Influence of prior information on pain involves biased perceptual decision-making

Autism spectrum disorder (ASD) is characterized by social interaction and communication impairments, as well as restrictive/repetitive patterns of behavior, interests or activities, which can coexist with intellectual disability and altered sensory processing. To study the mechanisms underlying these core features of ASD, preclinical research has developed animal models with manipulations in ASD-linked genes, such as CNTNAP2. In order to fully interpret the findings from mechanistic studies, the extent to which these models display behaviors consistent with ASD must be determined. Toward that goal, we conducted an investigation of the consequences of a functional loss of Cntnap2 on ASD-related behaviors by comparing the performance of rats with a homozygous or heterozygous knockout of Cntnap2 to their wildtype littermates across a comprehensive test battery. Cntnap2-/- rats showed deficits in sociability and social novelty, and they displayed repetitive circling and hyperlocomotion. Moreover, Cntnap2-/- rats demonstrated exaggerated acoustic startle responses, increased avoidance to sounds of moderate intensity, and a lack of rapid audiovisual temporal recalibration; indicating changes in sensory processing at both the pre-attentive and perceptual levels. Notably, sensory behaviors requiring learned associations did not reveal genotypic differences, whereas tasks relying on automatic/implicit behaviors did. Ultimately, because these collective alterations in social, stereotypic, and sensory behaviors are phenotypically similar to those reported in individuals with ASD, our results establish the Cntnap2 knockout rat model as an effective platform to study not only the molecular and cellular mechanisms associated with ASD, but also the complex relationship between altered sensory processing and other core ASD-related behaviors. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by social interaction differences, and restrictive/repetitive patterns of behavior. We studied the behavioral alterations caused by the loss of an autism-linked gene, Cntnap2, in the rat to determine how mutations in this gene contribute to autism-related behaviors. We show the loss of Cntnap2 leads to changes in social, stereotypic, and sensory behaviors, indicating this rat model can be used to better understand the brain changes underlying ASD. Autism Res 2020, 13: 1698-1717. © 2020 International Society for Autism Research and Wiley Periodicals LLC.

The evidence accumulation model is a widely used cognitive model of human decision-making, which assumes that decision-makers continuously gather and integrate information into evidence relevant to the decision and make a decision once the accumulated evidence reaches a predefined threshold. With the increasing popularity of evidence accumulation model, some researchers claim it has reached a theoretical plateau and can be considered as the standard model for analyzing response time and choices. However, the theoretical assumptions underlying these models lack rigorous testing. As an example, the drift-diffusion model (DDM) is an instantiation of evidence accumulation and has five underlying assumptions: (1) The universality of evidence accumulation; (2) the selectivity of evidence accumulation; (3) linear integration of evidence with noise; (4) a constant decision criterion; and (5) decision-making is independent of motor execution. DDM has been widely used in cognitive tasks, such as value-based decision-making, and social decision-making, probably due to the availability of user-friendly software for parameter estimation. However, only a few studies systematically examined to what extent these five assumptions of DDM were supported by empirical studies. To fill the gap, we reviewed studies that tested these five assumptions.For the first assumption of DDM, the universality of evidence accumulation, we only found direct evidence from studies that employed perceptual decision-making tasks. For other studies that used DDM for modeling, such as value-based decision-making or social decision-making, we found few studies that directly tested the existence of evidence accumulation. The second assumption, the selectivity of evidence accumulation, suggested that only information related to the goal would contribute to evidence accumulation. We did not find empirical data supporting this assumption except for O’Connell et al. However, evidence from conflict tasks (e.g., flanker task) suggested that information irrelevant to the goal may also be incorporated into the evidence accumulation. Data from conflict tasks inspired new models under evidence accumulation model and called for further investigation into the mechanism related to the selectivity of evidence. The third and fourth assumptions constitute the core assumptions of DDM, i.e., “evidence accumulate-to-bound”. Regarding the third assumption, which posits that evidence with noise is accumulated linearly, supporting data were found from animal studies and human EEG studies that employed perceptual decision-making. However, human EEG data from value-based decision-making tasks has challenged the validity of this assumption. The fourth assumption, that the decision criterion is constant, is controversial and has been challenged by several other evidence accumulation models, such as collapsing boundary models. The last assumption, that decision-making is independent of motor execution, has also been questioned by empirical data from both animal studies and human behavioral and electromyography data, despite support from EEG recording.In summary, we found that, while the standard DDM is commonly used in many sub-fields of psychology and neuroscience, empirical studies that directly tested five assumptions of DDM were mainly from perceptual decision-making tasks. Also, we found that challenging these assumptions often resulted in new computational models. These findings call for studies to test these assumptions and develop new models. Besides these findings suggest that researchers should be cautious when interpreting the parameters estimated from standard DDM. Finally, our review suggests that increasing transparency in model assumptions will accelerate the revision of models and theories, and ultimately deepen our understanding of human cognitive processes.

