To justify the use of this five-parameter model, we took a model-selection approach (using the Bayesian Information Criterion, BIC) to examine whether this model is preferred to an alter- native, less elaborate model in which the CNV resolution was immediate.

That is, this four- parameter model did not include a free parameter for a delay between the termination of the CNV buildup and the initiation of its resolution.

For each condition, the model with the lower BIC value was considered the preferred model.

In the Repeated-Interval condition, the five- parameter "resolution after delay" model turned out to be superior over an alternative four- parameter "immediate resolution" model (Fig 3D) with no delay (ΔBIC = 76).

However, in the Rhythmic condition, the four-parameter model was superior (ΔBIC = 7.3).

This indicates that the five-parameter model is indeed necessary, as it is preferred for the Repeated-Interval con- dition but also provides converging evidence to the difference between conditions, as it was not preferred for the Rhythmic condition.

Thus, in rhythmic streams, target omission trig- gered an immediate resolution of the CNV, while in memory-based temporal predictions, the initiation of the CNV resolution was delayed, presumably anticipating the upcoming event at the long SOA.


Previous studies found that the amplitude of alpha-band oscilla- tions (8-13 Hz) is reduced just prior to, or at the time of, an event that is temporally expected based on rhythms [9,34,35].

We tested whether this modulation of alpha-band amplitude is unique to rhythms or whether it is expressed to the same extent when the prediction is based on a memorized interval.

To dissociate the effect of expectation from response to the target we analyzed the alpha-band amplitude in the time window of the short SOA (700-900 ms after the WS) exclusively in trials in which the target appeared at the long SOA.

In this window, we expected to find in the Rhythmic condition lower alpha amplitude when expecting the target at the short compared to long SOA.

If this phenomenon is unique to rhythm-based predic- tions, the Repeated-Interval condition should have smaller, or even no modulation.


In our data, there were narrow-band amplitude modulations in the alpha range (Fig 4A).

The most pronounced amplitude modulation was a sharp decrease of amplitude of the alpha band following the WS, which then recovered, a typical response to visual stimuli (Fig 4B).

In the Rhythmic condition, when expecting a target at a short SOA, the recovery was blunted, resulting in lower amplitude in the short SOA window compared to when expecting a target at the long SOA (t (18) = 1.80, p = 0.044, d = 0.41).

This modulation was not explained by differ- ences in the average stream SOA, as it was not observed in the nonpredictable Random condi- tion, in which there was even a trend for higher alpha amplitude when expecting a target at the short SOA.

However, similar amplitude modulation of alpha-band activity was observed in the Repeated-Interval (t (18) = 1.82, p = 0.043, d = 0.42) condition, and an ANOVA conducted across the predictive conditions revealed no interaction between SOA and condition (F (1,18) = 0.14, p = 0.71) but only a main effect of SOA (F (1,18) = 5.23, p = 0.036).

There was also no main effect of condition (F (1,18) = 0.01, p = 0.92).

Thus, the reduction of alpha-band amplitude at the time of an expected event did not depend on whether the prediction was rhythm or memory based.


Previous studies reported increased PC in the delta band at the time of rhythm stimuli, such that the optimal phase for performance aligns with rhythmic stimuli times [3,6,7,21,22].

This effect was interpreted as reflecting entrainment of intrinsic oscillations to the rhythm.

Under this premise, PC should be stronger in the Rhythmic relative to the Random and Repeated-Interval conditions, since, in the latter two, the stream is less periodic and hence 9 / 30 less able to entrain oscillatory activity.

To test this, we extracted the phase of delta-band activity (0.5-3 Hz) from occipital electrodes at target time in the three experimental conditions and, as additional control, at the time of the WS in the Rhythmic condition.

The Random condition target was used as a control in which there was preparation for a target but no specific temporal prediction.

The WS in the Rhythmic condition was used as a control in which a task-relevant event (the WS) is temporally predictable, but there is no preparation to respond to it.


We first examined whether there is an optimal delta phase for performance, that is, a corre- lation between delta phase at target time and RTs.

Such correlation is essential for entrainment accounts because if performance is not associated with the phase of oscillations, there is no benefit from aligning the oscillation phase with expected times.


Plotting RTs as a function of delta phase across subjects revealed a circular-linear association in all conditions (sinusoidal instead of straight line, Fig 5A, compare with the much weaker correlation between RT and Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 11 / 30 delta phase at the time of the WS in the Rhythmic condition, S1 Fig and S1 Text).

Finding the phase-RT correlation in the Random condition is essential, as it indicates that this correlation is not merely driven by phase correction in the predictive conditions (Fig 5A, right panel).


To test this correlation across all subjects while allowing a different optimal angle for each subject, we used a linear mixed-effects model that predicted single trial RTs from delta phase (repre- sented as its sine and cosine) and target SOA in the Random condition (see S1 Text).

This analysis revealed a significant fixed effect for delta phase (w 2 ð2Þ ¼ 7:82, p = 0.02) but also a sig- nificant effect for the random slopes of delta phase (w 2 ð5Þ ¼ 15:16, p = 0.01), suggesting that delta phase was associated to RT with a different optimal phase for each subject.

Optimal phase did not differ between short and long SOAs (w 2 ð1Þ ¼ 0:06, p = 0.81).


Thus, the phase of delta activity at target time was associated with RT, in accordance with the idea that this activ- ity reflects fluctuations in efficiency of neural processing.

This also indicated that performance is optimal in selected portions of the delta cycle.


Next, we tested whether rhythm-based predictions lead to increased PC at the time of the tar- get relative to memory-based predictions or with no temporal information.

If delta PC reflects entrainment of low-frequency oscillations, the inter-trial phase coherence (ITPC) should be stronger in the Rhythmic condition compared to the other conditions.

For this purpose, we cal- culated the ITPC at target time (Fig 5B), and compared it between conditions using an omnibus permutation-based ANOVA that does not require the parametric assumptions of conventional ANOVA (see S1 Text).

This analysis revealed a main effect of condition (p < 0.01).

Planned contrasts revealed that the ITPC was increased in the Rhythmic condition compared to the Ran- dom condition (p < 0.01) and compared to the WS in the Rhythmic condition (p < 0.01).

How- ever, the ITPC was also increased in the Repeated-Interval condition compared to the Random condition (p < 0.01) and compared to the WS in the Rhythmic condition (p < 0.01).

Crucially, the ITPC did not differ between the Rhythmic and Repeated-Interval conditions (p > 0.5, CI for the ITPC difference: −0.061 to 0.035).

The ANOVA also revealed stronger ITPC for targets appearing at long compared to short SOA (p < 0.01) and a significant interaction between tar- get SOA and condition (p < 0.05).

Permutation-based t tests revealed that for short target SOA, there was a nonsignificant trend for the ITPC to be stronger for the Rhythmic compared to the Repeated-Interval condition (p = 0.1), while for long target SOA, the ITPC was in fact weaker for the Rhythmic compared to the Repeated-Interval condition (p < 0.01).

Thus, enhancement of delta PC was not unique to rhythm-based temporal predictions.


Finally, we examined whether the delta-band PC is around the optimal phase for perfor- mance.

It could be the case that memory-based predictions lead to increase in delta PC, but not towards the optimal angle, which would suggest that this PC reflects a different process than the one that takes place when predictions are based on rhythms.


First, we estimated the optimal phase for performance of each subject by averaging the phases of the fastest 33% of the trials in the Random condition (Fig 5C).

Next, we calculated for each subject in each condition the average phase at target time (Fig 5D).

If the phase at target time was shifted to the optimal angle, the difference between each subject's optimal phase and phase at target time should have an expected value of zero.


Fig 5E presents these differences for all subjects in each condi- tion, demonstrating a distribution around zero.

To quantify this, we used a circular statistical test, termed V test, which tests whether phases are unimodally distributed around an a priori specified angle (in contrast to uniformly distributed).

When using zero as the a priori angle, this test was significant in both short and long SOAs in the Rhythmic (short V = 14.04, long V = 15.54, all p < 0.01) and similarly in the Repeated-Interval (short V = 11.84, long V = 15.03, all p < 0.01) conditions.


Thus, the distribution of the circular distances between the phase angle at target time and the optimal phase for each subject was significantly concentrated 12 / 30 around zero, indicating alignment with the optimal phase in both predictive conditions (Fig 5C).

In summary, the delta PC and alignment with the optimal phase observed in the Rhythmic condition were observed at least to a similar extent in the Repeated-Interval condi- tion, implying that these effects were not unique to rhythms.


The P3 is a parietal-maximum ERP following target detection [41,42].

Its latency is shortened when target timing is expected compared to unexpected [26,34].

We examined whether this modulation differs between rhythm- and memory- based temporal pre- dictions, separately for short and long SOA targets (due to pretarget CNV-related effects, Fig 6A).

We used a jackknifing method (see S1 Text) to extract the latency in which the P3 reached 50% of its full amplitude and submitted them to a two-way ANOVA with factors Condition and Validity within each SOA.

As rhythm-based predictions lead to stronger behavioral valid- ity effect, it could have been expected that they will be reflected in a larger validity effect on the P3 latency.


Overall, the P3 latency was shorter for valid compared to invalid targets both for short SOA targets (F (1,18) = 24.57, p = 0.0001, Rhythmic: t (18) = 2.35, p = 0.03, Repeated-Inter- val: t (18) = 2.85, p = 0.01) and for long SOA targets (F (1,18) = 13.38, p = 0.0017, Rhythmic: t (18) = 2.57, p = 0.019, Repeated-Interval t (18) = 2.97, p = 0.008, Fig 6B).

Crucially, the validity effect did not differ between the Rhythmic and Repeated-Interval conditions (Validity X Condition interaction F (1,18) = 0.93, p = 0.35 and F (1,18) = 1.37, p = 0.26 for short and long SOA targets, Fig 6C).

There was also no main effect of condition in either target SOAs (both F's < 1, both p > 0.3).

Thus, the modulation of the P3 latency by temporal predictions did not differ between rhythm-based and memory-based predictions.


To examine whether the observed EEG results are consistent with an oscillatory entrainment mechanism, we used a computational oscillatory entrainment model [43,44] to estimate the ITPC magnitude and mean angles that entrained neural oscillators are expected to show in the three experimental conditions.

Following Large and colleagues [43,44], we used a model con- sisting of an array of neural oscillators with different characteristic frequencies in the delta range.

