Perceptual Decision-making Task Research Articles

Navigating Virtual Collisions: Insights Into Perception–Action Differences in Children and Young Adults Using a Head-On Avoidance Task

Children tend to make more last-minute locomotor adjustments than adults when avoiding stationary obstacles. The purpose of this study was to compare avoidance behaviors of middle-aged children (10–12 years old) with young adults during a head-on collision course with an approaching virtual pedestrian. Participants were immersed in a virtual environment and completed a perceptual decision-making task in which they had to respond to the future direction of an approaching virtual pedestrian once they disappeared. Following the perceptual task, participants walked along an 8-m pathway toward a goal, while avoiding a collision with a virtual pedestrian who approached along the midline than veered toward the left, right, or continued walking straight. Results revealed that children were able to correctly predict the future directions of the virtual pedestrian similar to adults, albeit at a slower response time (0.55 s vs. 0.33 s). During the action task, children initiated a deviation in their travel path later (i.e., closer to the virtual pedestrian) compared to adults (1.65 s vs. 1.52 s). Children were also more variable in their onset of deviation and time-to-contact. Although children appear to have developed adult-like perceptual abilities and can avoid an approaching virtual pedestrian, children employ riskier avoidance strategies and are highly variable, suggesting middle-aged children are still fine-tuning their perception-action system.

Temporal stability of Bayesian belief updating in perceptual decision-making.

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.

Prospective and Retrospective Metacognitive Abilities and Their Association with Impaired Self-awareness in Patients with Traumatic Brain Injury.

Metacognitive impairment often occurs in patients with traumatic brain injury (TBI) and is associated with clinical problems. The aim of this study was to clarify the pathology of metacognitive impairment in TBI patients using a behavioral task, clinical assessment of self-awareness, and lesion-symptom mapping. Metacognitive abilities of TBI patients and healthy controls were assessed using a modified perceptual decision-making task. Self-awareness was assessed using the Patient Competency Rating Scale and the Frontal Systems Behavior Scale. The associations between estimated metacognitive abilities, self-awareness, and neuropsychological test results were examined. The correspondence between metacognitive disabilities and brain lesions was explored by ROI-based lesion-symptom mapping using structural magnetic resonance images. Overall, 25 TBI patients and 95 healthy controls were included in the analyses. Compared with that in healthy controls, the prospective metacognitive ability of TBI patients was lower, with metacognitive evaluations revealing a bias toward overestimating their abilities. Retrospective metacognitive ability showed a negative correlation with self-awareness but not with neuropsychological test results. In the lesion-symptom mapping analysis, the left pFC was associated with lower retrospective metacognitive ability. This study contributes to a better understanding of the pathology of metacognitive and self-awareness deficits in TBI patients and may explain the cause of impaired realistic goal setting and adaptive behavior in these patients.

Bayesian accounts of perceptual decisions in the nonclinical continuum of psychosis: Greater imprecision in both top-down and bottom-up processes.

Neurocomputational accounts of psychosis propose mechanisms for how information is integrated into a predictive model of the world, in attempts to understand the occurrence of altered perceptual experiences. Conflicting Bayesian theories postulate aberrations in either top-down or bottom-up processing. The top-down theory predicts an overreliance on prior beliefs or expectations resulting in aberrant perceptual experiences, whereas the bottom-up theory predicts an overreliance on current sensory information, as aberrant salience is directed towards objectively uninformative stimuli. This study empirically adjudicates between these models. We use a perceptual decision-making task in a neurotypical population with varying degrees of psychotic-like experiences. Bayesian modelling was used to compute individuals' reliance on prior relative to sensory information. Across two datasets (discovery dataset n = 363; independent replication in validation dataset n = 782) we showed that psychotic-like experiences were associated with an overweighting of sensory information relative to prior expectations, which seem to be driven by decreased precision afforded to prior information. However, when prior information was more uncertain, participants with greater psychotic-like experiences encoded sensory information with greater noise. Greater psychotic-like experiences were associated with aberrant precision in the encoding both prior and likelihood information, which we suggest may be related to generally heightened perceptions of task instability. Our study lends empirical support to notions of both weaker bottom-up and weaker (rather than stronger) top-down perceptual processes, as well as aberrancies in belief updating that extend into the non-clinical continuum of psychosis.

