When a series of items is held in working memory, not all items are held with equal fidelity. Items early in the sequence may be forgotten, whereas items at the very start of a sequence may be easier to find. The final item in a sequence may also be held in a more “active,” privileged or prioritized state (Allen et al., 2014; Hu et al., 2016). This is known as the “recency effect,” and has been shown to be volatile, susceptible to a number of attentional manipulations (Davelaar et al., 2005; Hu et al., 2014). It decays quickly (Postman and Phillips, 1965; LaRocque et al., 2014), may be selectively impaired by TMS or lesions to modality-specific cortex (Vallar and Papagno, 1986; Zokaei et al., 2014a), and may relate to earlier items being forgotten through retroactive interference (Kool et al., 2014). For these reasons, it has been postulated that the benefits enjoyed by the final item in a sequence arise because it remains in the focus of attention.

Recent studies of working memory have begun to use continuous recall measures, which allow the precision or fidelity with which items are stored to be quantified. Most of these studies have used visual working memory, measuring the precision of storing spatial locations, colors or orientations (Bays and Husain, 2008; Zhang and Luck, 2008). These paradigms require participants to reproduce their memory of a continuously variable feature, for example by adjusting a dial. The reported feature can then be compared to the veridical feature, providing a trial-wise, quantitative precision measure. Recently, these precision paradigms have been extended to auditory and vibrotactile frequencies, and similar effects have been demonstrated, indicating that features in various modalities may all be encoded in a similar way (Kumar et al., 2013; Joseph et al., 2015). In neural models of working memory, the ability to hold several continuous features in memory has been taken to suggest that the feature dimensions are encoded in a set of independent feature-tuned channels, which are activated upon encoding each feature for each item in memory (Compte et al., 2000; Wimmer et al., 2014).

Could a similar storage method be used to hold temporal durations in memory? Periods of time are abstract: durations do not traditionally form a parameterised space represented by cells in sensory transduction. Intervals of time might need to be explicitly extracted or inferred from other kinds of representation (Matthews and Meck, 2016). Durations are also unusual things to hold in short-term memory. Despite this, it appears that we do in fact possess working memory for durations (Teki and Griffiths, 2014). Indeed we are able to repeat rhythms that we hear, for example in music, poetry or speech (McAuley, 2010). But it is not clear that the same mechanisms would be involved, as those that subserve visual or verbal working memory. The presence of set-size, serial position, and attentional effects could provide evidence for commonality of mechanisms.

Human time perception has been most commonly studied with simple interval estimation, reproduction and comparison tasks (Grondin, 2010). A number of factors increase or decrease the perceived duration of an interval. Practice can lengthen perceived durations (Eisler, 1976), as can arousal (Wittmann, 2013), whereas aging shortens them (Baudouin et al., 2006b). Attention and expectation play particularly important roles in interval timing. Attentional loads shorten perceived durations while they are experienced (Brown, 1985, 1997; Block et al., 2010) but lengthen the reproduction of durations (Fortin and Breton, 1995; Baudouin et al., 2006a,b). Evidence from patients also implicates attention in timing, with patients reporting shorter and less accurate estimates of durations (Danckert et al., 2007). We therefore studied whether attentional demands might alter retention of durations in working memory, by introducing variation of an irrelevant feature.

Importantly, expectation also impacts on timing. The presence of distractors during a time judgment task can lengthen the subjective duration of a stimulus, but this effect only arises when the distractors are unexpected (Penney et al., 2014). Similarly, producing an interval that is interrupted by a pause late in the interval leads to overestimation; this effect persisted on trials when a break did not actually occur, but was expected to occur (Fortin and Massé, 2000). These results suggest that expectation of an upcoming event shortens perceived durations. In the present study we investigate whether simply expecting an event could enhance memory retention for durations.

We set out to test a direct analog of visual working memory experiments, in the time domain. In particular we asked, does memory for durations show similar set-size and serial position effects as visual working memory? Further, we enquired whether set-size and serial position effects are susceptible to manipulation of attention and expectation. We asked whether the need to filter irrelevant information, and the expectation of the end of a sequence, altered the recency effect. We hypothesized that any attentional benefits would be attenuated if irrelevant features were being ignored. Regarding temporal expectation, we predicted that the unexpected end of a sequence can confer a recency benefit, whereas if the ends of sequences were expected, this advantage would be lost.

Participants were instructed to listen to each sequence of tones, and remember the time each one lasted for. They were told that after a delay, they would see a signal indicating which of the items in the sequence they had to recall (probed by serial order), and that they had to press and hold a key to try and match that duration as precisely as they could (Figure 1A).

Participants sat in a dimly lit room viewing a CRT monitor at a distance of 40 cm from a chinrest. Tones were presented through a pair of stereo speakers, situated either side of the computer screen 50 cm in front of the subjects, at shoulder height. Tones comprised a sine wave at 440 Hz (Experiments 1 and 3). Each tone was modulated to taper linearly over the first and last 10 ms, to minimize transients. The durations to be remembered were selected from a uniform distribution between 200 and 2000 ms. Sequences of 1 to 5 durations (Experiment 1) or 1 to 4 durations (Experiments 2 and 3) were chosen, with proportionally more trials for higher set-sizes. This permitted each serial position in each set-size to be probed equally frequently. The tones were separated by a fixed 500 ms inter-stimulus interval. After the end of the final tone, there was a 1000 ms silent retention interval.