Each neural oscillator was modeled using a dynamical system characterized by two state variables, phase angle (ϕ) and amplitude (r), and was coupled to an external stream (s) that was modeled as a sequence of transients at the times of stimuli onsets:


In the absence of external stimulation (i.e., s(t) = 0), this system produces periodic dynam- ics, with the angle revolving steadily with time as a function of the F, the natural frequency of the oscillator.

When a stimulus is presented (s(t) = 1), an additional term corrects the angle towards zero, which is assumed to be the angle of the external stream.

The strength of correc- tion is determined by a coupling parameter c, which was adjusted such that the modeled ITPC levels in the Rhythmic condition would be similar to those observed in the actual data.

Given a set of initial conditions, this system can be numerically integrated to examine its convergence to a limit cycle, its phase consistency at times of stimulus onsets, and the angle at stimulus times to which it converges.


Note that (a) the focus was on the phase of the oscillator and not its amplitude; therefore, the system was simplified relative to a canonical coupled oscillator model (e.g., the one sug- gested by [43]) by fixing the amplitude; (b) to quantify the extent to which oscillators at differ- ent frequencies can be entrained to the stimulation streams, we used an array of oscillators with fixed periods instead of a single oscillator that can change its frequency.

Therefore, the system was simplified relative to a canonical coupled oscillator model by removing the period correction term; (c) the model was implemented such that instead of receiving only the period and phase of the external stream as input (which would have only allowed rhythmic external streams, [44]), our model received a time series of stimulus energy (0 = no stimulus, 1 = full stimulus energy), such that stimulus bursts can have any desired SOA.

To estimate the ITPC values and phase angles expected in the experimental conditions, we numerically integrated this dynamical system using the Runge-Kutta method (fourth order).

The frequency range of interest were 0.2 to 5 Hz (logarithmic scale), corresponding to interval lengths of 5,000 to 200 ms in 50 ms steps.

The coupling parameter c was adjusted such that ITPC values in the Rhythmic condition at the stimulation frequency would be similar to those observed in the empirical data.

For each participant and each experimental condition, we applied the following steps:


1. Generate the time series that represents a single trial in the current condition.

The stimula- tion stream in this trial was represented as a train of impulses at the times of stimulus onsets.

Specifically, we created a time series vector with a 1,000 Hz resolution (i.e., one value for every millisecond).

This time series contained one at the time of stimulus onset in the actual trial and zero otherwise.


2. Determine the initial phase angle for the current trial.

Phase angles were sampled without replacement from a uniform circular distribution of equally-spaced angles, the number of which was identical to the number of trials in the specific experimental condition (48 for the Rhythmic and Repeated-Interval conditions, 24 for the Random condition).

The initial phase angle was identical to all oscillators stimulated by this trial, which guaranteed match- ing phase dispersion between frequencies and conditions.


Numerically integrate the system given the trial time series and initial phase angle (from stages 1 and 2, respectively), separately for each oscillator in the oscillator array, and register the angle at the time of the last stimulus in the stream (the target) for that oscillator.


4. Repeat steps 1-3 for each trial, in each experimental condition, to obtain a series of angles for each natural frequency (48 trials in the Rhythmic and Repeated-Interval, 24 in the Random).


Calculate the ITPC and the mean angle across trials, identically to how it was calculated for the EEG angle data, separately for each natural frequency.


Files of raw behavioral and EEG data, model simulation data, and cover information are deposited at the Dryad data repository (http://dx.doi.org/10.5061/dryad.5vb8h) [84].


The current study compared predictions formed in a rhythmic context to predictions formed by interval memorization in streams that are less rhythmic, in order to dissociate these two prediction modes and put the putative manifestations of oscillatory entrainment to a critical test.

We found that PC and alignment of delta-band EEG activity did not differ between the Rhythmic and Repeated-Interval conditions.

Thus, these measures are not good indicators of entrainment mechanisms and could reflect memory-based predictions.

This was also the case for behavioral facilitation for expected targets, modulations of alpha amplitude and post-target P3 latency.

However, we also found that rhythm-based predictions resulted in slower responses to unexpected targets than memory-based predictions and in immediate resolution of the CNV when a temporal prediction was unexpectedly violated.

These possibly reflect a res- onance mechanism compatible with entrainment.

Our findings thus suggest that temporal predictions in rhythmic contexts is a combination of memory-based and entrainment-like mechanisms, affecting different manifestations of performance and electrophysiology.

Cru- cially, they imply that resonance after stream termination, and not PC during the stream, is the indicator of rhythm entrainment.


Delta-band activity at rhythmic stimuli times demonstrates enhanced PC around the opti- mal angle for performance relative, e.g., to aperiodic nonpredictive streams [3,6,7,21,22].

This phenomenon, also replicated in our data, is commonly interpreted as reflecting entrainment of intrinsic low-frequency neural oscillators to the external rhythm [10If similar delta PC is observed in streams that clearly promote oscillatory entrainment and streams that are more detrimental to entrainment, what could be the source of PC?


One plausi- ble alternative is the temporal predictability of the streams, which is inherent to rhythms [33,34] and was matched in our study between the Rhythmic and Repeated-Interval conditions.

Neurophysiologically, temporal predictability is known to drive buildup of neuronal activity to peak at the expected time point and then resolve [30,31,38], a phenomenon that is often referred to as climbing neuronal activity (CNA) [45,46].

This pattern produces a waveform with a wavelength matching the expected interval, which, as the rhythm interval is in the delta range, seems like an apparent delta cycle (see also [21], for acknowledging this possibility).

Since accurate temporal prediction means that the peak repeatedly coincides with the stimulus, apparent PC is observed around stimulus time.

Furthermore, PC is observed around the opti- mal phase because the CNA peak coincides with the time in which temporally driven prepara- tion is maximal, making it seem as an optimal phase.

It was recently argued that a CNA cannot account for entrainment effects, as PC did not increase in conditions in which the CNV ampli- tude was expected to increase [47].

However, phase consistency could in fact be independent of amplitude.

Regardless, the present findings directly show that rhythmicity is not needed for apparent delta PC and that it could be well explained by CNA.

Our study relies on scalp EEG but even with finer spatial resolution methods (e.g., electrocorticography), the critical compari- son we present here is needed to disentangle entrainment from repeating climbing activity.


The source of the CNA recorded in occipital channels is yet to be determined.

Several lines of evidence point to a key role of the motor system in timing and in the generation of CNA, intracranially [48-50] or on the scalp as the CNV [38].

Possibly, the observed occipital CNA reflects volume-conducted CNV originating in premotor regions.

Notably, this caveat applies to all EEG studies of visual and especially auditory rhythms, as auditory responses and the CNV are measured in the same sites.

However, the motor system has also been associated with predictions even when these are nonmotor [51] and was suggested to be involved in purely sensory temporal predictions [52-54].

Thus, another possibility is that the occipital CNA may result from top-down signals from the motor system that prepare the relevant sensory cortex at the right time [55,56].

A final possibility is that the occipital CNA originates from nonmotor duration representations, for example in parietal regions [57], or even localized timing mecha- nisms in the sensory cortex itself [58].


Further support for PC not being due to continuous rhythm entrainment comes from the finding that PC was low at the time of the WS, despite the WS being embedded in a rhythmic stream, anticipated, and task-relevant (as it signaled an upcoming target, see also Fig 2A and 2B for absence of CNV or any oscillatory trace prior to the WS).

We speculate that in para- digms in which there is no WS and all rhythmic stimuli are possible targets (e.g., [6,22]), CNA is elicited after each stimulus, resulting in apparent continuous oscillation.


Importantly, the current findings do not refute the existence of low-frequency oscillations, their role in sensory selection, or the possibility that they become entrained to external rhythms.

However, we argue that phase modulations, whether increased concentration or angle reversal, of filtered neural signal during the presentation of the stimulus stream cannot be taken as evidence for the existence or entrainment of such oscillations.

This argument is agnostic to the question of whether the climbing activity (and in particular the CNV) is a result of phase-resetting of ongoing low-frequency oscillations by the WS [11,21] (see also [59]).

However, in the Repeated-Interval condition such phase-resetting should be selective for the oscillator with the wavelength of the expected interval, based on memory, rather than on bot- tom-up entrainment.

Interval timing loses its efficiency for intervals outside the range of 200-2,000 ms (i.e., the delta range), [60].

Thus, it is less likely that the effects of rhythmic stimulation at faster rates, especially alpha in visual perception [18], can be explained by interval timing.

Given the prom- inence of alpha rhythms in visual cortex and its hypothesized relation to the timing of neural activation [61], it is possible that effects of alpha-rate stimulation are indeed mediated by entrainment of alpha oscillations, aligning stimuli with a preferred phase of the alpha cycle [14,15].

Future studies should examine the mechanism of alpha entrainment using appropriate control for temporal predictability as used here.


Previous studies separately found behavioral validity effects for rhythms and for memory- based predictions [16,25].

Rhythm processing is supported by the motor system, especially the supplementary motor area [62,63].

Given the manual nature of our task, it was plausible to expect an advantage of rhythm-based over memory-based predictions.

Indeed, rhythms exerted a stronger expectation, but this was expressed in larger cost of prediction violation, rather than in stronger facilitation for expected targets.

This suggests a dissociation between the processes involved in increasing preparation at expected times and relative inhibition at unexpected times instead of a tradeoff of the same resource between the expected and unex- pected times.

The pattern of CNV resolution when the anticipated event was unexpectedly omitted provides an apparent neural correlate for the extra cost of unexpected events (Fig 3).

When a short SOA target was expected but did not appear, the CNV resolved immediately towards baseline with rhythm-based predictions (compare with [9]) but only after a delay for memory-based predictions (compare with [37]).


The interpretation of this pattern depends on the process reflected by the CNV, an issue that is still under debate [64].

Under the model that the CNV reflect the accumulation of pulses of a timer mechanism [37,65], the CNV resolution reflects "emptying" of the accumulator once the memorized interval has elapsed and a decision has been made.

In this context, the delayed resolution of the CNV in the Repeated-Interval condition could result from reduced temporal accuracy of memory-based predictions, which rely on multiple factors like working memory, arousal, and attention [28,66].

This would lead to more jitter in the peak latency of the accu- mulation at the end of the expected interval and, as a byproduct, to "leakage" of preparation to times other than the expected time.