Judging the difficulty of perceptual decisions

Deciding how difficult it is going to be to perform a task allows us to choose between tasks, allocate appropriate resources, and predict future performance. To be useful for planning, difficulty judgments should not require completion of the task. Here, we examine the processes underlying difficulty judgments in a perceptual decision-making task. Participants viewed two patches of dynamic random dots, which were colored blue or yellow stochastically on each appearance. Stimulus coherence (the probability, pblue, of a dot being blue) varied across trials and patches thus establishing difficulty, |pblue −0.5|. Participants were asked to indicate for which patch it would be easier to decide the dominant color. Accuracy in difficulty decisions improved with the difference in the stimulus difficulties, whereas the reaction times were not determined solely by this quantity. For example, when the patches shared the same difficulty, reaction times were shorter for easier stimuli. A comparison of several models of difficulty judgment suggested that participants compare the absolute accumulated evidence from each stimulus and terminate their decision when they differed by a set amount. The model predicts that when the dominant color of each stimulus is known, reaction times should depend only on the difference in difficulty, which we confirm empirically. We also show that this model is preferred to one that compares the confidence one would have in making each decision. The results extend evidence accumulation models, used to explain choice, reaction time, and confidence to prospective judgments of difficulty.

Adaptive decision-making depends on pupil-linked arousal in rats performing tactile discrimination tasks.

Perceptual decision-making is a dynamic cognitive process and is shaped by many factors, including behavioral state, reward contingency, and sensory environment. To understand the extent to which adaptive behavior in decision-making is dependent on pupil-linked arousal, we trained head-fixed rats to perform perceptual decision-making tasks and systematically manipulated the probability of Go and No-go stimuli while simultaneously measuring their pupil size in the tasks. Our data demonstrated that the animals adaptively modified their behavior in response to the changes in the sensory environment. The response probability to both Go and No-go stimuli decreased as the probability of the Go stimulus being presented decreased. Analyses within the signal detection theory framework showed that while the animals' perceptual sensitivity was invariant, their decision criterion increased as the probability of the Go stimulus decreased. Simulation results indicated that the adaptive increase in the decision criterion will increase possible water rewards during the task. Moreover, the adaptive decision-making is dependent on pupil-linked arousal as the increase in the decision criterion was the largest during low pupil-linked arousal periods. Taken together, our results demonstrated that the rats were able to adjust their decision-making to maximize rewards in the tasks, and that adaptive behavior in perceptual decision-making is dependent on pupil-linked arousal.NEW & NOTEWORTHY Perceptual decision-making is a dynamic cognitive process and is shaped by many factors. However, the extent to which changes in sensory environment result in adaptive decision-making remains poorly understood. Our data provided new experimental evidence demonstrating that the rats were able to adaptively modify their decision criterion to maximize water reward in response to changes in the statistics of the sensory environment. Furthermore, the adaptive decision-making is dependent on pupil-linked arousal.

Common computations formetacognition andmeta-metacognition.

Recent evidence shows that people have the meta-metacognitive ability to evaluate their metacognitive judgments of confidence. However, it is unclear whether meta-metacognitive judgments are made by a different system and rely on a separate set of computations compared to metacognitive judgments. To address this question, we asked participants (N = 36) to perform a perceptual decision-making task and provide (i) an object-level, Type-1 response about the identity of the stimulus; (ii) a metacognitive, Type-2 response (low/high) regarding their confidence in their Type-1 decision; and (iii) a meta-metacognitive, Type-3 response (low/high) regarding the quality of their Type-2 rating. We found strong evidence for the existence of Type-3, meta-metacognitive ability. In a separate condition, participants performed an identical task with only a Type-1 response followed by a Type-2 response given on a 4-point scale. We found that the two conditions produced equivalent results such that the combination of binary Type-2 and binary Type-3 responses acts similar to a 4-point Type-2 response. Critically, while Type-2 evaluations were subject to metacognitive noise, Type-3 judgments were made at no additional cost. These results suggest that it is unlikely that there is a distinction between Type-2 and Type-3 systems (metacognition and meta-metacognition) in perceptual decision-making and, instead, a single system can be flexibly adapted to produce both Type-2 and Type-3 evaluations recursively.

