ). This interaction was driven by the practitioners showing less ERD at time 2 in the attended condition only (t-test comparing ERD to target minus ERD to unattended deviant tones at time 2 vs time 1, t(1,13)=3.4, p<0.005), while no such effect was observed for the novices (t(1,16)=−1.1, p=0.29) (). The peak of this effect was located over frontal and left centro-posterior electrodes (). The lateralization of this ERD pattern above somato-sensory electrodes contralateral to the hand executing the motor response (paired t-test between the average across electrodes CP1, CP3, CP5, P1, P3, P5 and the average across CP2, CP4, CP6, P2, P4, P6, t(1,30)=−2.84, p<0.01) is in line with the proposal that beta-band ERD in part reflects motor selection processes ((Doyle, Yarrow and Brown, 2005
)). Different from the observed mental training-related increase in phase consistency, these mental training-related changes in ERD did not correlate with the observed mental training-related behavioral changes in attentional stability (i.e., variability of reaction time). This latter finding may indicate that the observed effects of mental training on the stability of attention and task engagement were independent. This may not be surprising given that ERD is thought to index the amount of cortical engagement allocated by the system to perform the task, rather than reflect the actual performance of the system during the task (Pfurtscheller and Lopes da Silva, 1999
). Alpha ERD was not affected by mental training, although this frequency band showed the greatest reduction in ERD to attended versus unattended deviant tones in general (data not shown). To summarize, the observed mental training-induced changes in ERD of beta band activity suggests a reduction in the amount of resources or engagement necessary to perform the task as a result of training.