However, the timer model of CNV is challenged by recent arguments that the CNV resolu- tion is modulated according to optimal decision strategies, which suggests that the CNV is more likely to reflect active preparation than mere passive timing [64,67,68].

Thus, the differ- ence between our predictive conditions in the CNV resolution, as well as the RT results, imply that memory-based predictions are more flexible, allowing dynamic shifting of resources to unexpected times when a prediction is violated.

Rhythmic predictions on the other hand are obligating, with inability to maintain a high level of preparation in between rhythmic stimuli.

This obligatory nature of the rhythmic condition is in line with our previous finding, showing that rhythms affect the CNV even when they are not predictive and not intentionally used to form predictions [34].


Earlier P3 latency for temporally expected compared to unexpected events was previously observed in both rhythmic [34,36] and memory-based paradigms [26], although the two Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 18 / 30 modes were not directly compared until now.

Since the P3 has been related to stimulus eval- uation and response selection [41,42], the earlier P3 for temporally expected stimuli was interpreted as reflecting sharpening of such processes due to preparation.

Our results, showing similar effects of rhythmic and memory-based predictions, imply that this sharp- ening results from intentional usage of available temporal information, independent of its source.


Previous studies found amplitude reduction of occipital alpha-band oscillations before or at the expected time of a target embedded in a rhythmic stream [9,34,35].

Our findings suggest that this phenomenon (presumably indexing increased perceptual excitability) is a signature of temporally focused preparation in general.

Anticipatory reduction of occipital alpha-band amplitude was also observed in paradigms in which a nontemporal feature was anticipated, such as in reduction of alpha power in electrodes contralateral to an expected target location [69,70].

While spatial information allows biasing the cortical excitability to match the expected location (e.g., across hemifields), temporal information allows the increase of cortical excitabil- ity to focus at the expected time, possibly sparing resources.

This may underlie synergistic effects of temporal and spatial predictions [8,71].


We previously showed that P3 and alpha modulations occurred only when intentionally using rhythms to form predictions but not incidentally (in contrast to CNV effects that were also observed with passive exposure to nonpredictive rhythms, [34]).

Taken together, our current and previous results imply that the alpha-band and P3 effects reflect general mecha- nisms of intentional (rather than incidental) execution of temporal predictions, regardless of source.


Models of dynamic resource allocation argue for a dichotomy between temporally selective anticipation in rhythmic streams, mediated by oscillatory entrainment ("rhythmic" mode), and anticipation in nonrhythmic streams, which requires sustained vigilance ("vigilance" mode) [11].

These models leave out the well-documented memory-based resource allocation in time, which was shown to occur without rhythmic context [1,26].

Moreover, it was not clear whether rhythm- and memory-based temporal predictions are distinct at all, as interval-timing neural signatures were explained by oscillatory phase resetting [11], and, in contrast, seeming oscillations could be explained by repeated interval-timing [32] or even repeated evoked responses [72].

Similarly, imaging studies revealed that both rhythm- and memory-based tem- poral predictions activate similar regions (premotor and inferior parietal cortices, for a review see [73]).


Directly comparing conditions in which timing is predictable, based on memory, rhythm, and not at all, allows us to extend the dichotomy into a trichotomy: availability of temporal information, regardless of its source, allows the brain to shift from the "continuous" mode into a "temporally predictive" mode.

This is characterized by pretarget CNA (such as the CNV), anticipatory alpha reduction, and posttarget facilitation of processing of temporally expected events, reflected by earlier P3 latency and shortened RTs.

When anticipation is based on rhythms, the brain can further switch into a "rhythmic" mode, characterized by similar mani- festations but also by immediate cessation of facilitation and possibly inhibition once the expected time interval has elapsed, manifested by CNV immediate resolution and larger behavioral costs for unexpected events.

Methodologically, studies that aim to infer rhythm- specific mechanisms should use a less rhythmic predictive control similar to our Repeated- Interval condition, which would allow attributing the effects of rhythms to rhythmicity and not to general temporal prediction.


A central remaining question is whether the unique effects of rhythms are mediated by oscil- latory entrainment.

On one hand, this possibility is weakened by our finding that PC of low- frequency oscillations, which were usually conceived as a signature of rhythm-specific entrain- ment, was observed to the same extent in less-rhythmic streams.

On the other hand, oscilla- tions are characterized by resonance, that is, extension of several oscillatory cycles even when external phase-resetting input is terminated.

Findings fluctuations of several cycles in behav- ioral and physiological markers after stimulus termination was often interpreted as a direct evidence for the alignment of a self-sustaining oscillatory process to the external rhythm [74- 76].

In our data, the conspicuous and immediate return of the CNV to baseline after an omis- sion, in the absence of any external event to phase-reset it, represents the expected pattern of a resonance mechanism, consistent with entrainment.

It could also explain the increased cost of presenting targets outside the expected time window.


More than the ability to recruit resources, what seems to be unique to the rhythmic mode (and not to the anticipatory mode in general) is the tendency to "turn off" anticipation periodi- cally, consistent with the idea of energy efficiency [11].

While this mode is indeed efficient when the input maintains its predictability, the current findings also emphasize the inflexibility and resultant cost of this mode when events are temporally surprising.

This may be an unavoidable consequence of the oscillatory mode.


This study and all of its procedures, including subject recruitment methods, instructions, experimental task, apparatus, debriefing, and reimbursement, were approved by the local Eth- ics Committee of the Hebrew University of Jerusalem, Israel.

All participants provided written informed consent according to the local Ethics Committee and the Declaration of Helsinki.


Twenty-one students (11 females, mean age = 25, 19 right handed) were tested in return for course credit or payment.

Participants reported no history of neurological or psychiatric dis- ease, normal or corrected-to-normal vision, and no professional musical training or playing an instrument.


Stimuli were colored disks (diameter 1.2˚) presented for 100 ms.

Each trial began with a prepa- ratory sequence of stimuli, followed by a white WS and a green target to which participants had to respond with a speeded button press.

A fixation point (black "+", 0.6˚X 0.6˚) preceded each trial for 500 ms.


There were three conditions presented in different blocks (Fig 1A).

In "Rhythmic" blocks, the sequence consisted of four, five, or six (uniform probability) black sti- muli presented rhythmically with an SOA of 700 ms (1.43 Hz, short cue) or 1,300 ms (0.77 Hz, long cue).

The WS appeared in-phase with the rhythm.

The WS-Target SOA was identical to the rhythm SOA in valid trials or to the other SOA in invalid trials.


In the "Repeated-Interval" condition, the sequence consisted of four, five, or six (uniform probability) black-then-red pairs of stimuli.

The within-pair SOA was 700 and 1,300 ms in short and long cue trials, respectively, but the SOA between pairs was jittered (short trials: 1,500-1,900 ms, 50 ms steps; long trials: 1,900-2,700 ms, 100 ms steps, uniform distribution).

We assumed that this


Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 20 / 30 aperiodic sequence structure would reduce the ability of endogenous delta oscillators to main- tain a stable phase relation to the stream, as the first stimulus of each pair falls approximately on the opposite phase of the oscillation that is entrained by the previous pair.


The last pair of the sequence consisted of a white WS followed by a green target.

The SOA within this pair was the same as in the preceding pairs in valid trials and had the other SOA in invalid trials.


In both Rhythmic and Repeated-Interval conditions, the sequences were predictive of target tim- ing, as 75% of the trials within a block were valid and 12.5% invalid.


In the remaining 12.5% of the trials, in each condition no target appeared following the WS, in order to diminish expecta- tions based on conditional probability that the stimulus will occur given that it has not occurred yet [25].

In these "catch" trials, a blank screen was displayed after the WS for 1,500 ms.


Finally, in the "Random" condition, the sequence consisted of four, five, or six (uniform probability) stimuli whose SOAs were jittered around the average of 700 or 1,300 ms (−200 to +200 in 50 ms steps, uniform distribution).

Target SOAs were also drawn from these short and long distributions, independently from the average sequence SOA [34].


While the sequence was not predictive, for analysis purposes, "valid" trials were defined as those in which cue and target SOAs were drawn from the same distributions (e.g., short cue trials followed by short SOA targets, 43.75% of the trials) and "invalid" trials as those in which cue and target SOAs were drawn from different distributions (e.g., short cue trials followed by long SOA targets, 43.75% of the trials).

The other 12.5% of the trials were catch trials.


The experiment was conducted in a sound attenuated chamber (Eckel C-26, United King- dom).

Stimuli were presented at the center of a 17-in CRT screen (ViewSonic G75f, with 100 Hz refresh rate) on gray background (viewing distance = 90 cm).

Stimulus presentation and response acquisition were handled using Psychophysics toolbox [77,78] for MATLAB (version 7.5.0, Mathworks, Natick, Massachusetts).


Trials were presented in blocks of 32 trials.

The experiment started with two Random blocks.

Next, Repeated-Interval and Rhythmic blocks alternated (four each).

Which condition started was counter-balanced across participants.

Par- ticipants were encouraged to use the predictive information if available.

Eight practice trials were performed on first encounter with each condition and at least two trials for ensuing blocks.

Short breaks were given between blocks.


At the end of the experiment, participants were debriefed, verifying that they had used the predictive cues to create predictions.


Prior to the entire experiment, all participants conducted three blocks of a condition from our previous study ("Non-Informative" condition) [34] for replication purposes.

This condition and its results will not be presented in the main text (see S1 Text, and [34]).


For each participant, trials were discarded if the RT was larger than three standard deviations from the mean RT, separately for each condition and validity of the cue, or if the RT was shorter than 50 ms.

RTs were subjected to a repeated-measures ANOVA with factors condi- tion (Random/Rhythmic/Repeated-Interval), cue validity (valid/invalid), and target SOA (short/long).

Where the sphericity assumption was violated, we report Greenhouse-Geisser corrected p-value and uncorrected degrees of freedom.

Due to the small number of trials at the exact in-phase SOA in the Random condition, trials with SOA of up to 100 ms around the short and long target SOAs were used as representing these SOAs.

The range of this interval (50-150 ms) did not affect the pattern of results.

To examine the benefits and costs of having temporal predictions, we separately analyzed valid and invalid trials, conducting planned one- Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 21 / 30 tailed contrasts to compare each predictive condition to the random condition, and two-tailed contrasts to compare the predictive conditions.


EEG was recorded continuously from 64 preamplified Ag/AgCl electrodes, using an Active 2 system (BioSemi, The Netherlands) mounted on an elastic cap according to the extended 10- 20 system.