Task-related modulation of motor response to emotional bodies: A TMS motor-evoked potential study

Exposure to emotional body postures during perceptual decision-making tasks has been linked to transient suppression of motor reactivity, supporting the monitoring of emotionally relevant information. However, it remains unclear whether this effect occurs implicitly, i.e., when emotional information is irrelevant to the task. To investigate this issue, we used single-pulse transcranial magnetic stimulation (TMS) to assess motor excitability while healthy participants were asked to categorize pictures of body expressions as emotional or neutral (emotion recognition task) or as belonging to a male or a female actor (gender recognition task) while receiving TMS over the motor cortex at 100 and 125 ms after picture onset. Results demonstrated that motor-evoked potentials (MEPs) were reduced for emotional body postures relative to neutral postures during the emotion recognition task. Conversely, MEPs increased for emotional body postures relative to neutral postures during the gender recognition task. These findings indicate that motor inhibition, contingent upon observing emotional body postures, is selectively associated with actively monitoring emotional features. In contrast, observing emotional body postures prompts motor facilitation when task-relevant features are non-emotional. These findings contribute to embodied cognition models that link emotion perception and action tendencies.

Quantifying decision-making in dynamic, continuously evolving environments.

During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

Initial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex

We used a dynamical systems perspective to understand decision-related neural activity, a fundamentally unresolved problem. This perspective posits that time-varying neural activity is described by a state equation with an initial condition and evolves in time by combining at each time step, recurrent activity and inputs. We hypothesized various dynamical mechanisms of decisions, simulated them in models to derive predictions, and evaluated these predictions by examining firing rates of neurons in the dorsal premotor cortex (PMd) of monkeys performing a perceptual decision-making task. Prestimulus neural activity (i.e., the initial condition) predicted poststimulus neural trajectories, covaried with RT and the outcome of the previous trial, but not with choice. Poststimulus dynamics depended on both the sensory evidence and initial condition, with easier stimuli and fast initial conditions leading to the fastest choice-related dynamics. Together, these results suggest that initial conditions combine with sensory evidence to induce decision-related dynamics in PMd.

Resting-state EEG dynamics help explain differences in response control in ADHD: Insight into electrophysiological mechanisms and sex differences.

Reductions in response control (greater reaction time variability and commission error rate) are consistently observed in those diagnosed with attention-deficit/hyperactivity disorder (ADHD). Previous research suggests these reductions arise from a dysregulation of large-scale cortical networks. Here, we extended our understanding of this cortical-network/response-control pathway important to the neurobiology of ADHD. First, we assessed how dynamic changes in three resting-state EEG network properties thought to be relevant to ADHD (phase-synchronization, modularity, oscillatory power) related with response control during a simple perceptual decision-making task in 112 children/adolescents (aged 8-16) with and without ADHD. Second, we tested whether these associations differed in males and females who were matched in age, ADHD-status and ADHD- subtype. We found that changes in oscillatory power (as opposed to phase-synchrony and modularity) are most related with response control, and that this relationship is stronger in ADHD compared to controls. Specifically, a tendency to dwell in an electrophysiological state characterized by high alpha/beta power (8-12/13-30Hz) and low delta/theta power (1-3/4-7Hz) supported response control, particularly in those with ADHD. Time in this state might reflect an increased initiation of alpha-suppression mechanisms, recruited by those with ADHD to suppress processing unfavourable to response control. We also found marginally significant evidence that this relationship is stronger in males compared to females, suggesting a distinct etiology for response control in the female presentation of ADHD.

Quantifying the contribution of subject and group factors in brain activation.

Research in neuroscience often assumes universal neural mechanisms, but increasing evidence points toward sizeable individual differences in brain activations. What remains unclear is the extent of the idiosyncrasy and whether different types of analyses are associated with different levels of idiosyncrasy. Here we develop a new method for addressing these questions. The method consists of computing the within-subject reliability and subject-to-group similarity of brain activations and submitting these values to a computational model that quantifies the relative strength of group- and subject-level factors. We apply this method to a perceptual decision-making task (n = 50) and find that activations related to task, reaction time, and confidence are influenced equally strongly by group- and subject-level factors. Both group- and subject-level factors are dwarfed by a noise factor, though higher levels of smoothing increases their contributions relative to noise. Overall, our method allows for the quantification of group- and subject-level factors of brain activations and thus provides a more detailed understanding of the idiosyncrasy levels in brain activations.

