Adopting Stimulus Detection Tasks for Cognitive Workload Assessment: Some Considerations.

OBJECTIVE: This article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator's workload. BACKGROUND: Stimulus detection tasks are a relative simple and inexpensive means of measuring the operator's state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic. METHOD: This mini-review details the use of common stimulus detection tasks and their contributions to the Human Factors practice. It also borrows from the conceptual framework of the inverted-U shape model to discuss the issue of data interpretation. RESULTS: The evidence being discussed here highlights a clear limitation of stimulus detection task paradigms. CONCLUSION: There is an inherent risk in using a unidimensional tool like stimulus detection tasks as the primary source of information for determining the operator's psychophysiological state. APPLICATION: Two recommendations are put forward to Human Factors researchers and practitioners dealing with the interpretation conundrum of dealing with stimulus detection tasks.

Modulation in cortical excitability disrupts information transfer in perceptual-level stimulus processing.

Despite significant interest in the neural underpinnings of behavioral variability, little light has been shed on the cortical mechanism underlying the failure to respond to perceptual-level stimuli. We hypothesized that cortical activity resulting from perceptual-level stimuli is sensitive to the moment-to-moment fluctuations in cortical excitability, and thus may not suffice to produce a behavioral response. We tested this hypothesis using electrocorticographic recordings to follow the propagation of cortical activity in six human subjects that responded to perceptual-level auditory stimuli. Here we show that for presentations that did not result in a behavioral response, the likelihood of cortical activity decreased from auditory cortex to motor cortex, and was related to reduced local cortical excitability. Cortical excitability was quantified using instantaneous voltage during a short window prior to cortical activity onset. Therefore, when humans are presented with an auditory stimulus close to perceptual-level threshold, moment-by-moment fluctuations in cortical excitability determine whether cortical responses to sensory stimulation successfully connect auditory input to a resultant behavioral response.

Visual Stimulus Detection Correlates with the Consistency of Temporal Sequences within Stereotyped Events of V1 Neuronal Population Activity.

UNLABELLED: Sensory information about the world is translated into rate codes, such that modulations in mean spiking activity of neurons relate to differences in stimulus features. More recently, it has been proposed that also temporal properties of activity, such as assembly formation and sequential population activation, are important for understanding the relation between neuronal activity and behavioral output. These phenomena appear to be robust properties of neural circuits, but their relevance for perceptual judgments, such as the behavioral detection of stimuli, remains to be tested. Studying neuronal activity with two-photon calcium imaging in primary visual cortex of mice performing a go/no-go visual detection task, we found that assemblies (i.e., configurations of neuronal group activity) reliably recur, as defined using Ward-method clustering. However, population activation events with a recurring configuration of core neurons did not appear to serve a particular function in the coding of orientation or the detection of stimuli. Instead, we found that, regardless of whether the population event showed a recurring or nonrecurring configuration of neurons, the sequence of cluster activation was correlated with the detection of stimuli. Moreover, each neuron showed a preferred temporal position of activation within population events, which was robust despite varying neuronal participation. Furthermore, the timing of neuronal activity within such a sequence was more consistent when a stimulus was detected (hits) than when it remained unreported (misses). Our data indicate that neural processing of information related to visual detection behavior depends on the temporal positioning of individual and group-wise cell activity. SIGNIFICANCE STATEMENT: Temporally coactive neurons have been hypothesized to form functional assemblies that might subserve different functions in the brain, but many of these proposed functions have not yet been experimentally tested. We used two-photon calcium imaging in V1 of mice performing a stimulus detection task to study the relation of assembly activity to the behavioral detection of visual stimuli. We found that the presence of recurring assemblies per se was not correlated with behavior, and these assemblies did not appear to serve a function in the coding of stimulus orientation. Instead, we found that activity in V1 is characterized by population events of varying membership, within which the consistency of the temporal sequence of neuronal activation is correlated with stimulus detection.

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.

Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation.

Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.

Stimulus detection rate and latency, firing rates and 1-40Hz oscillatory power are modulated by infra-slow fluctuations in a bistable attractor network model.

Recordings of membrane and field potentials, firing rates, and oscillation amplitude dynamics show that neuronal activity levels in cortical and subcortical structures exhibit infra-slow fluctuations (ISFs) on time scales from seconds to hundreds of seconds. Similar ISFs are salient also in blood-oxygenation-level dependent (BOLD) signals as well as in psychophysical time series. Functional consequences of ISFs are not fully understood. Here, they were investigated along with dynamical implications of ISFs in large-scale simulations of cortical network activity. For this purpose, a biophysically detailed hierarchical attractor network model displaying bistability and operating in an oscillatory regime was used. ISFs were imposed as slow fluctuations in either the amplitude or frequency of fast synaptic noise. We found that both mechanisms produced an ISF component in the synthetic local field potentials (LFPs) and modulated the power of 1-40Hz oscillations. Crucially, in a simulated threshold-stimulus detection task (TSDT), these ISFs were strongly correlated with stimulus detection probabilities and latencies. The results thus show that several phenomena observed in many empirical studies emerge concurrently in the model dynamics, which yields mechanistic insight into how infra-slow excitability fluctuations in large-scale neuronal networks may modulate fast oscillations and perceptual processing. The model also makes several novel predictions that can be experimentally tested in future studies.

Interspecific Contagious Yawning in Humans.