Additional electrodes were placed on the outer canthi of the right and left eyes and above and below the center of the right eye to track electro-oculographic activity, on the left and right mastoids, and near tip of the nose.

The EEG signal was sampled at a rate of 1,024 Hz (24 bits/channel) with an online anti-aliasing 204 Hz low-pass filter.

EEG preprocessing was conducted using BrainVision Analyzer 2.0 (Brain Products, Germany) using the following pipeline: referencing to the nose electrode; high-pass filtering using a zero-shift Butterworth filter with a cutoff of 0.1 Hz (24 dB/octave); correction of ocular artifacts using independent component analysis (ICA) [79] based on typical scalp topography and time course; elimination of epochs which contained other artifacts, defined as absolute activity larger than 100 μV, or a change of more than 100 μV in a 200-ms interval.

The data of two participants were rejected from EEG analyses due to excessive artifacts.


ERPs were analyzed separately for the preparatory period, i.e., during the presentation of the stimulus sequence, and the posttarget period.

For all ERP analyses, the data was re-referenced to the average of the left and right mastoids.

In the preparatory period, the analysis was con- ducted in two predefined electrode clusters: a central cluster (FC1, FCz, FC2, C1, Cz, C2, CP1, CPz, CP2), to test for modulations of the CNV potential, and an occipital cluster (PO3/PO4, PO7/PO8, O1/O2), to test oscillatory activity in visual circuits.

To visualize ongoing activity in these two clusters, segments extending from 5,600 or 3,200 ms before the target (for long and short SOA trials, respectively) to 1,000 ms after the target were averaged within condition across trials and subjects.


Two a priori hypotheses were tested regarding the CNV in the central electrode cluster.

First, we examined whether the modulation of the CNV buildup by the expected SOA (i.e., faster buildup as the expected SOA is shorter, [9,26]) differs between conditions.

For this, segments extending from 200 ms before to 1,300 ms after the WS were averaged within each condition for valid trials, separately for short and long cue SOA (in the Random condition according to the average of the sequence), with the period of 200 ms before the WS used as baseline.

In the Random condition, we only used trials in which the target did not inciden- tally appear in the first 700 or 1,300 ms after the WS, for short and long SOA trials, respec- tively.

Within each condition, the average CNV amplitude in a window of 400 to 700 ms after the WS was compared between expecting the target in short and long SOAs.

This time window was chosen to provide maximal differentiation, as it was at the end of the short inter- val but in the middle of the long interval.

Planned one-tailed contrasts were used to examine the hypothesis that the CNV will be more negative when expecting the target at a short SOA than long SOA.


Second, we compared the resolution of the CNV (i.e., return to baseline, [9,37,40]) between the different conditions in trials where an expected short SOA target was omitted (i.e., short- cue, invalid trials).

In this situation, the timed interval ends, but no target appears to end the anticipation.

For this, segments extending from 200 ms before to 1,400 ms after the WS were averaged separately for the Rhythmic and Repeated-Interval conditions, with the period of 200 ms before the WS used as baseline.

To quantify the CNV resolution, we fitted the amplitude of Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 22 / 30 the CNV waveform (averaged across participants) in each condition with a five-parameter continuous model, which allowed the CNV to buildup, remain at the peak amplitude for a flex- ible interval, and only then resolve (Fig 3C):


The free parameters of the model were the buildup initiation time (T 0 ), buildup slope (S 1 ), buildup termination time (T 1 ), resolution initiation time (T 2 ), and resolution slope (S 2 ).

The possibility for a variable delay between T 1 and T 2 allowed accurate estimation that would not be distorted by predefined choice of intervals and also reflected a cognitively plausible strategy of maintaining high preparation after target omission, in case the target appears at the long SOA.

Each parameter was compared between the Rhythmic and Repeated-Interval conditions using paired t tests using the jackknifing procedure (see S1 Text).

To verify that the five- parameter model does not overfit the data, this "resolution after delay" model was compared to a more restrictive four-parameter model, "immediate resolution," in which the transition between buildup termination and resolution initiation was immediate (T 1 = T 2 , see Fig 3D).

Model fitting was conducted using the "fminsearch" function in MATLAB (Nelder-Mead sim- plex optimization) with several initial values.

Model selection was based on calculation of the Bayesian Information Criterion (BIC, [80]).

For each condition, the model with the lowest BIC value was chosen (ΔBIC > 6 is considered strong evidence).


ERP analysis of posttarget activity focused on the P3 potential, which was analyzed at a cluster of midline-parietal electrodes (Pz, P1, P2).

We examined whether the modulation of the P3 latency by the validity of temporal prediction (shorter latency when the target appears at the expected SOA, [8,26]) differs between conditions.

For this, segments extending from 200 ms before to 700 ms after the target were averaged in each predictive condition, sepa- rately for trials with short or long target SOA and for valid or invalid cues.

As the pretarget CNV effect was expected to result in differences in the pretarget baseline in short versus long target SOAs, we used a period of 200 ms before the WS as baseline and analyzed each target SOA separately.

The time window for P3 analysis was 200-550 ms after target onset, based on unbiased visual inspection of average activity across all subjects and conditions.

The P3 latency was estimated by averaging the latencies in which the amplitude reached 30%, 50%, and 70% of the peak amplitude, allowing a stable estimation of the half-maximum point [81].

Reliable estimation of these latencies was achieved using a jackknifing procedure.

Within each condition and target SOA, the amplitudes and latencies of the P3 were each subjected to a repeated-measures ANOVA with factors condition (Rhythmic/Repeated Interval) and target validity (valid/invalid), and planned one-tailed contrasts were used to examine whether the P3 latency is shorter when the target SOA was expected compared to unexpected.


Following previous findings [9,34,35], we analyzed amplitude modulations of alpha-band activity (8-13 Hz) in occipital electrodes (PO3/PO4, PO7/PO8, O1/O2) by temporal


Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 23 / 30 predictions.

We compared the amplitude of alpha activity at the time of the short SOA target when expecting the target at the short versus long SOA.

In both short and long SOA trials, we only included trials in which the target actually appeared at the long SOA, avoiding contami- nation by target-evoked activity.

Thus, the only difference between the trials was the predicted target time.

We asked whether an amplitude reduction at the time of a temporally expected tar- get would differ between the different sequences.


The data were segmented from 1,400 ms before the WS to 1,800 ms after the target.

Instantaneous amplitudes were extracted using a complex Morlet wavelet transform (1-30 Hz, 1 Hz steps, ratio between the central frequency and the standard deviation of the Gaussian-shaped wavelet in the frequency domain = 8).

The first and last 1,000 ms of each segment absorbed edge artifacts and were discarded from analy- sis.

The resulting time-frequency representations were averaged across electrodes within each condition.


Baseline correction was performed using a range of 0-100 ms after the WS, as the occurrence of the WS is the only time point that is identical both in function and in perceptual input between the short and long SOA conditions (pre-WS intervals were contaminated with residual activity from previous stimuli, see [34]).

Average alpha-band amplitude (across 8-13 Hz and 700-900 ms after the WS) was subjected to a repeated-measures condition (Rhythmic/ Repeated-Interval) X expected SOA (short/long) ANOVA.

Within each condition, planned one-tailed contrasts examined whether the alpha-band amplitude is reduced when the target was expected at the short SOA compared to the long SOA.


We analyzed the effects of temporal predictions on the phase of delta-band activity in occipital electrodes in which these effects were expected to be maximal (PO3/PO4, PO7/PO8, O1/O2).

We examined whether increased PC and alignment to the optimal phase angle at target time [3,6,7,21,22] occur in the rhythmic and Repeated-Interval conditions.

Instantaneous phase of delta-band activity was extracted by band-pass filtering the unsegmented data in a frequency band of 0.5-3 Hz (zero-shift Butterworth filter, 24 dB/octave) and applying the Hilbert trans- form.

This was performed separately for each occipital electrode and then averaged (consider- ing the circularity of phase) across electrodes.

The delta-phase signal was segmented into epochs surrounding valid targets (−700 to 500 ms for short SOA targets and −1,300 to 500 ms for long SOA targets), separately for the Rhythmic, Repeated-Interval, and Random conditions and, for comparison, also surrounding the WS in the Rhythmic condition.

Analyses of circular variables were performed using the CircStat toolbox for MATLAB [82].


To examine whether certain phase angles were optimal for performance we tested the circu- lar-linear association between delta phase at target time and RTs in the random condition (as in the predictive conditions delta-phase was expected to have small variance due to PC).

We used a linear mixed-effect regression model to estimate this association at the group level, allowing each subject to have a different optimal value (see S1 Text).

Delta phase was linearized by taking its sine and cosine and using them as fixed effects along with target SOA.

The inter- cepts of participants, as well as by-participant random slopes for sine and cosine of the phase, were inserted as random effects.


Second, we examined delta PC at stimulus time (target/WS) by calculating the ITPC [83].

Across participants, these ITPC values were compared between conditions using an omnibus repeated-measures ANOVA with factors condition (Rhythmic/Repeated-Interval/Random/ WS-Control) and SOA (short/long), followed by subsidiary ANOVAs for comparing specific condition pairs.

Specifically, we examined the occurrence of ITPC in the predictive conditions by comparing them to the controls, and also compared the Rhythmic and the Repeated- Mechanisms of rhythm- and memory-based temporal prediction PLOS Biology | DOI:10.1371/journal.pbio.2001665 February 10, 2017 24 / 30 Interval conditions.

Due to the nonnormality of the ITPC data (bounded between zero and one), we used permutation-based ANOVAs (see S1 Text).


Finally, we examined whether delta phase at target time was aligned to the optimal phase angle, which was identified in each participant and each SOA by averaging the phases of the 33% fastest trials in the Random condition.

For each predictive condition, we then calculated for each participant the circular distance between the circular-averaged phase angle at target time and his\her optimal phase.

If the phase at target time was shifted to the optimal angle, the expectancy of these differences is zero, so they should be concentrated around zero across sub- jects.

We tested this using a V test, which contrasts a null hypothesis that phases are uniformly distributed to an alternative hypothesis that phases are unimodally distributed with an a priori specified mean angle, which, in the current case, was set to be zero (see [7]).

With the same approach, we also tested whether the phase angle at target time was identical between short and long SOA targets.


Neural oscillations align to external stimulus rhythms, such as the recurring onsets in rhythmic sequences, via neural entrainment—that is, adjustment to the oscillation’s phase and period.