OCD symptoms are related to seeking and relying on external information even in neutral perceptual decisions

IntroductionDoubt and decision-making difficulties are very common in obsessive-compulsive disorder (OCD). In the present study, we focused on a particular feature of decision-making in OCD – increased information-seeking. Based on the Seeking Proxies for Internal States and the Intolerance for Uncertainty theoretical frameworks, we hypothesized that OCD symptoms will be positively associated with information-seeking, even for neutral perceptual decisions. MethodFifty-eight UK participants were recruited via Prolific. They performed a perceptual decision-making task and completed questionnaires assessing OCD and associated variables. The perceptual task entailed locating the exact mid-point of a brightness continuum of a specific hue. Upon request, participants could obtain objective hints (purported responses of other participants), although hints incurred time-out penalties. ResultsConsistent with our hypothesis, OCD symptom levels predicted how many hints participants requested, even after controlling for anxiety and depression symptoms. Additionally, OCD symptoms were partially related to indecisiveness in the task. DiscussionOur findings suggest that obsessive-compulsive tendencies are related to indecisiveness and to seeking external information even in a neutral context. Moreover, OCD tendencies were related to finding external information desirable enough to justify mildly aversive penalties. This need for clarity and objectivity might account for the development of compulsions despite personal costs.

Post-stimulus encoding of decision confidence in EEG: toward a brain–computer interface for decision making

Objective. When making decisions, humans can evaluate how likely they are to be correct. If this subjective confidence could be reliably decoded from brain activity, it would be possible to build a brain–computer interface (BCI) that improves decision performance by automatically providing more information to the user if needed based on their confidence. But this possibility depends on whether confidence can be decoded right after stimulus presentation and before the response so that a corrective action can be taken in time. Although prior work has shown that decision confidence is represented in brain signals, it is unclear if the representation is stimulus-locked or response-locked, and whether stimulus-locked pre-response decoding is sufficiently accurate for enabling such a BCI. Approach. We investigate the neural correlates of confidence by collecting high-density electroencephalography (EEG) during a perceptual decision task with realistic stimuli. Importantly, we design our task to include a post-stimulus gap that prevents the confounding of stimulus-locked activity by response-locked activity and vice versa, and then compare with a task without this gap. Main results. We perform event-related potential and source-localization analyses. Our analyses suggest that the neural correlates of confidence are stimulus-locked, and that an absence of a post-stimulus gap could cause these correlates to incorrectly appear as response-locked. By preventing response-locked activity from confounding stimulus-locked activity, we then show that confidence can be reliably decoded from single-trial stimulus-locked pre-response EEG alone. We also identify a high-performance classification algorithm by comparing a battery of algorithms. Lastly, we design a simulated BCI framework to show that the EEG classification is accurate enough to build a BCI and that the decoded confidence could be used to improve decision making performance particularly when the task difficulty and cost of errors are high. Significance. Our results show feasibility of non-invasive EEG-based BCIs to improve human decision making.

Conspiracy beliefs are associated with a reduction in frontal beta power and biases in categorizing ambiguous stimuli

Prior beliefs, such as conspiracy beliefs, significantly influence our perception of the natural world. However, the brain activity associated with perceptual decision-making in conspiracy beliefs is not well understood. To shed light on this topic, we conducted a study examining the EEG activity of believers, and skeptics during resting state with perceptual decision-making task. Our study shows that conspiracy beliefs are related to the reduced power of beta frequency band. Furthermore, skeptics tended to misclassify ambiguous face stimuli as houses more frequently than believers. These results help to explain the differences in brain activity between believers and skeptics, especially in how conspiracy beliefs impact the categorization of ambiguous stimuli.

Metacognitive Information Theory.

The capacity that subjects have to rate confidence in their choices is a form of metacognition, and can be assessed according to bias, sensitivity and efficiency. Rich networks of domain-specific and domain-general regions of the brain are involved in the rating, and are associated with its quality and its use for regulating the processes of thinking and acting. Sensitivity and efficiency are often measured by quantities called meta-d' and the M-ratio that are based on reverse engineering the potential accuracy of the original, primary, choice that is implied by the quality of the confidence judgements. Here, we advocate a straightforward measure of sensitivity, called meta-𝓘, which assesses the mutual information between the accuracy of the subject's choices and the confidence reports, and two normalized versions of this measure that quantify efficiency in different regimes. Unlike most other measures, meta-𝓘-based quantities increase with the number of correctly assessed bins with which confidence is reported. We illustrate meta-𝓘 on data from a perceptual decision-making task, and via a simple form of simulated second-order metacognitive observer.

Predictive saccades and decision making in the beetle-predating saffron robber fly.

