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The importance of temporal expectation for sensory perception has been demonstrated across diverse paradigms and multiple modalities. Overall, the findings are consistent: temporal expectation results in greater encoding precision, higher perceptual sensitivity, and decreased response times during
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Periodicity versus Prediction in Sensory Perception
XVani G. Rajendran and XSundeep Teki
Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford OX1 3PT, United Kingdom
Review of Morillon et al.
The importance of temporal expectation for
sensory perception has been demonstrated
across diverse paradigms and multiple mo-
dalities. Overall, the findings are consistent:
temporal expectation results in greater en-
coding precision, higher perceptual sensi-
tivity, and decreased response times during
behavioral tasks. Temporal expectation it-
self can take several forms. “Controlled” ex-
pectation arises when a symbolic cue
indicates that a stimulus will occur at a par-
ticular time in the future (Rohenkohl et al.,
2012). Temporal expectations also arise
through rhythmic sensory stimulation
(McAuley and Jones, 2003). Finally, a form
of “automatic” temporal expectation builds
up over time if a sensory event is expected
but precisely when it will occur is unknown
(Nobre et al., 2007).
By designing a task that explores the
space between symbolic and rhythmic ex-
pectations, Morillon et al. (2016) investi-
gated whether the advantages conferred
by temporal expectation, specifically the
enhancement of perceptual sensitivity
and facilitation of motor responses, arise
as a result of temporal prediction in gen-
eral, or are specific to periodic stimula-
tion. In their first experiment, stimulus
sequences consisted of 12 “target tones”
(six 880 Hz deviants, six 440 Hz stan-
dards) embedded pseudorandomly every
1.5– 6 s in a stream of 440 Hz “reference
tones,” and listeners were tasked with
identifying deviant target tones. Tone se-
quences were embedded in continuous
white noise and presented in three differ-
ent temporal contexts. In the periodic
predictable (PP) context, tone onsets were
equally spaced at one of five chosen values
of stimulus-onset asynchrony (SOA; 255,
290, 345, 445, 770 ms). In the aperiodic
predictable (AP) condition, the five SOAs
were arranged ordinally such that they al-
ternated between progressively increasing
and decreasing intervals. Listeners could
therefore exploit the pattern of time inter-
vals to form temporal predictions about
the onset of the next tone even though the
stream of tones itself was not isochron-
ous. Finally, in an aperiodic unpredictable
(AU) condition, SOAs were chosen in a
pseudorandom manner. Visual cues pre-
sented simultaneously on a gray back-
ground informed participants whether a
given sound was a reference (white cross;
92% of the time) or a target (red circle;
8% of the time).
The authors found that performance,
as measured by d(a criterion-free mea-
sure of perceptual sensitivity derived
from signal detection theory), did not
differ significantly between the two pre-
dictable conditions (PP and AP), but
was worse in the unpredictable condi-
tion (AU). In contrast, reaction times
were fastest in the periodic condition
(PP), and were not significantly differ-
ent between the two aperiodic condi-
tions (AP and AU).
The expectations manipulated in this
experiment were purely temporal, and the
authors went one step further in a second
experiment to examine the main effects
and possible interactions between pre-
dictability of temporal and spectral, or
frequency-based, features. In this para-
digm, reference and target stimuli were
bursts of colored (either blue or pink)
noise, and listeners were tasked with de-
tecting a pure tone (“target tone”) on half
of the target stimuli (“target noise”). Col-
ored noises had symmetrical 1/f power
density spectra that either increased
(blue) or decreased (pink) by 3 dB per oc-
tave and intersected at 2027 Hz, the fre-
quency of the target tone. The authors
manipulated temporal (T) and spectral
(S) predictability in a balanced factorial
paradigm (T
where and denote predictable and
unpredictable conditions, respectively).
In T
conditions, SOA was fixed at 400
ms, and in T
conditions, SOA was drawn
pseudorandomly from one of five possible
values (200, 300, 400, 500, 600 ms). Refer-
ence and target noises were identical in the
context, and of contrasting colors in
. The same visual cues described previ-
ously indicated whether a given noise was
a reference (87.5% of the time) or a target
(12.5% of the time).
Consistent with their results from Ex-
periment 1, the authors found that peri-
odic stimulation (T
) yielded faster
reaction times. In addition, they showed
that this was the case regardless of whether
target and reference noises were of the
same color (S
or S
). In contrast, audi-
tory sensitivity was facilitated only by
Received April 22, 2016; revised June 1, 2016; accepted June 6, 2016.