As such, measures of neural phase coherence or “phase concentration” can inform us about the precision of entrainment.

Entrainment of ongoing neural oscillations is considered a potent mechanism that the brain utilizes to generate temporal predictions and to aid active perception, at least in sensory cortices.

However, as attempts to falsify or question this hypothesis are scarce, the idea that temporal predictions are instantiated in neural oscillatory entrainment should not be set in stone just yet.


For this reason, it is very important that a recent study by Breska and Deouell, published in PLOS Biology [1], set out to determine whether phase concentration at the time of a critical target stimulus would also be observed in instances when stimulus sequences are non-rhythmic, but targets are nonetheless temporally predictable [2].

Indeed, temporal predictions can certainly be formed on the basis of non-rhythmic information, such as the passage of time itself [3].

Breska and Deouell propose a “memory-based” prediction mechanism that would not be instrumented by entrainment but instead might utilize alternate, interval-based timing mechanisms [4,5].

While the study raises very important questions, logical and methodological considerations have motivated us to lay out a short guide for future experiments that aim to demonstrate oscillatory entrainment or the lack thereof.

Throughout, we support our arguments with simulations and supplemental audio, which can be found at https://osf.io/phs6e/.


Breska and Deouell aimed to assess behavioral and electrophysiological measures in contexts that vary in their rhythmicity, with the goal of exploring the bounding conditions of neural entrainment as well as the neural mechanisms that might support temporal predictions when entrainment is not possible.

The trouble with examining neural mechanisms in contexts with varying rhythmicity is that we are still lacking a good working definition of rhythm.

What does “rhythm” mean to a human or non-human brain, and to a perceiver more generally, and how variable does a sequence of events need to be so that our brains will cease to register it as rhythmic? Many researchers seem to use “rhythm” to refer to isochrony, that is, strict regularity, and contrast this with situations in which sequences are composed using variable stimulus onset asynchronies (SOAs; e.g., “repeated-interval” and “random” conditions in Breska and Deouell’s study).


However, there are many types of sequences that might be perceived as rhythmic despite being decidedly aperiodic and having relatively high variance in terms of the intervals making up the rhythm.

For example, metrical musical rhythms comprising intervals of different sizes (e.g., quarter notes, half notes, and dotted half notes) can give rise to a sense of regularity at a rate that is not actually represented by any of the intervals in the sequence (that is, at the whole note level).

In fact, many previous studies on neural entrainment did not even utilize the strictly isochronous sequences presented here as a hallmark of rhythm but instead allowed for considerable jitter between single stimuli (e.g., [6–9]).


Empirically, rhythmicity can be assessed best by asking individuals whether they perceive a sequence as rhythmic.

To this end, we transferred Breska and Deouell’s sequences to the auditory domain (arguably the more natural domain for assessing rhythm and entrainment) in an exercise that was quite informative: it turns out that their “repeated-interval” condition, conceived to reduce rhythmicity, feels very rhythmic indeed (see supplemental audio at https://osf.io/phs6e/).

Theoretically, rhythmicity can be assessed by attempting to align (that is, to entrain) a sinusoidal oscillation to a stimulus sequence (Fig 1), as Breska and Deouell have also done: if the oscillation aligns to the sequence such that its relative phase is sufficiently non-random relative to stimulus onsets, the sequence should be considered rhythmic from the perspective of the underlying oscillator.

Our attempts to do so suggest that the degree of jitter employed by Breska and Deouell, even in their “random” condition, would still allow for successful neural entrainment (Fig 1C).

We note that Breska and Deouell also report results of such a simulation and also show that, in particular for the long SOA condition, their “random” stimulation would have led to successful oscillatory entrainment.


An orthogonal issue contributing to Breska and Deouell’s largely similar phase-concentration results across “rhythmic” and “repeated-interval” conditions is the presence of large-amplitude contingent negative variation (CNV) and P3 components flanking the targets, which likely distorted the phase measures and resulted in artificially high phase concentrations (Fig 1D).

This suggestion (also put forward by Breska and Deouell) was confirmed by our simulations and accurately predicted lower phase concentration at the time of the warning signal compared to the time of the target, which would not be predicted by neural entrainment alone (Fig 5B of Breska and Deouell [1]).

The bottom line here has already been discussed at length in the field: phase concentration measures do not just index oscillations—they index the entire underlying signal—and therefore should be interpreted with utmost caution.


Nonetheless, to conclude that “phase concentration and alignment of slow EEG [electroencephalogram] oscillations are not a signature of rhythmic entrainment” ([1]; as in the title of their paper) is worrisome: Breska and Deouell seem only to consider the possibility that entrainment measures might not be good indicators of entrainment.

Potentially, however, their manipulation simply did not vary the intended independent measure (that is, rhythmicity) to a conclusive degree.


Our reservations notwithstanding, Breska and Deouell’s paper is an important reminder of how little we actually know about the way(s) in which rhythmic—or otherwise predictable—patterns in our environment are utilized by behaving organisms.

Accordingly, a hallmark contribution of their paper is to demonstrate the behavioral costs (in terms of response times) that can arise for a behaving organism from entrainment to a strictly periodic stimulus.


Let us conclude by briefly outlining requirements of an experiment that we think would settle the important questions raised by Breska and Deouell more conclusively.

First, the experiment would need to manipulate a perceiver’s ability to predict the precise timing of upcoming, behaviorally relevant events by truly varying rhythmicity.

That is, the presence of rhythmicity should be empirically verified by asking for information about the (non-)rhythmic percept.

One particularly promising approach is to manipulate meter: rhythms with different degrees of perceived rhythmicity can be constructed by reordering the exact same interval set, creating stimuli with identical statistical properties but different degrees of perceived regularity [13].

Such stimuli allow for a rigorous test of the effects of rhythmicity on neural entrainment.


Second, we suggest that unpredictable, near-threshold targets avoid as much as possible the contamination by large CNV and P3 components that can distort phase-concentration measures.

Inevitably, however, testing a memory-based prediction mechanism is contingent on a subject’s ability to predict when the target will occur—a process that can hardly escape large transient evoked responses like the CNV and so may be better studied using a psychophysically sound behavioral paradigm.

It remains to be conceded, however, that it is far from trivial to arbitrate between a (theoretically and empirically thus far substantiated) entrainment account on the one hand, and a potentially more parsimonious view that would subsume both periodic and aperiodic predictions but might challenge entrainment on the other.


So, what do we talk about when we talk about rhythm? As we have laid out here, regularity manipulations themselves need to be of sufficient magnitude and quality to modulate both percepts of rhythmicity and entrainment of a (neural or other) oscillator.

Even then, however, our beloved tools for dissecting rhythmic and non-rhythmic processes in the neural domain can be turned into rusty blades by notorious interpretational problems.

This should encourage us to humbly spell out our predictions in those domains where rhythm truly resides: in perception and behavior [14].


The idea of entrainment of neural oscillations to temporal structure has become a central theory for attentional selection in time [1,2].

In our study [3], we separated unique electroencephalogram (EEG) signatures of oscillatory entrainment to rhythmic streams from those (specifically, inter-trial phase coherence [ITPC]) that overlap with other mechanisms of prediction.

Obleser, Henry, and Lakatos’s (OHL’s) comment [4] highlights important issues regarding the study of entrainment mechanisms.

We share OHL’s main message: rhythms may be complex and not necessarily isochronous.

In fact, finding a stream devoid of any regularity is challenging.

This is probably why entrainment mechanisms are functionally important! Yet we should not see entrainment mechanisms as omnipresent, nor should we render them irrefutable.

Below, we reflect on some of OHL’s concerns regarding our study.


Oscillatory entrainment predicts increased ITPC for rhythms [2,5], as both our and OHL’s models show.

However, taking ITPC as evidence for entrainment, without ruling out other explanations, would be making the logical fallacy of "affirming the consequence" (a!b does not imply that b!a).

Our study [3] thus asked which electrophysiological phenomena are uniquely associated with entrainment to rhythms instead of with general temporal prediction mechanisms that also operate in rhythmic contexts [6].

We conjectured that if ITPC reflects entrainment it should be sensitive to the level of regularity.

However, we found that reducing the level of temporal regularity of streams did not reduce ITPC when predictability was preserved but only did so if predictability was also reduced.

OHL’s argument that this is explained by predictions-related climbing neuronal activity (CNA; e.g., the contingent negative variation) only recapitulates one of our main arguments [3].

Given this fact, can a repeated-CNA explanation be ruled out from previous ITPC findings, especially in designs with no warning signal?

Using near-threshold stimuli [7] reduces onset-responses–driven ITPC but not anticipatory activity.


OHL point out (like we did [3]) that our repeated-interval condition (RIC) was not arrhythmic, explaining observed ITPC levels.

Critically though, the RIC was not designed to be arrhythmic but to be less periodic than the isochronous condition (IsoC), which should diminish entrainment signatures.

For perceptual judgments evidence (cf.

OHL’s demo) that this was achieved, see Fig 1.


However, in accordance with OHL’s appropriate assertion that rhythmicity is ill defined, we worry that resorting to subjective judgment falls into the same ambiguity of periodicity/predictability that motivated our study.

Preferably, the degree to which a sequence is conducive to entrainment of a given oscillation, well defined by frequency and phase, could be objectively quantified.


In fact, OHL’s model, like ours, predicts a difference in phase (their figure 1b) and a lower ITPC (their figure 1c showing the effect of stimulus onset asynchrony [SOA] variance) in the RIC compared to IsoC. However, being a single-oscillator model with adjustable frequency, OHL’s model cannot attribute the ITPC to specific frequencies.

Our multi-oscillator model shows that the expected ITPC is in lower frequencies in the RIC than the IsoC, consistent with the RIC being by design destructive to entrainment at the IsoC frequency.


The predictions of both entrainment models are thus inconsistent with the EEG findings of similar ITPC, in the same frequency, and to the same (behaviorally optimal) phase angle in the 2 conditions.


For us, the strongest indication that the 2 sequences, while not differing in ITPC, were not as “rhythmic” (able to entrain) for the brain is the clear behavioral and electrophysiological differences they induced [3].

Crucially, these differences agreed with entrainment theories: the more rhythmic IsoC led to resonance and momentum after stream termination.

We emphasize again this overlooked point: our findings support, rather than falsify, entrainment theories.

However, they call for proper predictability controls when using ITPC during stream presentation as evidence for entrainment.

