Perceptual Decision-making Task Research Articles

Learning-induced uncertainty reduction in perceptual decisions is task-dependent.

Perceptual decision-making in which decisions are reached primarily from extracting and evaluating sensory information requires close interactions between the sensory system and decision-related networks in the brain. Uncertainty pervades every aspect of this process and can be considered related to either the stimulus signal or decision criterion. Here, we investigated the learning-induced reduction of both the signal and criterion uncertainty in two perceptual decision tasks based on two Glass pattern stimulus sets. This was achieved by manipulating spiral angle and signal level of radial and concentric Glass patterns. The behavioral results showed that the participants trained with a task based on criterion comparison improved their categorization accuracy for both tasks, whereas the participants who were trained on a task based on signal detection improved their categorization accuracy only on their trained task. We fitted the behavioral data with a computational model that can dissociate the contribution of the signal and criterion uncertainties. The modeling results indicated that the participants who were trained on the criterion comparison task reduced both the criterion and signal uncertainty. By contrast, the participants who were trained on the signal detection task only reduced their signal uncertainty after training. Our results suggest that the signal uncertainty can be resolved by training participants to extract signals from noisy environments and to discriminate between clear signals, which are evidenced by reduced perception variance after both training procedures. Conversely, the criterion uncertainty can only be resolved by the training of fine discrimination. These findings demonstrate that uncertainty in perceptual decision-making can be reduced with training but that the reduction of different types of uncertainty is task-dependent.

The Cat is on the Mat. or is it a Dog? Dynamic Competition in Perceptual Decision Making

Recent neurobiological findings suggest that the brain solves simple perceptual decision-making tasks by means of a dynamic competition in which evidence is accumulated in favor of the alternatives. However, it is unclear if and how the same process applies in more complex, real-world tasks, such as the categorization of ambiguous visual scenes and what elements are considered as evidence in this case. Furthermore, dynamic decision models typically consider evidence accumulation as a passive process disregarding the role of active perception strategies. In this paper, we adopt the principles of dynamic competition and active vision for the realization of a biologically-motivated computational model, which we test in a visual categorization task. Moreover, our system uses predictive power of the features as the main dimension for both evidence accumulation and the guidance of active vision. Comparison of human and synthetic data in a common experimental setup suggests that the proposed model captures essential aspects of how the brain solves perceptual ambiguities in time. Our results point to the importance of the proposed principles of dynamic competition, parallel specification, and selection of multiple alternatives through prediction, as well as active guidance of perceptual strategies for perceptual decision-making and the resolution of perceptual ambiguities. These principles could apply to both the simple perceptual decision problems studied in neuroscience and the more complex ones addressed by vision research.

Joint perceptual decision-making: a case study in explanatory pluralism.

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches.

Does interaction matter? Testing whether a confidence heuristic can replace interaction in collective decision-making

In a range of contexts, individuals arrive at collective decisions by sharing confidence in their judgements. This tendency to evaluate the reliability of information by the confidence with which it is expressed has been termed the 'confidence heuristic'. We tested two ways of implementing the confidence heuristic in the context of a collective perceptual decision-making task: either directly, by opting for the judgement made with higher confidence, or indirectly, by opting for the faster judgement, exploiting an inverse correlation between confidence and reaction time. We found that the success of these heuristics depends on how similar individuals are in terms of the reliability of their judgements and, more importantly, that for dissimilar individuals such heuristics are dramatically inferior to interaction. Interaction allows individuals to alleviate, but not fully resolve, differences in the reliability of their judgements. We discuss the implications of these findings for models of confidence and collective decision-making.

The left inferior frontal gyrus is involved in adjusting response bias during a perceptual decision‐making task

IntroductionChanging the way we make decisions from one environment to another allows us to maintain optimal decision-making. One way decision-making may change is how biased one is toward one option or another. Identifying the regions of the brain that underlie the change in bias will allow for a better understanding of flexible decision-making.MethodsAn event-related, perceptual decision-making task where participants had to detect a picture of an animal amongst distractors was used during functional magnetic resonance imaging. Positive and negative financial motivation were used to affect a change in response bias, and changes in decision-making behavior were quantified using signal detection theory.ResultsResponse bias became relatively more liberal during both positive and negative motivated trials compared to neutral trials. For both motivational conditions, the larger the liberal shift in bias, the greater the left inferior frontal gyrus (IFG) activity. There was no relationship between individuals' belief that they used a different strategy and their actual change in response bias.ConclusionsThe present findings suggest that the left IFG plays a role in adjusting response bias across different decision environments. This suggests a potential role for the left IFG in flexible decision-making.

Procedures for Behavioral Experiments in Head-Fixed Mice

The mouse is an increasingly prominent model for the analysis of mammalian neuronal circuits. Neural circuits ultimately have to be probed during behaviors that engage the circuits. Linking circuit dynamics to behavior requires precise control of sensory stimuli and measurement of body movements. Head-fixation has been used for behavioral research, particularly in non-human primates, to facilitate precise stimulus control, behavioral monitoring and neural recording. However, choice-based, perceptual decision tasks by head-fixed mice have only recently been introduced. Training mice relies on motivating mice using water restriction. Here we describe procedures for head-fixation, water restriction and behavioral training for head-fixed mice, with a focus on active, whisker-based tactile behaviors. In these experiments mice had restricted access to water (typically 1 ml/day). After ten days of water restriction, body weight stabilized at approximately 80% of initial weight. At that point mice were trained to discriminate sensory stimuli using operant conditioning. Head-fixed mice reported stimuli by licking in go/no-go tasks and also using a forced choice paradigm using a dual lickport. In some cases mice learned to discriminate sensory stimuli in a few trials within the first behavioral session. Delay epochs lasting a second or more were used to separate sensation (e.g. tactile exploration) and action (i.e. licking). Mice performed a variety of perceptual decision tasks with high performance for hundreds of trials per behavioral session. Up to four months of continuous water restriction showed no adverse health effects. Behavioral performance correlated with the degree of water restriction, supporting the importance of controlling access to water. These behavioral paradigms can be combined with cellular resolution imaging, random access photostimulation, and whole cell recordings.