This work was supported by the Wellcome Trust to V.G.R.
(WT099750MA;WellcomeTrust Doctoral Programmein Neuroscience) and
S.T. (WT106084/Z/14/Z; Sir Henry Wellcome Postdoctoral Fellowship).
The authors declare no competing financial interests.
Correspondence should be addressed to either Vani G. Rajendran or
Sundeep Teki, Department of Physiology, Anatomy and Genetics, Uni-
versity of Oxford, South Parks Road, Oxford OX1 3PT, UK. E-mail: or
Copyright © 2016 the authors 0270-6474/16/367343-03$15.00/0
The Journal of Neuroscience, July 13, 2016 36(28):7343–7345 • 7343
periodic stimulation (T
) if target noises
were also spectrally predictable (S
Spectral unpredictability (S
) impaired
auditory sensitivity regardless of temporal
predictability (T
or T
The major contribution made by this
study is the behavioral dissociation be-
tween response speed and perceptual acu-
ity, the former resulting from periodic
stimulation only, and the latter from tem-
poral expectation more generally. The im-
plications of these findings are potentially
far-reaching and will be discussed below,
but first it is worth noting a few method-
ological issues. First, the major finding of
the double dissociation could have been
even more compelling if Experiment 2
had included an AP condition because, as
it stands, the Tcondition here is both
predictable and periodic. This under-
scores a more general issue that the results
from Experiments 1 and 2 are difficult to
compare directly, their paradigms differ-
ing to the point that one could consider
Experiment 1 a deviant “detection” task
(detecting an 880 Hz deviant tone in a
stream of 440 Hz standard tones) and
Experiment 2 a “discrimination” task
(discriminating a 2027 Hz target tone in
target-colored noise). An alternative par-
adigm using a common stimulus and task
ina23 factorial design with two kinds
of predictions (temporal and spectral)
and three levels of predictability (PP, AP,
and AU for both features) could have
yielded more clearly interpretable main
effects and interactions. Finally, the justi-
fication for using an audiovisual task with
visual cues for the target is unclear, and
somewhat muddles the interpretation of
the results because the two modalities
might contribute differentially to the
formation of the temporal expectations
probed in this study.
These methodological criticisms
aside, the effects reported, though rela-
tively small, are significant and imply
that temporal expectation through
periodic stimulation affects motor
preparation in a way that other forms of
temporal expectation do not. The role of
motor regions in rhythmic timing is well
established (Grahn and Brett, 2007).
Specifically, functional imaging stud-
ies have shown that striato-thalamo-
cortical areas are more active during
temporally regular sequences, whereas
olivocerebellar circuits are more
strongly activated during irregular se-
quences (Teki et al., 2011,2012). This is
consistent with neurophysiological re-
cordings that have identified beta-band
oscillations in the striatum as a putative
marker for temporal regularity (Bartolo
et al., 2014). Striatal beta activity repre-
sents a general sequence-initiation sig-
nal but persists subsequently only for
regular sequences and is suppressed for
irregular ones (Bartolo and Merchant,
2015). An open question is whether the
motor system is recruited only when
sensory stimuli are strictly periodic.
Though Morillon et al. (2016) show no
motor facilitation in the aperiodic pre-
dictable condition, they chose a form of
aperiodicity that is also arrhythmic. An
interesting follow-up experiment would
be to explore rhythmic (but aperiodic)
patterns, such as those used by Nozara-
dan et al. (2011), which have been
shown to entrain cortical activity, but
whose interaction with the motor sys-
tem is not fully understood.
In Experiment 2, a possible neural
mechanism for the establishment of spec-
tral predictions at the sensory level that
was not particularly emphasized in the
current study is stimulus-specific adapta-
tion (SSA), which manifests as a suppres-
sion of neural responses to a repeated
stimulus (Ulanovsky et al., 2003,2004).