We join OHL in hoping for clearer definition and careful controls when dissecting predictive mechanisms.


An awake craniotomy (AC) is the gold standard for the resection of supra tentorial brain tumours in eloquent areas.

Intraoperative monitoring "ondemand" of essential eloquent brain functions and the increasing need to preserve higher intel lectual functions during surgery requires a unique anaesthetic approach during AC.

Dexmedetomidine is considered the firstchoice pharmacological agent for sedation during AC.


Twentysix patients with a single brain tumour located in areas of eloquent brain function were enrolled in this prospective study.

The patients underwent AC un der conscious sedation.

Motorevoked potentials and brainstemevoked auditory po tentials were measured using neurophysiological tests during surgery to assess brain potentials.

Intraoperative brain relaxation was reached using a modified Bristow scale.

Neuromonitoring and psychological tests were maintained until meningeal closure.


All operations were carried out successfully, and no reoperations were needed.

No significant impact on circulatory and respiratory parameters was observed during conscious sedation based on dexmedetomidine.

Neither instrumental airway support nor conversion to general anaesthesia was necessary.

Brain relaxation was good in 84% of cases.

Intraoperative epileptic episodes were observed in 15% of the patients.

Neuro logical and psychological monitoring was satisfactory.

Unaltered muscle force was ob served postoperatively in 88% of the patients.


AC performed under conscious sedation, and dexmedetomidine infu sion without instrumental airway support, was safe and welltolerated by patients with comfortable physiological sleep for most of the procedure.

This approach to AC was associated with minimal risk of perioperative adverse events and may be particularly beneficial in patients with severe comorbidities.


Bogusława Ewa Lechowicz-Głogowska, Agnieszka Uryga, Artur Weiser, et al. ation, significantly increases the chance of a good neurological and cognitive outcome [8].


Awake craniotomy (AC) is the gold standard for surgical removal of tumours in eloquent areas of the brain.

Maximal tumour resection with simultaneous preservation of brain functions such as movement, speech, and cognitive abilities are the goals of these procedures [9].

The joint use of brain-evoked poten- tials, neuropsychological tests, and intraoperative real-time imaging (magnetic resonance imaging [MRI], ultrasound, or computed tomography [CT]) increases the probability of maximal and functional- ly safe tumour resection [10-12].

However, the best method of anaesthesia for AC is still in question.


Various anaesthetic management protocols are used for AC, such as the asleep-awake-asleep tech- nique (AAA), monitored anaesthetic care (MAC), and CS with propofol, remifentanil, and infiltration anaes thesia [9, 10, 13, 14].

Most clinicians use the AAA technique with instrumental upper airway sup- port during the initial and closing phase.

The patient is awake only during neurological monitoring [15].

The intubation tube or the laryngeal mask inser- tion can be very difficult due to the patient's fixed head position in a Mayfield clamp and the surgical dressings that cover the head.

During intubation or extubation, various adverse effects can occur, such as prolonged apnoea, hypoventilation, and reten- tion of CO 2 .

All of these events can cause extensive brain oedema, epileptic episodes, additional brain ischaemia near the edge of the craniotomy, or in- tense bleeding in the operating field and may even prevent further surgery.

Sedation with propofol and opioids may lead to respiratory depression with hypercapnia, and hypoxia, which results in brain oedema.

Furthermore, other adverse events can occur during conventional sedation: vomiting, myo- clonus, uncontrolled movement of the patient, and non-cooperativeness [16-18].


Due to difficulties with AAA (agitation, difficult airways, uncooperativeness, sudden disagreement about being awake during surgery), another anaes- thesia protocol that is better tolerated is needed.

Dexmedetomidine, which is used as a basic seda- tive for AC, may be a promising solution.

This alpha2 adrenoceptor (a2-AR) agonist works as a sedative, light anxiolytic, and analgesic through the activa- tion of a2 brain receptors.

It does not depress res- piration and has no impact on the neurophysio logy of the brain.

In addition, it does not negatively in- fluence monitored brain-evoked potentials and can protect the brain.

Through activation of receptors located in the coeruleus locus area of the brain, dexmedetomidine mimics the natural physiologi- cal pattern of sleep without REM phase II/III [11-13].


In this study, the results of a CS research proto- col using dexmedetomidine infusion and a scalp block with ropivacaine are presented.

The objec- tive of this research was to evaluate the risk of re- spiratory and circulatory complications, changes in neurophysiological monitoring, and other adverse events during AC.

The vital element of this protocol was the psychological evaluation before, during, and after surgery.


This study was a single-centre prospective study without a control group for comparison, approved by the Bioethics Committee of the University Hos- pital in Wroclaw (10.10.2013) and by the Bioethics Committee of the Wrocław Medical University (KB - 279/2016 [02.06.2016]) in accordance with the Declaration of Helsinki.

Written informed consent was obtained from all subjects.


Thirty-one patients admitted to the University Hospital in Wroclaw between 2014 and 2018 were screened to ensure they met the study inclusion cri- teria.

The main inclusion criteria were a single brain tumour localized near or in the eloquent cortical areas (qualified for elective AC), good neurological state, age > 16 years, ASA 1-4, good patient cooper- ation, and good intellectual function confirmed by neuropsychological tests.

Exclusion criteria included alcohol or drug abuse, psychiatric disorders, severe anxiety, allergies to study medications, recent clini- cal manifestation of epilepsy, electrolyte or acid- base imbalance, significant glucose imbalance, low heart rate (< 55 bpm), arrhythmias and lack of neu- ropsychological evaluation.

Figure 1 presents a flow chart showing exclusion criteria and the experimen- tal design of the study.

Ultimately, 26 patients were enrolled in the study.


The preoperative patient evaluation was per- formed at least one day before surgery.

A neuropsy- chological evaluation, including a general assess- ment of neurological and psychological status, as well as an evaluation of the higher mental functions (such as speech, memory, thinking, perception, and attention), was performed using the following bat- tery of tests (before surgery): STAI - Inventory of State and Anxiety (C.D. Spielberger, R.L. Gorsuch, R.E. Lushene), Eysenck Personality Questionnaire-Revised Short Scale (EPQR-s), Hamilton Depression Rating Scale HAM-D, Numerical Rating Scale, Benton Visual Retention Test, Hodges J. Addenbrooke Cognitive Examination - ACR-III, Schmidt M. Rey Auditory Ver- bal Learning Test (RAVL); (intraoperatively): Hodges J. Addenbrooke Cognitive Examination -ACR-III, and W. Łucki questionnaire for the study of cognitive pro- cesses in patients with brain injuries.

Furthermore, each patient was informed of the operation in terms of decision-making and motivation for participation.

The issue of stress management, anxiety, and claus- trophobia was also discussed.

Patient treatment sat- isfaction was assessed using the Postoperative Short Psychological Questionnaire (see Supplemental File) and the following battery of tests: Addenbrooke's Cognitive Examination - ACE-III, Rey's Auditory Verbal Learning Test (RAVL), Benton's Visual Retention Test, and the numerical rating scale.


Premedications were not used, to avoid any pos- sible influence on cognition.

We avoided a loading dose of dexmedetomidine due to the risk of cardio- vascular depression.

We prefer a stable low-dose infusion of dexmedetomidine (0.1-1.0 µg kg -1 h -1 ).

The level of sedation was adjusted to the surgery phase to reach a level of sedation of -1/-3 on the Richmond Agitation Sedation Scale (RAAS).


After intraarterial cannulation under local anaes- thesia, the following parameters were monitored: electrocardiography, heart rate (HR), intraarterial blood pressure, bispectral index monitoring (BIS) (Integra, Ohio, USA) with electrodes typically fixed on the contralateral side of the craniotomy, satura- tion (Pulsoximetry, LG, Korea), respiratory frequency, and EtCO 2 with a nasal cannula.

Saturation, EtCO 2 , systolic arterial pressure (SAP), diastolic arterial pres- sure (DAP), mean arterial pressure (MAP), and HR were collected and analysed at baseline before dex- medetomidine infusion (T0), and then 5, 10, 30, and 60 minutes (T5, T10, T30, T60, respectively) after the start of dexmedetomidine infusion and 60 minutes after discontinuation of dexmedetomidine (Tpo).

Arterial blood gases (PaCO 2 , PaO 2 ), electrolytes, and glucose levels were collected and analysed at T0, T30, T60, and Tpo.

Furthermore, a modified Bristow Scale was used to assess brain relaxation after dura opening (quality of operative condition).


The standard analgesia plan was provided peri- operatively to our patients.

Paracetamol (acetamin- ophen) 1.0 g IV or metamizole 2.5 g IV was given before skin incision, and then both drugs - postope- ratively, in dose 1.0 g IV every 6 hours and 8 hours, respectively.

It was continued for 24-48 hours ac- cording to the requirements of individual patients.

There were no patients with an allergy to those drugs in the presented cohort of patients.

A scalp block was performed using 0.75% ropivacaine with adrenaline 1 : 200,000.

If a patient complained of pain, assessed on the Visual Analogue Scale (VAS), then additionally IV/SC oxycodone was used at a dose of 5-10 mg every 4 hours.


The small doses of propofol (10-20 mg IV) were used for scalp block, head fixation with a Mayfield clamp to the meningeal opening, and skull closure.

Some patients were also given small doses of mid- azolam (0.5-1.0 mg IV) after the neuromonitoring and psychological evaluation phase.

Before skull pin application, local skin was anaesthetized with 2-3 mL of 1% lidocaine and adrenaline 1 : 200,000 at each pin site.

Next, each patient received ondanse- tron (8 mg IV), omeprazole (40 mg IV), dexametha- sone (8-12 mg IV), and mannitol (0.5 to 1.0 g kg -1 ) within 20 to 30 minutes of skin incision.

The infusion was completed before opening the dura.

The dura was then flushed with 10 mL of a 1% lidocaine solu- tion before the incision.

In the event of an epileptic seizure, the following medications were prepared: clonazepam, valproate acid, midazolam, propofol, and ice-cold saline (to apply to the operating field).


Oxygen was provided through a mask at 2-4 L min -1 , and PaO 2 was maintained at a level between 100 and 160 mmHg.

Instrumental airway manage- ment and conversion to general anaesthesia were pre- pared (if necessary).

The patient was placed according to the surgeon's preference and checked to ensure safe positioning.

The neck and legs were supported with pillows as needed.

The patient's face was uncov- ered with surgical covers secured above the face.

