Sleep deprivation enhances inter-stimulus interval effect on vigilant attention performance

Abstract

Study objective: Sleep deprivation significantly reduces the ability to maintain a consistent alertness level and impairs vigilant attention. Previous studies have shown that longer inter-stimulus interval (ISI) are associated with faster reaction times (RTs) on the Psychomotor Vigilance Test (PVT). However, whether and how sleep deprivation interacts with this ISI effect remains unclear.

Methods: N = 70 healthy adults (age range 20-50 years, 41 males) participated in a 5-day and 4-night in-laboratory controlled sleep deprivation study, including N = 54 in the experimental group with one night of total sleep deprivation and N = 16 in the control group without sleep loss. All participants completed a neurobehavioral test battery every 2 hours while awake, including a 10-minute standard PVT (PVT-S, N = 1626) and a 3-minute brief PVT (PVT-B, N = 1622). The linear approach to threshold with ergodic rate (LATER) model was used to fit the RT data.

Results: RT decreased significantly with longer ISI on the PVT-S and PVT-B. Increased ISI effect was found for both PVT-S and PVT-B during sleep deprivation compared to baseline or recovery sleep in the experimental group, whereas no differences in the ISI effect were found in the control group. The LATER model fitting indicated that changes in perceptual sensitivity rather than threshold adjustment may underlie the ISI effect.

Conclusions: Both standard and brief PVT showed a similar ISI effect on vigilant attention performance. Sleep deprivation increased the ISI effect on both PVT-S and PVT-B, which may be due to impaired temporal resolution and time estimation after sleep loss.

Figure 1.

Protocol summary. Participants arrived at the laboratory on late afternoon of day 1 and were provided 9 hours TIB sleep for night 1. Day 2 was the baseline day for TSD group (upper panel). TSD group were kept awake throughout night 2. Day 3 was the sleep deprivation day. Then, TSD group were allowed 12 TIB recovery sleep at night 3. Day 4 was the recovery day. For control group (bottom panel), 8 hours TIB sleep was provided every night at nights 2, 3, and 4. All participants completed a cognitive test battery (CTB) that includes PVT-S and PVT-B every 2 hours while they were awake and not doing fMRI scans during days 2–4 (except for 1600 hours of day 3 in TSD group). Each time point of cognitive battery was depicted in the figure (i.e. 10 denotes test time around 1000 hours). Three fMRI scans were scheduled between 0700 and 1000 hours on day 2, 3, and 5 (scan duration for each participant was about an hour).

Figure 2.

Panel A: An illustration of a single trial on PVT-S (PVT-B). PVT-S (PVT-B) requires a simple response to a cue, i.e. the onset of a millisecond counter. The millisecond counter stops after participant’s response and remains for another 1 second to allow participants to see their reaction time, i.e. 1 second feedback. The next cue presents after a random ISI ranging from 2 to 10 seconds (1 to 4 seconds). Panel B: The LATER model. When the stimulus onset, a decision signal rise linearly from a certain starting point to a decision threshold (D). If the decision signal reaches the decision threshold, a response is initiated. The slope of the decision signal is followed a Gaussian distribution with mean slope s and with SD slope sd. The RT of each trial reflects the time elapsed before decision signal reaches the threshold decision.

Figure 3.

Two hypotheses about how temporal expectation of stimulus modulates reaction time. Left panel shows the rise of decision signal (mean slope of this linear rise: s, standard deviation of the slope: sd) towards the decision threshold (D). Right panel shows the reciprobit analysis of RT distribution. For decision threshold (DT) modulation hypothesis: increased temporal expectation (e.g. under long ISI) leads to lower decision threshold (D_l < D_s, top left panel), which is captured by the swivel effect on reciprobit line (top right panel). For gain control of processing speed hypothesis (GAIN): increased temporal expectation (e.g. under long ISI) leads to faster processing speed (s_l > s_s, bottom left panel), which is captured by the shift effect on reciprobit line (bottom right panel). Note: Z-score reflects Z-score of the cumulative distribution of 1/RT.

Figure 4.

The relationship between model-based RT and ISI sub-groups in PVT-B (left column) and PVT-S (right column) of the TSD group during day 2 (baseline), day 3 (sleep deprivation), and day 4 (recovery). Different colored line represents data collected from different time-of-day.

Figure 5.

The relationship between percentage of lapse (%lapse) and ISI sub-groups in PVT-B (left column) and PVT-S (right column) of the TSD group during day 2 (baseline), day 3 (sleep deprivation), and day 4 (recovery). Different colored line represents data collected from different time-of-day.

Figure 6.

Representative examples of reciprobit plot for both PVT-B (left panel, data from test at 1000 hours, day 2) and PVT-S (right panel, data from test at 1000 hours, day 2) showing a shift towards shorter RT as temporal expectation increases (i.e. from ISI sub-group 1 to ISI sub-group 7). This is consistent with Gain control of processing speed hypothesis.

Figure 7.

Differences in the log-likelihood ratio (LLR) between the two LATER hypotheses (Gain-DT) when fitting the PVT-S and PVT-B data from the TSD group and control group, respectively. Sleep deprivation significantly reduced LLR for the TSD group (p < 0.05 for PVT-S and p < 0.001 for PVT-B), whereas no LLR differences were found across 3 days for the control group (all p > 0.1). Note: error bar denotes standard error.

Figure 8.

Sleep deprivation changed the relationships between the ISI sub-groups and RT on both PVT-S and PVT-B. Red cross in each picture represents median RT of each ISI sub-group from day 2 (baseline), red line is a linear regression of red cross, and shadow represents standard error of each data point. Likewise, blue and green denote data from day 3 (sleep deprivation) and day 4 (recovery), respectively. Slopes of each line are shown in the bracket. (A and B) Sleep deprivation significantly changed the slopes of regression line for both PVT-S and PVT-B (p < 0.001). (C and D) No differences were found among the slopes in 3 days in the control group for both PVT-S and PVT-B (all p > 0.1).

Figure 9.

Sleep deprivation changed the relationships between the ISI sub-groups and Lapse% on both PVT-S and PVT-B. Red cross in each picture represents Lapse% of each ISI sub-group from day 2 (baseline), red line is a linear regression of red cross, and shadow represents standard error of each data point. Likewise, blue and green denote data from day 3 (sleep deprivation) and day 4 (recovery), respectively. Slopes of each line are shown in the bracket. (A and B) Sleep deprivation significantly changed the slopes of regression line for both PVT-S and PVT-B (p < 0.001). (C and D) No differences were found among the slopes in 3 days in the control group for both PVT-S and PVT-B (all p > 0.1).