The dorsal anterior cingulate cortex (dACC) and the anterior insulae (AIs) are coactivated in various perceptual decision-making (PDM) tasks and form the salience network (SN): a key network in sensory perception and the coordination of behavioral responses. However, what the functional role of SN is, how these key SN nodes interact with each other to form a network in a perceptual decision, and how the network depends on the perceptual difficulty remain largely unknown. In the present study, we measured blood oxygen level-dependent (BOLD) signals using functional magnetic resonance imaging (fMRI). During four PDM tasks (1) face-house discrimination, (2) happy-angry face discrimination, (3) audiovisual asynchrony and synchrony perception, and a (4) random dot motion direction task, we varied the task difficulty and examined the interactions between these SN nodes. In all the experiments, behavioral accuracy decreased and response time increased with task difficulty. The BOLD signal increased in SN nodes with the ambiguity in the sensory information. We also found that there were significant directed functional connections between AIs and dACC in all four tasks and that the interactions between these nodes increased with task difficulty. The observed difficulty-dependent functional architecture of SN suggests that the dACC and AIs are part of a large-scale cognitive system that facilitates sensory integration in PDM.

Humans visually process the world with varying spatial resolution and can program their eye movements optimally to maximize information acquisition for a variety of everyday tasks. Diseases such as macular degeneration can change visual sensory processing, introducing central vision loss (a scotoma). However, humans can learn to direct a new preferred retinal location to regions of interest for simple visual tasks. Whether such learned compensatory saccades are optimal and generalize to more complex tasks, which require integrating information across a large area of the visual field, is not well understood. Here, we explore the possible effects of central vision loss on the optimal saccades during a face identification task, using a gaze-contingent simulated scotoma. We show that a new foveated ideal observer with a central scotoma correctly predicts that the human optimal point of fixation to identify faces shifts from just below the eyes to one that is at the tip of the nose and another at the top of the forehead. However, even after 5000 trials, humans of both sexes surprisingly do not change their initial fixations to adapt to the new optimal fixation points to faces. In contrast, saccades do change for tasks such as object following and to a lesser extent during search. Our findings argue against a central brain motor-compensatory mechanism that generalizes across tasks. They instead suggest task specificity in the learning of oculomotor plans in response to changes in front-end sensory processing and the possibility of separate domain-specific representations of learned oculomotor plans in the brain.SIGNIFICANCE STATEMENT The mechanism by which humans adapt eye movements in response to central vision loss is still not well understood and carries importance for gaining a fundamental understanding of brain plasticity. We show that although humans adapt their eye movements for simpler tasks such as object following and search, these adaptations do not generalize to more complex tasks such as face identification. We provide the first computational model to predict where humans with central vision loss should direct their eye movements in face identification tasks, which could become a critical tool in making patient-specific recommendations. Based on these results, we suggest a novel theory for oculomotor learning: a distributed representation of learned eye-movement plans represented in domain-specific areas of the brain.

Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision-making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as individual differences in the general population. While behavioral paradigms are commonly used to characterize individual differences in perception as a stable characteristic, measurement reliability in these behavioral tasks is rarely assessed. To remedy this gap, we empirically evaluate the reliability of a perceptual decision-making task that quantifies individual differences in Bayesian belief updating in terms of the relative precision weighting afforded to prior and likelihood information (i.e., sensory weight). We analyzed data from participants (n = 37) who performed this task twice. We found that the precision afforded to prior and likelihood information showed high internal consistency and good test-retest reliability (ICC = 0.73, 95% CI [0.53, 0.85]) when averaged across participants, as well as at the individual level using hierarchical modeling. Our results provide support for the assumption that Bayesian belief updating operates as a stable characteristic in perceptual decision-making. We discuss the utility and applicability of reliable perceptual decision-making paradigms as a measure of individual differences in the general population, as well as a diagnostic tool in psychiatric research.