At the end of the retention interval, the computer screen displayed a cue indicating which item was to be recalled. This was done graphically by displaying a row of squares, each representing one of the items heard on the current trial, in sequential order from left to right. One square was filled in, indicating the item that had to be recalled. For example, if four tones were heard, there would be four boxes, and to indicate that the first tone should be recalled, the left-most square was filled in white, whereas the other three were hollow frames.

Participants then pressed and released the key, to indicate their memory of the duration of the indicated tone. After the response, an inter-trial interval of 500 ms followed, and the next trial began. No feedback was provided.

In all experiments, 10 practice trials were performed, and participants were debriefed to check they understood the task, before the experiment began.

This study asked whether memory for a sequence short auditory durations follows well-known laws associated with working memory in other modalities. The results confirm the existence of set-size and serial position effects that are in line with other modalities (Figure 1D). We then asked whether attention and expectation could modulate memory for durations. When a variable irrelevant feature was introduced into the sequences, memory for single items was worse, suggesting that the high performance normally observed for single items may be susceptible to attentional disruption (Figure 2C). When the number of items was expected, we found a similar disruption of the ability to recall a single item in memory. Thus single items are best remembered when they are unexpectedly the only item (Figure 3C). The benefit of having to remember one item, rather than a sequence is thus disrupted by the presence of irrelevant information, but enhanced when more items in the sequence are expected.

One possible interpretation of these findings is that both filtering and expectation interfere with a common aspect of the maintenance of singular items. Could the benefits for single items be mediated by an attentional focus, conferring more mnemonic resources on an item that is isolated? In attentional focus models, some items in memory are held in a “privileged” state (Oberauer, 2002; Cowan, 2011). If multiple items are held in working memory, not all items are recalled with the same accuracy, and some of the differences between items may arise because of a privileged or attended state conferred to one item (Lewis-Peacock et al., 2012; Postle, 2015). The benefit can be transferred among items (Zokaei et al., 2014b), and may explain the susceptibility of recency effects to attentional manipulations (Öztekin et al., 2010; Morrison et al., 2014; Souza et al., 2016). Our findings add weight to suggestions that working memory may contain one high-resolution but volatile representation. However, it is notable that we did not find attentional disruptions for the last item of longer sequences. This suggests that the recency effect might not always be susceptible to attentional load or expectation.

There may be other, more complex reasons for the disruption by expectation and filtering. Eye movements may distort time perception (Morrone et al., 2005; Burr et al., 2010) and thus the cue preceding the stimulus might alter time perception. Another possibility is that expectation of an event (e.g., further items that might be presented) can increase perceived durations (Fortin and Massé, 2000; Penney et al., 2014). Alternatively, a dual-task effect might occur in the filtering condition, which is known to shorten perceived durations of stimuli (Block et al., 2010). In Experiment 3 pitch differences between notes may also increase the perceived duration of gaps between tones (Crowder and Neath, 1995; Lake et al., 2014).

However, all these effects would be expected to lead to distortions of perception and thus systematic biases to over- or under-estimate the duration. In contrast, our results suggested no bias but an increase in error, i.e., the variability of responses around the same fixed duration. This might suggest that the measured effects occur at encoding or storage, rather than being perceptual biases. Could focusing attention explain the results of experiments 2 and 3?

An important property of attention is its refractoriness, as characterized by attentional blink or inhibition of return. These phenomena impose temporal capacity limits on deployment of attention to sequentially presented items. Could the set-size cue itself capture attention in experiment 3, and impair encoding of the subsequent tone? We think this is a less likely explanation, because the attentional blink tends to arise between 150 and 450 ms after a stimulus (Shapiro et al., 1997), whereas the gaps in our task were 500 ms. Further, this might also be expected to slow down RTs, whereas we in fact observed faster RTs. We suggest an alternative explanation: when the recall cue is expected after the item, the preparation of the response begins as soon as the tone ends. Note that such immediate response preparation cannot occur in any other type of trial, because either the item-to-be-probed is unknown, or the end of the sequence is not expected. Early response preparation could be the factor that leads to disruption of duration memory.

The present study is one of few that examine working memory for durations that are not intrinsically rhythmic. Most studies that investigate memory for multiple durations test our ability to discriminate rhythms, i.e., sequences of durations that are integer multiples of a discrete, quantised beat (Penhune et al., 1998; Teki et al., 2011; Grahn, 2012b). Such studies do demonstrate limitations in the number of durations that can be remembered, but give no indication of the precision with which each duration is remembered. Rhythm discrimination may in fact predispose subjects to use discrete categorical strategies for representing time, whereas for non-rhythmic time sequences, different neural mechanisms are thought to be recruited (Grahn and Brett, 2007; Grube et al., 2010; Joseph et al., 2016).