SSA represents a potential single-neuron
correlate of the mismatch negativity and
refers to the observation that neural re-
sponses are typically stronger for “devi-
ant” (ie, relatively rare or unexpected)
acoustic events than for commonly oc-
curring and therefore highly predic-
table “standard” events (for review, see
Näätänen et al., 2007;Nelken and
Ulanovsky, 2007). In Experiment 2, the
target tone in the S
context is a clear de-
viant, potentially evoking a strong mis-
match signal. In the S
context, however,
the color of the noise potentially repre-
sents the most salient deviant, which
could have masked the target tone and re-
sulted in the lower dobserved. Thus, SSA
could possibly account for why spectral
predictability enhanced perceptual sensi-
tivity in the S
context relative to S
. The
formation of spectral predictions may
therefore be explained by neural adapta-
tion, a process that may or may not inter-
act with the formation of temporal
predictions through oscillatory entrain-
ment or active sensing mechanisms dis-
cussed below.
Of special note is the authors’ finding
that perceptual sensitivity in the spectrally
predictable context is further facilitated
by periodic stimulation, despite the ob-
served dissociation between perceptual
acuity and response speed. The authors
interpret this result as suggestive of a
hierarchy of predictive filters in sensory
cortices where predictions about “what”
will occur supersede predictions about
“when” something will occur, suggesting
that “what” and “when” predictions inter-
act to shape perception. Indeed the sup-
pression of neural activity in response to
repeated sounds is strongest when the
sounds occur at regular intervals (Costa-
Faidella et al., 2011). Furthermore, the ac-
tivation of a periodicity detector model
based on low-frequency modulation fil-
ters correlates strongly with perceptual
acuity in temporally jittered sequences
(Rajendran et al., 2016). These observa-
tions are consistent with findings that
entrainment of low-frequency delta oscil-
lations to the temporal structure of an at-
tended stimulus can boost perceptual
sensitivity (Lakatos et al., 2008;Schroeder
and Lakatos, 2009), and furthermore sug-
gest that such response gain might require
that elements of the attended stimulus
(“what”) be spectrally predictable.
The neural substrates underlying
“what” and “when” predictions are not
yet fully understood, but the present
findings are consistent with the prevail-
ing idea that the motor system interacts
with sensory circuits, possibly via cross-
frequency coupling between delta and
beta oscillations, to modulate temporal
predictions for adaptive behavior (Ar-
nal et al., 2015). The authors suggest a
model of active sensing, whereby overt
or covert motor signals may be used to
predictively improve sensory processing
in time (Morillon et al., 2015). This
model is similar to the Action Simula-
tion for Auditory Prediction hypothesis
(Patel and Iversen, 2014), which pro-
poses that simulation of rhythmic
movement in motor planning regions
helps the auditory system predict the
timing of an upcoming musical beat.
The findings by Morillon et al. (2016)
and the aforementioned mechanistic
hypotheses may furthermore relate to
studies probing how sensorimotor cir-
cuits encode temporal structure in
speech and music through rhythmic os-
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Rajendran and Teki Journal Club J. Neurosci., July 13, 2016 36(28):7343–7345 • 7345
... It is worth noting, however, that by design these studies look at differences in predictions of not only ''when" an auditory event is expected, but also ''what" that auditory event should be (Teki and Kononowicz, 2016). Behavioral evidence suggests that these two types of predictions may have distinct neural substrates (Morillon et al., 2016;Rajendran and Teki, 2016), and it is therefore not yet possible to say whether pre-attentive responses are a result of temporal expectation alone or a combination of expectations of ''what" and ''when" (Arnal, 2012;Arnal and Giraud, 2012;Schwartze et al., 2013). ...
... It is worth noting that the rhythmic form of temporal expectation is just one of several forms of temporal expectation, each resulting in subtle differences in perception that may arise from differences in the underlying neural substrates (Nobre et al., 2007;Breska and Deouell, 2017). For example, an enhancement of perceptual sensitivity has been demonstrated in both periodic and non periodic sequences that are temporally predictable, but motor facilitation through faster response latencies were only observed in the periodic condition (Morillon et al., 2016;Rajendran and Teki, 2016). ...
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Music is a curious example of a temporally patterned acoustic stimulus, and a compelling pan-cultural phenomenon. This review strives to bring some insights from decades of music psychology and sensorimotor synchronization (SMS) literature into the mainstream auditory domain, arguing that musical rhythm perception is shaped in important ways by temporal processing mechanisms in the brain. The feature that unites these disparate disciplines is an appreciation of the central importance of timing, sequencing, and anticipation. Perception of musical rhythms relies on an ability to form temporal predictions, a general feature of temporal processing that is equally relevant to auditory scene analysis, pattern detection, and speech perception. By bringing together findings from the music and auditory literature, we hope to inspire researchers to look beyond the conventions of their respective fields and consider the cross-disciplinary implications of studying auditory temporal sequence processing. We begin by highlighting music as an interesting sound stimulus that may provide clues to how temporal patterning in sound drives perception. Next, we review the SMS literature and discuss possible neural substrates for the perception of, and synchronization to, musical beat. We then move away from music to explore the perceptual effects of rhythmic timing in pattern detection, auditory scene analysis, and speech perception. Finally, we review the neurophysiology of general timing processes that may underlie aspects of the perception of rhythmic patterns. We conclude with a brief summary and outlook for future research.
