Pupillary fluctuation amplitude before target presentation reflects short-term vigilance level in Psychomotor Vigilance Tasks

Our daily activities require vigilance. Therefore, it is useful to externally monitor and predict our vigilance level using a straightforward method. It is known that the vigilance level is linked to pupillary fluctuations via Locus Coeruleus and Norepinephrine (LC-NE) system. However, previous methods of estimating long-term vigilance require monitoring pupillary fluctuations at rest over a long period. We developed a method of predicting the short-term vigilance level by monitoring pupillary fluctuation for a shorter period consisting of several seconds. The LC activity also fluctuates at a timescale of seconds. Therefore, we hypothesized that the short-term vigilance level could be estimated using pupillary fluctuations in a short period and quantified their amplitude as the Micro-Pupillary Unrest Index (M-PUI). We found an intra-individual trial-by-trial positive correlation between Reaction Time (RT) reflecting the short-term vigilance level and M-PUI in the period immediately before the target onset in a Psychomotor Vigilance Task (PVT). This relationship was most evident when the fluctuation was smoothed by a Hanning window of approximately 50 to 100 ms (including cases of down-sampled data at 100 and 50 Hz), and M-PUI was calculated in the period up to one or two seconds before the target onset. These results suggest that M-PUI can monitor and predict fluctuating levels of vigilance. M-PUI is also useful for examining pupillary fluctuations in a short period for elucidating the psychophysiological mechanisms of short-term vigilance.

Corticospinal correlates of hand preference for reaching during whole-body motion

Behavioral studies have shown that humans account for inertial acceleration in their decisions of hand choice when reaching during body motion. Physiologically, it is unclear at what stage of movement preparation information about body motion is integrated in the process of hand selection. Here, we addressed this question by applying transcranial magnetic stimulation over motor cortex (M1) of human participants who performed a preferential reach task while they were sinusoidally translated on a linear motion platform. If M1 only represents a read-out of the final hand choice, we expect the body motion not to affect the MEP amplitude. If body motion biases the hand selection process prior to target onset, we expect corticospinal excitability to modulate with the phase of the motion, with larger MEP amplitudes for phases that show a bias to using the right hand. Behavioral results replicate our earlier findings of a sinusoidal modulation of hand choice bias with motion phase. MEP amplitudes also show a sinusoidal modulation with motion phase, suggesting that body motion influences corticospinal excitability which may ultimately reflect changes of hand preference. The modulation being present prior to target onset suggests that competition between hands is represented throughout the corticospinal tract. Its phase relationship with the motion profile suggests that other processes after target onset take up time until the hand selection process has been completely resolved, and the reach is initiated. We conclude that the corticospinal correlates of hand preference are modulated by body motion.

Estimating Time: Comparing the Accuracy of Estimation Methods for Interval Timing

In interval timing experiments, motor reproduction is the predominant method used when participants are asked to estimate an interval. However, it is unknown how its accuracy, precision and efficiency compare to alternative methods, such as indicating the duration by spatial estimation on a timeline. In two experiments, we compared different interval estimation methods. In the first experiment, participants were asked to reproduce an interval by means of motor reproduction, timeline estimation, or verbal estimation. We found that, on average, verbal estimates were more accurate and precise than line estimates and motor reproductions. However, we found a bias towards familiar whole second units when giving verbal estimates. Motor reproductions were more precise, but not more accurate than timeline estimates. In the second experiment, we used a more complex task: Participants were presented a stream of digits and one target letter and were subsequently asked to reproduce both the interval to target onset and the duration of the total stream by means of motor reproduction and timeline estimation. We found that motor reproductions were more accurate, but not more precise than timeline estimates. In both experiments, timeline estimates had the lowest reaction times. Overall, our results suggest that the transformation of time into space has only a relatively minor cost. In addition, they show that each estimation method comes with its own advantages, and that the choice of estimation method depends on choices in the experimental design: for example, when using durations with integer durations verbal estimates are superior, yet when testing long durations, motor reproductions are time intensive making timeline estimates a more sensible choice.

Automatic inhibition of habitual response associated with a non-target object while performing goal-directed actions

This study is devoted to investigating mechanisms that inhibit habituated response associated with affordance of a non-target while executing action directed to a target. In four experiments, a paradigm was used that required a rapid left- or right-hand response according to the direction of the target arrow presented simultaneously or in close temporal proximity to a non-target whose handle position afforded grasping with the left or right hand. In general, responding was decelerated and more erroneous when the handle position was compatible with the responding hand. This effect of response inhibition was removed when the delay between the non-target offset and target onset was longer than 200 ms, and reversed into response facilitation when the target onset was delayed for 400–600 ms. The study suggests that processes that control withholding habitual response associated with affordance of a non-target utilise response inhibition mechanisms overlapping with those involved in behavioural control of the stop-signal task. This response inhibition is triggered automatically and directly by affordance of a non-target without preceding response excitation associated with this affordance cue.