Purpose: To compare pain severity during laser in situ keratomileusis (LASIK)between first- and second – eye surgery in a Pakistani population.Material and Methods: This was a prospective cohort study. 31 individualseligible for LASIK in both eyes were recruited at a laser clinic between June2012 and November 2015. All underwent surgery using microkeratome andCustomVis Solid state laser. After completion of the procedure, patients ratedseverity of their pain during Lasik on a 4 – point scale (e.g. none, mild, moderate,severe pain) for each eye separately. Wilcoxon signed – rank test was used tocompare pain severity between first- and second – eye surgery.Results: A total of 31 patients (62 eyes) were enrolled in the study. 16 (51.6%)patients perceived more pain in the second eye and 6 (19.4%) in the first one.There were 9 (29.0%) ties. The Wilcoxon signed – rank test showed a statisticallysignificant change in pain perception in the second eye (Z =-2.343; P = 0.019).Conclusions: Patients undergoing LASIK perceived more pain in the secondeye. Larger studies are needed to investigate this finding further, and to identifyfactors influencing this change in pain perception.

Threat cues have been widely shown to elicit increased sensory and attentional neural processing. However, whether this enhanced recruitment leads to measurable behavioral improvements in perception is still in question. Here we adjudicate between two opposing theories: that threat cues do or do not enhance perceptual sensitivity. We created threat stimuli by pairing one direction of motion in a random dot kinematogram with an aversive sound. While in the MRI scanner, 46 subjects (both men and women) completed a cued (threat/safe/neutral) perceptual decision-making task where they indicated the perceived motion direction of each moving dots stimulus. We found strong evidence that threat cues did not increase perceptual sensitivity compared to safe and neutral cues. This lack of improvement in perceptual decision-making ability occurred despite the threat cue resulting in widespread increases in frontoparietal BOLD activity, as well as increased connectivity between the right insula and the frontoparietal network. These results call into question the intuitive claim that expectation automatically enhances our perception of threat, and highlight the role of the frontoparietal network in prioritizing the processing of threat-related environmental cues.

Altered sensory processing has been linked to symptoms of obsessive-compulsive disorder (OCD) and anxiety disorders (ADs) in youth, but few studies have examined sensory processing in clinical samples and no study has analyzed self-report data from youth meeting diagnostic criteria for OCD or ADs. This study included 86 youth with OCD, 82 youth with ADs, and 46 youth without psychiatric disorders. Participants completed the adolescent version of the Sensory Profile and scales measuring three symptom dimensions of OCD, four symptom dimensions of anxiety, and symptoms of major depression. Results showed that different forms of sensory processing difficulties (sensitivity, avoidance, low registration) were adequately captured by one broad sensory processing factor. Youth with OCD and ADs reported statistically significantly more sensory difficulties than youth without psychiatric disorders, but the two clinical groups did not differ from each other. Altered sensory processing in the clinical groups was not explained by the presence of neurodevelopmental disorders. Sensory difficulties were moderately to strongly related to all self-reported symptom dimensions, and uniquely related to the OCD dimension of symmetry/ordering and the anxiety dimensions of panic and social anxiety. Most youth in the clinical groups were classified as having difficulties with sensory processing. The present study shows that sensory processing difficulties are common in youth with OCD and ADs, not explained by co-occurring neurodevelopmental disorders, and linked to a host of internalizing symptoms. More research is needed to identify whether sensory processing difficulties precede, follow, or mutually reinforce the development of OCD and ADs in youth.