Con- stant and clear access to the head was maintained for patient observation and to allow instrumental airway support if needed.

Before mapping the cortex and neurological tests, the infusion of dexmedetomidine was stopped.

During the post-monitoring closure phase, the sedation was deepened, if necessary, with an infusion of small doses of propofol, midazolam, or fentanyl.


During surgery, the following brain potentials and neurophysiological tests were performed: mo- tor-evoked potentials (MEP) - after direct electrical stimulation of the cortical and subcortical brain re- gions, brainstem-evoked auditory potentials (BEAP) Bogusława Ewa Lechowicz-Głogowska, Agnieszka Uryga, Artur Weiser, et al. - for the evaluation of brain function, sensation - as- sessed by a subjective feeling of sensory phenome- na by the patient.


Motor functions were evaluated based on electromyography (EMG) traces.


During the resection of the brain tumour, the patients performed motor tasks to engage specific groups of muscles necessary for the movement of the in- dicated limb.


Furthermore, the patients contracted the indicated muscles while needle electrodes were inserted.


The higher psychological functions, such as speech, memory, attention, and perception, were assessed with neuropsychological tests.


The entire exposed gyri were stimulated directly in 5-mm steps using a bipolar electrode with a tip distance of 5 mm.


During stimulation, patients were asked to perform either a counting task or a naming test.


All black and white pictures presented were famil- iar to the patient according to preoperative assess- ment, and each name was preceded by 'this is' [16].


Speech arrest or the appearance of semantic errors was considered a positive result of mapping and led the surgeon to mark it [17].


Statistical analyses were performed with Statis- tica software (v.13.1, StatSoft Inc.).

Descriptive sta- tistics are presented as mean ± SD unless otherwise indicated.

Statistical significance was assumed at a = 0.05.

Data distributions were tested using a Kol- mogorov-Smirnov test.

The hypothesis of normality was rejected for most of the analysed parameters; therefore, nonparametric tests were used.

To evalu- ate the differences between physiological param- eters at baseline before dexmedetomidine infusion (T0) and then 5, 10, 30, and 60 minutes (T5, T10, T30, T60, respectively) after beginning the dexme- detomidine infusion and 60 minutes after discon- tinuation of dexmedetomidine (Tpo), a Friedman nonparametric ANOVA test was applied.

Post-hoc analyses were performed using Wilcoxon signed- rank tests with Holm-Bonferroni corrections for multiple comparisons.

The Spearman rank correla- tion coefficient was used to examine the linear rela- tionships between BIS and RASS.


The group consisted of 16 men and 10 women, with a mean age of 51 ± 17 years (min 19 years, max 77 years).

The clinical characteristics of the patients are presented in Table 1.

The mean surgery time was 6 h 10 min ± 1 h 25 min.

The consumption of dexmedetomidine during the procedure was on average 711 ± 240 µg (min 400 µg, max 1200 µg).

The application of other drugs was marginal in the total group: propofol 36 ± 51 mg (max 150 mg), fen- tanyl 0.01 ± 0.03 mg (max 0.10 mg), and midazolam 0.08 ± 0.27 mg (max 1 mg).

No catecholamines were used intraoperatively.

Small doses of ephedrine were administered to 3 patients for transient blood pressure drops.

Significant (> 500 mL) intraopera- tive blood loss was noted in one patient (4%) with a large meningioma.


Intraoperative brain relaxation assessed using the modified Bristow scale was assessed as 2 points (a compliant brain within craniotomy edge) in 22 patients (84%), as 3 points (slightly tight brain, little above craniotomy edge) in 3 patients (12%), and as 4 points (tense brain, brain oedema, signifi- cantly above craniotomy edge) in one patient (4%).

Surgical conditions were excellent in 6 cases (23%), good in 16 cases (62%), and poor in 4 cases (15%; all with intraoperative epileptic episodes).


Intraoperative and postoperative complica- tions are presented in Table 2.

Intraoperative epi- leptic episodes were observed in 4 patients (15%).

The patients experienced generalized seizures caused by electrical stimulation of the motor cortex (EEG monitoring).

The seizures were observed in 31% of patients with an identified motor cortex.


The onset of seizures in 75% occurred during electrical stimu- lation of the cerebral cortex.

However, in one case, a generalized tonic-clonic seizure occurred during traction placed on brain tissue or the use of a Cavitron Ultrasonic Surgical Aspirator (CUSA).

All patients who experienced seizures during surgery presented tran- sient lower limb muscle force.

In one case, decreased consciousness without accompanying seizure was observed during motor cortex stimulation.


None of them showed sensory or speech disorders; however, no eloquent areas were identified in these patients.

In the event of a seizure, the surgical field was filled with ice-cold Ringer's solution, and in half of the cases, an additional 1 mg of clonazepam was administered intravenously, resulting in regression of convulsive activity and restoration of consciousness.


The following abnormalities were found on post- operative head CT (24 hours after surgery): haema- toma in 3 patients (12%) and venous stroke in one patient (4%).

No reoperation was needed.

Except for one ASA-4 patient, no patient required ICU observa- tion.

In this case, the patient had a severe chronic ob- structive pulmonary disease and pulmonary tumours compressing the aorta that required transfer to the ICU for 24 hours of observation.

Postoperative follow- up was good in all patients (including the ASA-4 case).

A death in the late postoperative period (7 th day after AC) was caused by a pulmonary embolism.


SAP, DAP, and MAP changed significantly during the analysed points in time (c 2 = 45.40, P < 0.001; c 2 = 33.56, P < 0.001; c 2 = 21.94, P < 0.001, respec- tively).

These alterations were within the clinically accepted range during the measurements and did not exceed 20% of the initial values.

SAP was lower at T30 (P = 0.001), T60 (P < 0.001), and Tpo (P < 0.001) vs. T0.

DAP decreased at T30 (P = 0.002), T60 (P < 0.001), and Tpo (P < 0.001) vs. T0.

MAP decreased at T60 (P = 0.001) vs. T0 (Figure 2A).

HR altered significantly at the analysed points of time (c 2 = 34.20, P < 0.001).

HR decreased at Tpo vs. T0 (P = 0.001) (Figure 2A).

Those changes were unim- portant (20% change from the initial value).


The saturation did not change significantly at the analysed points in time, and at no point in time was it less than 94%.

EtCO 2 did not change consid- erably during the analysed points of time.

PaCO 2 and PaO 2 increased over time (c 2 = 14.38, P = 0.002; c 2 = 9.70, P = 0.021); however, neither parameter


Most patients perceived AC as a positive (50%) or neutral (27%) experience (see 'Postoperative short psychological questionnaire' , question 1 and Figure 3).

18% of patients assessed AC as a negative experi- ence, and 6% of patients would not undergo awake surgery again (see 'Postoperative Short Psychologi- cal Questionnaire' , question 4).

The post operative interviews with patients showed that the greatest sources of discomfort and pain were clamping, op- erating position, limited field of vision, and staff be- haviour, which can lead to iatrogenic disorders.

Fac- tors that patients mentioned as a source of support (see 'Postoperative Short Psychological Question- naire' , Question 2) were as follows: extensive com- munication, a relaxed atmosphere, feedback from an operator (especially positive), attendance of a neu- rophysiologist and psychologist, and mental prepa- ration before operation by members of a specialized The mapping of the eloquent areas of the brain cortex was performed based on correct word articu- lation (aloud counting from 1 to 10) and the name of the presented images in 81% of the cases.

During the stimulation of the cerebral cortex, only 3 patients suffered speech deterioration.

Two of them had a mi- nor speech deficit of 1/2 intensity, and in one case, the speech deteriorated.

In this single case, partial resection of the left cingulate gyrus resulted in aki- netic mutism - speech disorder in grade 0/2, which improved after logopaedic therapy in the postopera- tive period.

Patients who had intraoperative seizure attacks did not show any speech disorders.


Intraoperative neurophysiological monitoring was performed in 96% of AC patients.

Electrical map- ping of the cerebral cortex allowed the identification of the motor cortex in 50% of patients and the sub- cortical structures in 12% of the cases.

Preoperatively, muscle force was 5/5 in 85% of patients and 4/5 in 2 patients, using the Lovett scale.

Unaltered muscle force was observed postoperatively in 88% of the pa- tients.


Postoperatively, one patient decreased from 5 to 4 on the Lovett scale and 2 others from 5 to 1.

Additionally, one patient with a score of 4/5 was tem- porarily paralyzed after surgery.

Sensory function measured after cortex or peripheral stimulation was evaluated in 62% of patients, and in 22% of cases the sensory cortex was successfully stimulated.

None of the operated patients reported quantitative or qualita- tive disturbances during surgery.


Brainstem auditory- evoked potentials were recorded in 15% of patients.

The latency and amplitude of peaks I-IV, II, III, and V, as well as the interpeak latency of I-III and III-V, were close to the initial values.

Of all patients eli- gible for AC, 73% had a previous diagnosis of epi- lepsy.

Suppressive treatment in 74% of the patients required an antiepileptic drug, and 26% required 2 different drugs.


AC is a technique developed for maximizing re- section while preserving neurological function [1].

Multiple studies have documented that CS based on low doses of dexmedetomidine, along with neuro monitoring, is a feasible approach [18-20].

Dexmedetomidine-based CS with a scalp block without instrumental airway support in conjunc- tion with psychologist support provides good qual- ity intraoperative sedation for AC, even during long surgical procedures requiring intraoperative mag- netic resonance imaging.


The protocol of anaes- thetic management proposed in this study allows one to achieve a good quality of analgesia while still maintaining sedation with fast recovery to full consciousness for neuropsychological monitoring after cessation of dexmedetomidine infusion.

It is comfortable and not too demanding for the pa- tient.

The clinical study showed that the anaesthe- tics used in this protocol did not significantly influ- ence cardiovascular and respiratory parameters.


Operative conditions were good according to the surgeon's opinion and the modified Bristow scale.

The quality of the monitored brain potentials, as well as neuropsychological monitoring, was satis- factory.

We did not observe symptoms of cough, nausea, vomiting, agitation, anxiety, brain swell- ing, or haemostatic disorders intraoperatively, as reported in the literature [18, 21].


Various anaesthetic management strategies for AC are being utilized; however, there are no clear recommendations [14].

Several authors have re- searched propofol-remifentanil and dexmedetomi- dine-based sedation, but only a few comparative studies have been performed [22-24].