Internal predictions about the sensory consequences of self-motion, encoded by corollary discharge, are ubiquitous in the animal kingdom, including for fruit flies, dragonflies, and humans. In contrast, predicting the future location of an independently moving external target requires an internal model. With the use of internal models for predictive gaze control, vertebrate predatory species compensate for their sluggish visual systems and long sensorimotor latencies. This ability is crucial for the timely and accurate decisions that underpin a successful attack. Here, we directly demonstrate that the robber fly Laphria saffrana, a specialized beetle predator, also uses predictive gaze control when head tracking potential prey. Laphria uses this predictive ability to perform the difficult categorization and perceptual decision task of differentiating a beetle from other flying insects with a low spatial resolution retina. Specifically, we show that (1) this predictive behavior is part of a saccade-and-fixate strategy, (2) the relative target angular position and velocity, acquired during fixation, inform the subsequent predictive saccade, and (3) the predictive saccade provides Laphria with additional fixation time to sample the frequency of the prey's specular wing reflections. We also demonstrate that Laphria uses such wing reflections as a proxy for the wingbeat frequency of the potential prey and that consecutively flashing LEDs to produce apparent motion elicits attacks when the LED flicker frequency matches that of the beetle's wingbeat cycle.

Integrated control of non-motor and motor efforts during perceptual decision-making and action execution: a pilot study

Humans daily life is characterized by a succession of voluntary actions. Since energy resources are limited, the ability to invest the appropriate amount of effort for selecting and executing these actions is a hallmark of adapted behavior. Recent studies indicate that decisions and actions share important principles, including the optimization of their duration when the context requires it. In the present pilot study, we test the hypothesis that the management of effort-related energy resources is shared between decision and action too. Healthy human subjects performed a perceptual decision task where they had to choose between two levels of effort to invest in making the decision (i.e. two levels of perceptual difficulty), and report it with a reaching movement. Crucially, the movement accuracy requirement gradually increased from trial to trial depending on participants’ decision performance. Results indicate an overall moderate and non-significant impact of the increasing motor difficulty on the choice of the non-motor (decision) effort to invest in each trial and on decision performance. By contrast, motor performance strongly decreased depending on both the motor and decisional difficulties. Together, the results support the hypothesis of an integrated management of the effort-related energy resources between decision and action. They also suggest that in the present task, the mutualized resources are primarily allocated to the decision-making process to the detriment of movements.

Associative memory retrieval modulates upcoming perceptual decisions.

Expectations can inform fast, accurate decisions. But what informs expectations? Here we test the hypothesis that expectations are set by dynamic inference from memory. Participants performed a cue-guided perceptual decision task with independently-varying memory and sensory evidence. Cues established expectations by reminding participants of past stimulus-stimulus pairings, which predicted the likely target in a subsequent noisy image stream. Participant's responses used both memory and sensory information, in accordance to their relative reliability. Formal model comparison showed that the sensory inference was best explained when its parameters were set dynamically at each trial by evidence sampled from memory. Supporting this model, neural pattern analysis revealed that responses to the probe were modulated by the specific content and fidelity of memory reinstatement that occurred before the probe appeared. Together, these results suggest that perceptual decisions arise from the continuous sampling of memory and sensory evidence.

Stabilizing expectations when shifting from analytical to intuitive reasoning: The role of prediction errors in reasoning

As humans, we rely on intuitive reasoning for most of our decisions. However, when there is a novel or atypical decision to be made, we must rely on a slower and more deliberative thought process—analytical reasoning. As we gain experience with these novel or atypical decisions, our reasoning shifts from analytical to intuitive, which parallels a reduction in the need for cognitive control. Here, we sought to confirm this claim by employing electroencephalographic (EEG) measures of cognitive control as participants performed a simple perceptual decision-making task. Specifically, we had participants categorize “blobs” into families based on their visual attributes so we could examine how their reasoning changed with learning. In a key manipulation, halfway through the experiment we introduced novel blob families to categorize, thus temporarily increasing the need for analytical reasoning (i.e., cognitive control). Congruent with past research, we focused our EEG analyses on frontal theta activity as it has been linked to cognitive control and analytical thinking. As hypothesized, we found a transition from analytical to intuitive decision-making systems with learning as indexed by a decrease in frontal theta power. Further, when the novel blobs were introduced at the midpoint of the experiment, we found that decisions about these stimuli recruited analytical reasoning as indicated by increased theta power in comparison to decisions about well-practiced stimuli. We propose our findings to reflect prediction errors to decision demands—a monitoring process that determines whether our expectations of demands are met. Shifting from analytical to intuitive reasoning thus reflects the stabilization of our expectations of decision demands, which can be violated with unexpected demands when encountering novel stimuli.