It is possible that in our task, durations could either be encoded individually, as absolute time intervals, or as relative times approximating a rhythmic structure. The present study is not able to distinguish these two possibilities. Rhythm perception involuntarily leads to complex changes in perceived intensity and timing, which vary according to expertise (Povel and Essens, 1985). Perceiving rhythm also leads to phase-dependent facilitation for many aspects of auditory perception and cognition (McAuley, 2010; Grahn, 2012a). Expecting further items in a sequence (Experiment 3) could potentially promote adoption of a rhythmic strategy, and this strategic change might drive the improvements observed with expectation. Rhythm-perceptual effects may be overlaid upon working memory effects, and could lead to more efficient storage of intervals at the expense of precision (Jones and Ralston, 1991; Large, 2002), similar to “lossy compression” or configural effects observed in visual memory (Alvarez, 2011). Further study would be required to directly measure the effect of rhythm-based encoding on duration memory.

We cannot exclude that our findings might be specific to the auditory modality, rather than representing a general effect in temporal cognition. The duration of auditory stimuli are generally reproduced more precisely than visual stimuli, with sounds being perceived as lasting around 20% longer than lights of matched duration (Goldstone and Lhamon, 1974; Wearden et al., 2006; McAuley and Henry, 2010). As we were primarily interested in the precision of memory, we used auditory stimuli for this experiment. Moreover, we tested temporal memory using “filled durations” – i.e., a tone lasting for the desired duration, as opposed to a gap in a tone, or the interval between a pair of clicks delineating an “unfilled” interval. The use of tones minimizes bias caused by start and end markers themselves (Rammsayer and Leutner, 1996), and produces more precise interval reproduction than the duration of gaps, whose durations tend to be systematically underestimated (Wearden et al., 2007).

How might neurones encode time durations in memory? Single time intervals could be reproduced by gradually varying neural activity during the encoding period which, upon termination of the interval, determines the subsequent rate-of-rise of an accumulator (Jazayeri and Shadlen, 2015) – somewhat like a pendulum that swings back to the height it was released from. But in order to use such an arrangement for sequences of several durations, an elaborate orchestration of segregated neuronal populations would be required (Kleinman et al., 2016). One way of achieving this might be to harness existing domain-general working memory processes.

Our results do suggest a conserved pattern of storage for remembering many different kinds of information, even including short durations. But for this to occur, durations should be encoded by a similar mechanism that has been proposed for other sensory modalities – i.e., a channel-based place code. What is the evidence that time intervals might be encoded by duration-selective channels? First, adaptation effects can be observed when we repeatedly hear a fixed duration, and these cross-modal adaptation effects are highly redolent of those observed in visual orientation and spatial frequency channels (Aaen-Stockdale et al., 2010; Heron et al., 2012). Second, neurophysiology provides evidence for duration-selective channels, for example with channels of the order of 30 ms in the brain stem (Brand et al., 2000; Aubie et al., 2009), around 100 ms in primary auditory cortex (He et al., 1997), up to 400 ms in V1 there, and in prefrontal cortex units have been found that are selective for durations up to 4 s (Yumoto et al., 2011). These neural representations could provide a substrate for storing duration information in working memory. Further, if duration-selective channels of this kind operate similarly to classical visuospatial or auditory feature domains studied in working memory, then similar capacity limits should be evident. In line with this, holding more than one duration in memory reduces the precision with which they can be remembered, and pre-cueing one of several durations can selectively improve memory (Teki and Griffiths, 2014).

Alternative classes of neural model have been proposed to explain how a single interval might be reproduced. First, pacemaker-accumulator models postulate a signal occurring at a fixed average rate that is integrated by a counter, and then compared to some threshold (Treisman, 1963; Gibbon et al., 1984). Second, population clock models posit that neural ensembles transition through a sequence of states in a probabilistic manner to produce accurate timing (Buonomano and Laje, 2010). Third, coincidences of noisy cortical oscillations may be detected by striatal neurons, rendering them sensitive to “beats” that occur after a learned interval (Oprisan and Buhusi, 2014). However, none of these proposals can straightforwardly account for the ability to hold multiple durations in mind, as observed in the current task. Functional imaging findings suggest that sensorimotor thalamocortical-basal-ganglia pathways may subserve the more complex aspects of temporal cognition (Schubotz et al., 2000; Schubotz and von Cramon, 2001; Grahn, 2012a). Indeed working memory may itself be central in producing an interval, because some form of counter needs to be maintained online during the interval (Brown, 1997; Gu et al., 2015). Individuating items in working memory and interval timing might utilize the same temporal context cues, an idea supported by correlations between memory performance and temporal discrimination performance (Unsworth and Engle, 2005; Broadway and Engle, 2011). Interval timing and working memory might thus be two modes of operation of the same neural system (Gu et al., 2015).

In summary, we show that several temporal durations can be held in working memory at once, and they are subject to standard sequential working memory limits. We demonstrated that the memory of single auditory durations in memory is especially susceptible to manipulations of attention and expectation.

SM conceived, conducted, and analyzed data from the experiments. SM and MH wrote the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.