Patients with chronic pain often complain of pain when they wake at night, but the accuracy of their perception of the pain after waking at night is unknown. While cognitive functions are reduced for a short time after waking from sleep, a situation known as sleep inertia, it is unclear how sleep inertia may affect the perception of pain. We investigated the effects of sleep inertia on the perception of experimentally induced pain. Fourteen male volunteers were exposed to a randomized thermal heat stimulus of 43.1 degrees C 'hot' and 46.5 degrees C 'hurting' during provoked waking from Stage 2 sleep, slow wave sleep and rapid eye movement (REM) sleep. Subjects rated their pain on awakening on a Visual Analogue Scale at 30 s after awakening and each minute thereafter for 5 min. We found no change in pain perception over the 5-min period irrespective of temperature used or sleep stage. However, perceived pain when awoken abruptly from REM sleep was significantly lower than the awake score for both the hot (P = 0.0069) and hurting (P = 0.0025) temperatures. Pain perception when woken from Stage 2 sleep or slow wave sleep was not significantly different from perception when awake. Our findings indicate that sleep inertia reduces pain perception when awoken abruptly from REM. This suggests that patients who wake up in pain either perceive accurately the pain they are experiencing, or at worst underestimate the level of pain if woken from REM sleep.

Decision Making in Recurrent Neuronal Circuits

Recent theories and data suggest that adapted behavior involves economic computations during which multiple trade-offs between reward value, accuracy requirement, energy expenditure, and elapsing time are solved so as to obtain rewards as soon as possible while spending the least possible amount of energy. However, the relative impact of movement energy and duration costs on perceptual decision-making and movement initiation is poorly understood. Here, we tested 31 healthy subjects on a perceptual decision-making task in which they executed reaching movements to report probabilistic choices. In distinct blocks of trials, the reaching duration (“Time” condition) and energy (“Effort” condition) costs were independently varied compared to a “Reference” block, while decision difficulty was maintained similar at the block level. Participants also performed a simple delayed-reaching (DR) task aimed at estimating movement initiation duration in each motor condition. Results in that DR task show that long duration movements extended reaction times (RTs) in most subjects, whereas energy-consuming movements led to mixed effects on RTs. In the decision task, about half of the subjects decreased their decision durations (DDs) in the Time condition, while the impact of energy on DDs were again mixed across subjects. Decision accuracy was overall similar across motor conditions. These results indicate that movement duration and, to a lesser extent, energy expenditure, idiosyncratically affect perceptual decision-making and action initiation. We propose that subjects who shortened their choices in the time-consuming condition of the decision task did so to limit a drop of reward rate.

Perceptual decision making is believed to be driven by the accumulation of sensory evidence following stimulus encoding. More controversially, some studies report that neural activity preceding the stimulus also affects the decision process. We used a multivariate pattern classification approach for the analysis of the human electroencephalogram (EEG) to decode choice outcomes in a perceptual decision task from spatially and temporally distributed patterns of brain signals. When stimuli provided discriminative information, choice outcomes were predicted by neural activity following stimulus encoding; when stimuli provided no discriminative information, choice outcomes were predicted by neural activity preceding the stimulus. Moreover, in the absence of discriminative information, the recent choice history primed the choices on subsequent trials. A diffusion model fitted to the choice probabilities and response time distributions showed that the starting point of the evidence accumulation process was shifted toward the previous choice, consistent with the hypothesis that choice priming biases the accumulation process toward a decision boundary. This bias is reflected in prestimulus brain activity, which, in turn, becomes predictive of future decisions. Our results provide a model of how non-stimulus-driven decision making in humans could be accomplished on a neural level.

Cortical responses to auditory novelty across task conditions: An intracranial electrophysiology study

Dynamic functional connectivity underlying temporal summation of pain in fibromyalgia

The perception of pain is highly variable. It depends on bottom-up-mediated factors like stimulus intensity and top-down-mediated factors like expectations. In the brain, pain is associated with a complex pattern of neuronal responses including evoked potentials and induced responses at alpha and gamma frequencies. Although they all covary with stimulus intensity and pain perception, responses at gamma frequencies can be particularly closely related to the perception of pain. It is, however, unclear whether this association holds true across all types of pain modulation. Here, we used electroencephalography to directly compare bottom-up- and top-down-mediated modulations of pain, which were implemented by changes in stimulus intensity and placebo analgesia, respectively. The results show that stimulus intensity modulated pain-evoked potentials and pain-induced alpha and gamma responses. In contrast, placebo analgesia was associated with changes of evoked potentials, but not of alpha and gamma responses. These findings reveal that pain-related neuronal responses are differentially sensitive to bottom-up and top-down modulations of pain, indicating that they provide complementary information about pain perception. The results further show that pain-induced gamma oscillations do not invariably encode pain perception but may rather represent a marker of sensory processing whose influence on pain perception varies with behavioral context.