How can we learn what attention is? Response gating via multiple direct routes kept in check by inhibitory control processes

To explore the time course of space- and object-based attentional selection processes I analysed the shapes of the response time (RT) and accuracy distributions of left/right arrow identification responses in the two-rectangle paradigm. After cueing one of the four ends of two horizontally or vertically oriented rectangles the arrow typically appears at the cued location (valid), or sometimes at an uncued location in the same (invalid-same) or other rectangle (invalid-different). The data point to a multiple-route model in which (a) an informative cue generates response channel activation before arrow signals emerge, (b) the task-irrelevant arrow location is represented in multiple egocentric and allocentric reference frames around 150 ms after target onset, with the former including a reference frame centered on the currently attended location, (c) the task-irrelevant spatial codes activate premature response tendencies that are actively inhibited to allow gating of arrow direction signals, (d) after an invalid cue the onset of the arrow triggers an “attention shift” – acting between 150 and 240 ms after target onset – that strongly interferes with task performance in certain conditions (invalid-same cueing with horizontal rectangles, and invalid-different cueing with vertical rectangles), and (e) participants differ in which task-irrelevant codes they preferentially inhibit. These results pave the way for future confirmatory studies to temporally characterize and disentangle the contributions of different types of response channel activation processes, from those of reactive cognitive control processes including active and selective response suppression.

What is causing “inhibition of return” in spatial cueing tasks? Temporally disentangling multiple cue-triggered effects on multiple time scales using response history and conditional accuracy analyses.

Research on spatial cueing has shown that uninformative cues often facilitate mean response time (RT) performance in valid- compared to invalid-cueing conditions at short cue-target stimulus-onset-asynchronies (SOAs), and robustly generate a reversed or inhibitory cueing effect at longer SOAs that is widely known as inhibition-of-return (IOR). To study the within-trial time course of IOR we employ discrete-time hazard and conditional accuracy analyses to describe and model the shapes of the RT and accuracy distributions measured in two experimental tasks. In contrast to the mean performance measures, our distributional analyses show that (a) the uninformative cue generates response channel activation, (b) which continues during the cue-target interval so that the cue location must be stored in spatial working memory, (c) the premature cue-triggered response is selectively inhibited before target onset, (d) the IOR effect (valid versus invalid cueing) emerges around 160 ms after target onset in the hazard functions when cue-target SOA exceeds ~200 ms, quickly increases and decreases in size, and is gone within 120 ms, (e) the inhibitory component does not diminish over the course of the experiment, and (f) the location of an additional central cue relative to the current focus of spatial attention can generate response channel activation as well. These distributional data show that mean performance patterns conceal crucial information about behavioral dynamics, and suggest that sensory IOR is the direct result of encoding the cue location in spatial working memory to promote change detection, instead of attention leaving an inhibitory tag to promote visual search.

Electrophysiological correlates of visual backward masking in patients with bipolar disorder

BackgroundIn visual backward masking (VBM), a target is followed by a mask that decreases target discriminability. Schizophrenia patients (SZ) show strong and reproducible masking impairments, which are associated with reduced EEG amplitudes. Patients with bipolar disorder (BP) show masking deficits, too. Here, we investigated the neural EEG correlates of VBM in BP.Methods122 SZ, 94 unaffected controls, and 38 BP joined a standard VBM experiment. 123 SZ, 94 unaffected controls and 16 BP joined a corresponding EEG experiment, analyzed in terms of the global field power.ResultsAs in previous studies, SZ and BP show strong masking deficits. Importantly and similarly to SZ, BP show decreased global field power amplitudes at approximately 200 ms after the target onset, compared to controls.ConclusionsThese results suggest that VBM deficits are not specific for schizophrenia but for a broader range of functional psychoses. Potentially, both SZ and BP show deficient target enhancement.

When Temporal Certainty Doesn't Help

In a dynamically changing environment, the ability to capture regularities in our sensory input helps us generate predictions about future events. In most sensory systems, the basic finding is clear: Knowing when something will happen improves performance on it [Nobre, A. C., & van Ede, F. (2017). Anticipated moments: Temporal structure in attention. Nature Reviews Neuroscience, 19, 34–48, 2017]. We here examined the impact of temporal predictions on a less-explored modality: touch. Participants were instructed to detect a brief target embedded in an ongoing vibrotactile stimulus. Unbeknownst to them, the experiment had two timing conditions: In one part, the time of target onset was fixed and thus temporally predictable, whereas in the other, it could appear at a random time within the ongoing stimulation. We found a clear modulation of detection thresholds due to temporal predictability: Contrary to other sensory systems, detecting a predictable tactile target was worse relative to unpredictable targets. We discuss our findings within the framework of tactile suppression.