Recording direct neural activity when periodically inserting exemplars of a particular category in a rapid visual stream of other objects offers an objective and efficient way to quantify perceptual categorization and characterize its spatiotemporal dynamics. However, since periodicity entails predictability, perceptual categorization processes identified within this framework may be partly generated or modulated by temporal expectations. Here we present a stringent test of the hypothesis that temporal predictability generates or modulates category-selective neural processes as measured in a rapid periodic visual stimulation stream. In Experiment 1, we compare neurophysiological responses to periodic and nonperiodic (i.e., unpredictable) variable face stimuli in a fast (12 Hz) visual stream of nonface objects. In Experiment 2, we assess potential responses to rare (10%) omissions of periodic face events (i.e., violations of periodicity) in the same fast visual stream. Overall, our observations indicate that category(face)-selective processes elicited in a fast periodic stream of visual objects are immune to temporal predictability. These observations do not support a predictive coding framework interpretation of category-change detection in the human brain and have important implications for understanding automatic human perceptual categorization in a rapidly changing (i.e., dynamic) visual scene.
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Predicting not only what will happen, but also when it will happen is extremely helpful for optimizing perception and action. Temporal predictions driven by periodic stimulation increase perceptual sensitivity and reduce response latencies. At the neurophysiological level, a single mechanism has been proposed to mediate this twofold behavioral improvement: the rhythmic entrainment of slow cortical oscillations to the stimulation rate. However, temporal regularities can occur in aperiodic contexts, suggesting that temporal predictions per se may be dissociable from entrainment to periodic sensory streams. We investigated this possibility in two behavioral experiments, asking human participants to detect near-threshold auditory tones embedded in streams whose temporal and spectral properties were manipulated. While our findings confirm that periodic stimulation reduces response latencies, in agreement with the hypothesis of a stimulus-driven entrainment of neural excitability, they further reveal that this motor facilitation can be dissociated from the enhancement of auditory sensitivity. Perceptual sensitivity improvement is unaffected by the nature of temporal regularities (periodic vs aperiodic), but contingent on the co-occurrence of a fulfilled spectral prediction. Altogether, the dissociation between predictability and periodicity demonstrates that distinct mechanisms flexibly and synergistically operate to facilitate perception and action.
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This study investigates the influence of temporal regularity on human listeners’ ability to detect a repeating noise pattern embedded in statistically identical non-repeating noise. Human listeners were presented with white noise stimuli that either contained a frozen segment of noise that repeated in a temporally regular or irregular manner, or did not contain any repetition at all. Subjects were instructed to respond as soon as they detected any repetition in the stimulus. Pattern detection performance was best when repeated targets occurred in a temporally regular manner, suggesting that temporal regularity plays a facilitative role in pattern detection. A modulation filterbank model could account for these results.
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β oscillations in the basal ganglia have been associated with interval timing. We recorded the putaminal local field potentials (LFPs) from monkeys performing a synchronization-continuation task (SCT) and a serial reaction-time task (RTT), where the animals produced regularly and irregularly paced tapping sequences, respectively. We compared the activation profile of β oscillations between tasks and found transient bursts of β activity in both the RTT and SCT. During the RTT, β power was higher at the beginning of the task, especially when LFPs were aligned to the stimuli. During the SCT, β was higher during the internally driven continuation phase, especially for tap-aligned LFPs. Interestingly, a set of LFPs showed an initial burst of β at the beginning of the SCT, similar to the RTT, followed by a decrease in β oscillations during the synchronization phase, to finally rebound during the continuation phase. The rebound during the continuation phase of the SCT suggests that the corticostriatal circuit is involved in the control of internally driven motor sequences. In turn, the transient bursts of β activity at the beginning of both tasks suggest that the basal ganglia produce a general initiation signal that engages the motor system in different sequential behaviors. Copyright © 2015 the authors 0270-6474/15/354635-06$15.00/0.