Contagious yawning, or the reflexive tendency to yawn following the detection of yawning in others, is well-documented among humans and a growing number of social vertebrates. While the most common form of yawn contagion occurs between conspecifics, some non-human animals in captivity have been reported to yawn in response to yawns from human handlers/caregivers. The current research sought to provide the first formal investigation of whether people yawn contagiously in response to yawns from non-human animals. In addition, this study aimed to test whether this response was modulated by phylogenetic relatedness and domestication/social closeness. A total of 296 participants from Amazon Mechanical Turk self-reported on their yawning behavior following exposure to a (1) control (non-yawning) condition or a compilation of yawning stimuli either from (2) fish, (3) amphibians, (4) reptiles, (5) birds, (6) non-primate mammals, (7) apes, or (8) domesticated cats and dogs. The results provide strong support for interspecific yawn contagion. However, neither the propensity to yawn (binary) nor total yawn frequency varied significantly across interspecific conditions. Overall, these findings suggest that the mechanisms governing yawn contagion can be activated by varied forms of yawning stimuli, including those from distantly related and unfamiliar species.

Attentional signals projecting centrifugally to the avian retina: A dual contribution to visual search.

Among vertebrates, birds have a particularly well-developed retinopetal system, i.e., the centrifugal system projecting from the brain to the retina. Primary, secondary and tertiary neurons of the retinopetal system connect serially in a one-to-one-to-one fashion, thereby assembling several thousand retinopetal modules projecting in parallel to the retina. The signal conveyed by the retinopetal system enhances the visual responses of retinal ganglion cells (RGCs), and each retinopetal module may facilitate the RGCs in a topographically restricted area. We investigated how the retinopetal signal contributes to visual search by first training Japanese quail to search and peck a target stimulus presented on one of three touch-sensor monitors around the bird and then examining the effect of retinopetal signal blockage on the task. Our results indicate that the retinopetal signal improves both stimulus detectability and target discriminability. Thus, this study confirms that the avian retinopetal system functions specifically in attentional facilitation of the retina; this new finding suggests that this system benefits early detection and late selection phases of visual search. The fast and precise target detection facilitated by the retinopetal signal may be transformed into quick and correct orienting to the target through visuomotor transformation mechanisms implemented in the optic tectum.

On the link between emotional contagion and contagious yawning.

Palagi et al. (Neurosci. Biobehav. Rev. 111:149-165, 2020) propose a multidisciplinary approach to the study of spontaneous mimicry, focusing on comparative research on facial mimicry and contagious yawning. In doing so, the authors highlight connections between these behaviors and emotional contagion. The aim of this commentary is to critically evaluate the link between contagious yawning and emotional contagion, address the role of attention in contagious yawning, and promote further research examining the sensory and perceptual factors driving variability in contagious yawning. Contrary to the position of Palagi et al., a strong matching between emotional contagion and contagious yawning has not been established. Variation in contagious yawning appears to be driven by biased attentional processes and yawn detection rather than emotional sharing.

Increased auditory stimulus intensity results in an earlier and faster rise in corticospinal excitability.

Increasing the intensity of auditory stimuli has been shown to produce faster simple reaction times (RTs). Typical explanations for this effect involve earlier detection of the more intense stimulus; however, these explanations fail to consider how stimulus intensity may impact response initiation processing. To investigate the mechanism responsible for the auditory stimulus intensity effect, transcranial magnetic stimulation (TMS) was applied at various times during the simple RT interval (equivalent to 0, 30, 45, 60, and 75% of baseline RT) to examine changes in corticospinal excitability after a go-signal of varying intensity (60, 70, 80, or 90 dB). Premotor RT data confirmed a stimulus intensity effect whereby the 90 dB stimulus resulted in faster RTs than all other intensities. Analysis of motor evoked potential (MEP) amplitude elicited by TMS across stimulus intensity conditions revealed that in the 80 dB and 90 dB conditions, corticospinal excitability began to increase earlier from baseline (pre-stimulus) levels, supporting the detection hypothesis. In addition, MEP amplitude increased at a greater rate during the RT interval for the 90 dB condition, indicative of impacts on response initiation. These results indicate that stimulus intensity effects result from a combination of earlier detection and faster initiation.

The effects of stimulus degradation after 48 hours of total sleep deprivation.

STUDY OBJECTIVES: To test the hypothesis that total sleep deprivation (TSD) slows stimulus detection and evaluation processes. Towards that end we manipulate degradation of the imperative stimulus, a manipulation well established to affect the processes of interest, in a delayed letter recognition (DLR) task and the psychomotor vigilance task (PVT), and predicted that after TSD the ordinary reaction time (RT) slowing effect of stimulus degradation would be increased. These hypotheses were only partially confirmed (see below). DESIGN: Participants were exposed to 48 h of total sleep loss. The PVT and DLR were administered to the same participants. The PVT was administered 8 times -every 6 h from 12:00 on Day 1. The DLR was administered twice, at 09:00 of Day 1 and 48 h later. SETTING: Participants were continuously monitored in a sleep laboratory. SUBJECTS: 26 healthy young adults enrolled. Due to dropouts and technical failures, the final n's were 20 for the DLR and 21 for the PVT. MEASUREMENTS AND RESULTS: General linear mixed models were employed. In the DLR task there was no interaction between TSD and degradation on any variable. There was, however, a significant interaction between TSD and degradation on mean reaction time in the PVT (P = 0.01). CONCLUSIONS: As in our previous reports, we observe the specificity with which total sleep deprivation affects cognitive processes. One aspect of visual processing, stimulus detection, was affected by total sleep deprivation and made a significant contribution to the performance impairments observed. Another aspect of visual processing, stimulus evaluation, remained unaffected after 2 days and nights of total sleep loss.