Dexmedeto- midine has been reported to depress the cardio- vascular system by relaxing the autonomic system, increasing the risk of global or regional hypoper- fusion of the brain [25, 26].

However, in our study, no clinically significant influence on cardiovascular or respiratory parameters was observed.

SBP, DBP, MAP, and HR decreased significantly at T30 and T60 compared to initial values and continued at that level until 60 min after discontinuation of sedation.

It is noteworthy that these changes did not reach clinical significance.

Similar results were reported in another retrospective observation on a large cohort of patients, where the doses of dexmedetomidine used in that trial (up to 1.7 µg kg -1 h -1 ) were higher than what was proposed in this study [21].

However, due to the limited group of patients in our study, the impact of dexmedetomidine on the cardiovas- cular system requires further investigation.


We also marked that, except for one case, pa- tients were not admitted to the intensive care unit, due to stable immediate postoperative status.

Af- ter AC, patients were taken to a postoperative re- covery room for 2-3 hours and then transferred to the neurosurgery unit.

They were allowed to drink a few hours later.

The next day, they were mobilized after the completion of the postoperative head CT.

The duration of hospitalization was as short as 48 to 72 hours in 2 patients.

The remaining patients required longer hospitalizations due to neurologi- cal dysfunctions or fear of delayed new neurologi- cal complications and inadequate supervision after being sent home.

It is noteworthy that because of the short patient hospitalization after AC, the cost Bogusława Ewa Lechowicz-Głogowska, Agnieszka Uryga, Artur Weiser, et al. of the entire procedure would be greatly reduced compared to general anaesthesia [27, 28].


In this study protocol, a sedation level of -1/-3 on the RASS scale was maintained up to meningeal closure, and tests were frequently per- formed to warn the operator of possible white matter injury that could cause further emo- tional, memory, or character disorders [29].

The level of sedation was also monitored with BIS.

It is well documented that the RASS scale and BIS are correlated with the level of sedation [30, 31].

Such a correlation was also found in this study.

As reported previously [32], we did not observe a significant change in BIS values under seda- tion with dexmedetomidine RASS -1/-2, but we observed lower BIS values after a bolus of propo- fol and initiating deeper anaesthesia (RASS -3).

The time to achieve complete consciousness for a patient was 3-5 min (from RASS -1/-2), up to 10-13 min (RASS: -3) after stopping dexmedeto- midine, and is consistent with other research.

This study showed that RASS -2/-3, corresponding to BIS 98-50, is comfortable for the patient while al- lowing them to regain complete cooperativeness in a few minutes at any time during surgery to allow neuro and psychological evaluation.


The risk of seizures triggered by electrical brain stimulation is a common adverse event during brain mapping.

This study has shown that dexmedetomi- dine does not influence epileptiform discharges in EEG after IV infusion [33].

In cases without EEG, continuous free-running EMG recordings during the surgical removal procedure were successfully used to identify increased EMG activity and possible im- minent seizure.

The 15% incidence of intraoperative seizures experienced in our study was within the range described in the literature [34].

The seizures were predominantly caused by relatively high- intensity stimulation, which usually exceeds 10 mA despite the use of 50-Hz stimulation.

In 3 cases the seizures were generalized, and in one case it was a focal seizure, and all were stopped with irriga- tion with Ringer solution.

Half of the patients who experienced seizures had motor deterioration, but the motor functions of the remaining patients were stable despite preoperative weakness.


The quality of the monitored brain potentials did not change from the initial value.

It was pre- viously shown that appropriate dosing of dexme- detomidine is crucial to avoid its suppressive effect on motor function.

The motor function changes observed in our patients were a consequence of tumour removal manoeuvres rather than a direct pharmacological influence on cerebral blood flow that affected motor function [35].

Patients who regu larly performed simple and complex motor tasks to assess agility and muscle strength were well tolerated by them and did not alter the progress of the operation.

The results obtained from motor function monitoring were informative for the sur- geon and anaesthesiologist and consistent with the postoperative neurological achievements of the pa- tients [36].

Intraoperatively and postoperatively, all patients did not complain of sensory disturbance.


The indications for the use of CS for AC are in- creasing: all grade 1-2 WHO gliomas, basilar artery aneurysms, and other complex aneurysms, deep brain stimulation, cerebellopontine tumours, and pa- tients with complex comorbidities and obesity [29].

Furthermore, according to recent recommenda- tions, some of the patients included in this study would have been disqualified from using the AAA technique or any other type of CS for AC using pro- pofol, fentanyl, or remifentanil due to severe obe- sity, difficult airways, and severe respiratory and car- diovascular comorbidities due to an unacceptable increase in risks of severe intraoperative complica- tions.

Also, most anaesthetists would have excluded some of the surgical positions (park bench, sitting, prone) if a different type of sedation were used.

Pa- tients with severe comorbidities or obesity are the best candidates for the techniques presented in this study becuase many complications can be avoided.


Neuropsychological examination, which was not affected by dexmedetomidine, allowed efficient pro- tection of language and cognitive skills.

It was shown that dexmedetomidine did not block differentiation between congruent and incongruent language tasks based on the presence of N400 and is recommended during craniotomy [37].

It is worth mentioning that 50% of the patients had language disturbances before surgery, but only 30% of the electrical map- pings allowed the identification of cortical language epicentres.

After the operation, deterioration of the language was observed in 4 cases (15%).


The preoperative psychological evaluation was an important part of our study.

The patients in our study were evaluated by the psychologist not only before AC but also during the total procedure and 24-48 hours after AC.

The presence of a psycholo- gist during the whole procedure (in the operating room) is not a standard element of the procedure.

Previous studies have shown that hypnosis could be used successfully in the paediatric population dur- ing AC for the resection of brain tumours located close to eloquent areas [38] and during AC of low- grade gliomas [39].

Thus, we expected that, similarly to hypnosis, the presence of a psychologist would encourage patients to gain motivation and safety during AC and decrease the risk of conversion to general anaesthesia.

Our experience indicates that building patient trust and comfort can increase the chances of a positive patient experience during the long-lasting procedure and after hospital discharge.

The detailed psychological evaluation of patients in terms of early and late postoperative stress injury will be a matter of a separate report.


The age distribution in our group of patients was as follows: one case was < 20 years, 7 cases were between 20 and 40 years, 14 cases were between 40 and 65 years, and 4 cases were > 65 years.

The reac- tivity of sedative-analgesic agents could depend on age [40, 41].

However, the Kruskal-Wallis ANOVA test did not show significant differences in the total dose of dexmedetomidine (c2 = 2.65; P = 0.265), which is in line with other studies on the pharmacodynam- ics and pharmacokinetics of dexmedetomidine [42].


The anaesthetic protocol during AC is still under investigation.

Abazieu [43] reported that remifent- anil could be an independent risk factor for adverse events during AC.

Remifentanil can depress the re- spiratory centre in the brain and cause nausea and vomiting, leading to respiratory insufficiency, pro- longed hypoventilation, and conversion to general anaesthesia.

It should be noted that a combination of this opioid with propofol is generally recom- mended and used (including in the author's cen- tre) for the AAA protocol of anaesthesia [43].

This sedation procedure probably should be questioned, especially if we recognize that already impaired neuronal function in operated patients, due to any further imbalance, might be irreversibly damaged.

It has been shown that in older patients anaesthetized with remifentanil and propofol, there were higher incidences of cognitive deterioration.

Such mental disorders were not observed in patients sedated with dexmedetomidine and propofol [44].

Further- more, the other authors underlined the negative impact of propofol on cognitive functions, which can mask real neuronal dysfunction and cognitive impairment that must be minimized during AC [45].


This observational clinical study has limitations.

The procedures performed were long (about 5 hours on average), which can affect the patient's comfort.

However, dexmedetomidine-based sedation led to physiologically similar sleep with immediate "on- demand" arousal.

Other studies on dexmedetomi- dine sedation have analysed much shorter proce- dures in retrospective research, which could have an impact on the conclusions [25].


Secondly, we only analysed clinical parameters a few moments from the start of dexmedetomidine infusion to 60 minutes after infusion.

However, we noticed that all monitored parameters were stable from T60 until the end of the surgery.


Third, although anaes- thetic management was similar for all analysed pa- tients, some subjects required a bolus of propofol or mida zolam during head closure to maintain pa- tient comfort.

The synergistic effect of these chosen supplements deepens anaesthesia without the risk of adverse events.

In addition, the relaxation of the brain and the operative conditions were based on the observation of an experienced neurosurgeon.

The modified Bristow scale seems to be a suitable tool to access for brain relaxation assessment, but it is subjective.


Lastly, the character of this study was prospective without a control group.

However, the lack of adequate control was not perceived as a major deficiency in the study design.

This research has been designed as uncontrolled due to previous experiences in the AAA procedure that propofol and opioid sedation led to respiratory depression, uncon- trolled movements, poor arousal quality, long recov- ery to cooperative consciousness, and high risk of re- spiratory complications during AC.

Furthermore, the number of patients who met the inclusion criteria for AC was minimal at that time in our centre.

Given these limitations, a multicentre study with a control group would provide more reliable data and improve the generalizability of these observations.


CS with dexmedetomidine and scalp block can provide a safe and comfortable anaesthesia pro- cedure during AC for the surgeon and the patient.

It allows the implementation of advanced, multi- level intellectual tests, where perioperative psycho- logical support plays an important role.

Smooth in- duction and arousal with a cooperative patient are possible with the presented anaesthetic method, even during long-lasting procedures (5-6 hours).

Further observations and comparative trials are needed to conclude the best anaesthetic protocol for AC procedures.


Dear Editor, We read with great interest the recent study “Awake craniotomy with dexmedetomidine during resection of brain tumours located in eloquent regions” presented by Lechowicz-Głogowska et al. [ 1] and the method used to perform awake craniotomy (AC) in the authors’ centre.

Although AC is considered as a gold standard of management during resection of intra-axial lesions in proximity to eloquent cortical and subcortical regions, until now a uniform consensus on anaesthetic management has not been established, as the authors rightly pointed out.

Therefore, we would like to acknowledge and congratulate the authors for their effort to perform the study on such an interesting and still uncommonly used anaesthetic technique.

Proper selection of patients for elective AC in conscious sedation (CS) is a key factor determining the success of the whole procedure.

After reading the article we would like to raise a few issues concerning selection criteria and the standard of the AC procedure presented by the authors which need clarification.