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Humans possess an ability to perceive and synchronize movements to the beat in music ('beat perception and synchronization'), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia-thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization-continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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The ability to generate temporal predictions is fundamental for adaptive behavior. Precise timing at the time-scale of seconds is critical, for instance to predict trajectories or to select relevant information. What mechanisms form the basis for such accurate timing? Recent evidence suggests that (1) temporal predictions adjust sensory selection by controlling neural oscillations in time and (2) the motor system plays an active role in inferring “when” events will happen. We hypothesized that oscillations in the delta and beta bands are instrumental in predicting the occurrence of auditory targets. Participants listened to brief rhythmic tone sequences and detected target delays while undergoing magnetoencephalography recording. Prior to target occurrence, we found that coupled delta (1–3 Hz) and beta (18–22 Hz) oscillations temporally align with upcoming targets and bias decisions towards correct responses, suggesting that delta–beta coupled oscillations underpin prediction accuracy. Subsequent to target occurrence, subjects update their decisions using the magnitude of the alpha-band (10–14 Hz) response as internal evidence of target timing. These data support a model in which the orchestration of oscillatory dynamics between sensory and motor systems is exploited to accurately select sensory information in time.
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Every human culture has some form of music with a beat: a perceived periodic pulse that structures the perception of musical rhythm and which serves as a framework for synchronized movement to music. What are the neural mechanisms of musical beat perception, and how did they evolve? One view, which dates back to Darwin and implicitly informs some current models of beat perception, is that the relevant neural mechanisms are relatively general and are widespread among animal species. On the basis of recent neural and cross-species data on musical beat processing, this paper argues for a different view. Here we argue that beat perception is a complex brain function involving temporally-precise communication between auditory regions and motor planning regions of the cortex (even in the absence of overt movement). More specifically, we propose that simulation of periodic movement in motor planning regions provides a neural signal that helps the auditory system predict the timing of upcoming beats. This "action simulation for auditory prediction" (ASAP) hypothesis leads to testable predictions. We further suggest that ASAP relies on dorsal auditory pathway connections between auditory regions and motor planning regions via the parietal cortex, and suggest that these connections may be stronger in humans than in non-human primates due to the evolution of vocal learning in our lineage. This suggestion motivates cross-species research to determine which species are capable of human-like beat perception, i.e., beat perception that involves accurate temporal prediction of beat times across a fairly broad range of tempi.
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Gamma (γ) and beta (β) oscillations seem to play complementary functions in the cortico-basal ganglia-thalamo-cortical circuit (CBGT) during motor behavior. We investigated the time-varying changes of the putaminal spiking activity and the spectral power of local field potentials (LFPs) during a task where the rhythmic tapping of monkeys was guided by isochronous stimuli separated by a fixed duration (synchronization phase), followed by a period of internally timed movements (continuation phase). We found that the power of both bands and the discharge rate of cells showed an orderly change in magnitude as a function of the duration and/or the serial order of the intervals executed rhythmically. More LFPs were tuned to duration and/or serial order in the β- than the γ-band, although different values of preferred features were represented by single cells and by both bands. Importantly, in the LFPs tuned to serial order, there was a strong bias toward the continuation phase for the β-band when aligned to movements, and a bias toward the synchronization phase for the γ-band when aligned to the stimuli. Our results suggest that γ-oscillations reflect local computations associated with stimulus processing, whereas β-activity involves the entrainment of large putaminal circuits, probably in conjunction with other elements of CBGT, during internally driven rhythmic tapping.
Animal models of MMN may serve both to further our understanding of neural processing beyond pure sensory coding and for unraveling the neural and pharmacological processes involved in the generation of MMN. We start this review by discussing the methodological issues that are especially important when pursuing a single-neuron correlate of MMN. Correlates of MMN have been studied in mice, rats, cats, and primates. Whereas essentially all of these studies demonstrated the presence of stimulus-specific adaptation, in the sense that responses to deviant tones are larger than the responses to standard tones, the presence of real MMN has been established only in a few. We argue for the use of more and better controls in order to clarify the situation. Finally, we discuss in detail the relationships between stimulus-specific adaptation of single-neuron responses, as established in the cat auditory cortex, and MMN. We argue that this is currently the only fully established correlate of true change detection, and hypothesize that it precedes and probably induces the neural activity that is eventually measured as MMN.