Copy Alert: A Method and Metric to Detect Visual Copycat Brands

The authors propose a method and metric to quantify the consumer confusion between leading brands and copycat brands that results from the visual similarity of their packaging designs. The method has three components. First, image processing techniques establish the objective similarity of the packages of leading and copycat brands on the basis of their colors and textures. Second, a perceptual decision task (triangle test) assesses the accuracy and speed with which consumers can identify differences between brands from rapidly (300 milliseconds) flashed images of their packages. Third, a competing accumulator model describes the buildup of evidence on each of the alternative brands during consumers’ perceptual decisions and predicts the accuracy and response time of brand identification. Jointly, these components establish the impact of copycat packaging's visual features on consumer confusion. The method is applied in a test of experimentally designed copycats and market copycats in 15 product categories. A three-tiered metric (“copy alert,” “copy watch,” and “copy safe”) establishes the extent to which copycat brands imitate the package designs of target brands and identifies which visual features are responsible.

Adaptive Sampling of Information in Perceptual Decision-Making

In many perceptual and cognitive decision-making problems, humans sample multiple noisy information sources serially, and integrate the sampled information to make an overall decision. We derive the optimal decision procedure for two-alternative choice tasks in which the different options are sampled one at a time, sources vary in the quality of the information they provide, and the available time is fixed. To maximize accuracy, the optimal observer allocates time to sampling different information sources in proportion to their noise levels. We tested human observers in a corresponding perceptual decision-making task. Observers compared the direction of two random dot motion patterns that were triggered only when fixated. Observers allocated more time to the noisier pattern, in a manner that correlated with their sensory uncertainty about the direction of the patterns. There were several differences between the optimal observer predictions and human behaviour. These differences point to a number of other factors, beyond the quality of the currently available sources of information, that influences the sampling strategy.

An Optimal Decision Population Code that Accounts for Correlated Variability Unambiguously Predicts a Subject’s Choice

Decisions emerge from the concerted activity of neuronal populations distributed across brain circuits. However, the analytical tools best suited to decode decision signals from neuronal populations remain unknown. Here we show that knowledge of correlated variability between pairs of cortical neurons allows perfect decoding of decisions from population firing rates. We recorded pairs of neurons from secondary somatosensory (S2) and premotor (PM) cortices while monkeys reported the presence or absence of a tactile stimulus. We found that while populations of S2 and sensory-like PM neurons are only partially correlated with behavior, those PM neurons active during a delay period preceding the motor report predict unequivocally the animal's decision report. Thus, a population rate code that optimally reveals a subject's perceptual decisions can be implemented just by knowing the correlations of PM neurons representing decision variables.

Linking sensory neurons to visually guided behavior: relating MST activity to steering in a virtual environment.

Many complex behaviors rely on guidance from sensations. To perform these behaviors, the motor system must decode information relevant to the task from the sensory system. However, identifying the neurons responsible for encoding the appropriate sensory information remains a difficult problem for neurophysiologists. A key step toward identifying candidate systems is finding neurons or groups of neurons capable of representing the stimuli adequately to support behavior. A traditional approach involves quantitatively measuring the performance of single neurons and comparing this to the performance of the animal. One of the strongest pieces of evidence in support of a neuronal population being involved in a behavioral task comes from the signals being sufficient to support behavior. Numerous experiments using perceptual decision tasks show that visual cortical neurons in many areas have this property. However, most visually guided behaviors are not categorical but continuous and dynamic. In this article, we review the concept of sufficiency and the tools used to measure neural and behavioral performance. We show how concepts from information theory can be used to measure the ongoing performance of both neurons and animal behavior. Finally, we apply these tools to dorsal medial superior temporal (MSTd) neurons and demonstrate that these neurons can represent stimuli important to navigation to a distant goal. We find that MSTd neurons represent ongoing steering error in a virtual-reality steering task. Although most individual neurons were insufficient to support the behavior, some very nearly matched the animal's estimation performance. These results are consistent with many results from perceptual experiments and in line with the predictions of Mountcastle's "lower envelope principle."

Social Influence and Perceptual Decision Making

Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria.

A Laboratory Investigation of Anxious Cognition: How Subliminal Cues Alter Perceptual Sensitivity to Threat

Emotional stimuli represent a category of signals that are relevant for survival. This relevance is reflected in the prioritization of threatening over neutral information, which has been demonstrated for inherently threatening stimuli and stimuli with acquired affective significance. The present study aimed to investigate whether threatening cues presented without conscious awareness have an impact on perceptual judgements. For this purpose, neutral or angry facial expressions associated with prior congruent (Experiment 1), incongruent (Experiment 3) or no aversive learning (Experiment 2) were presented subliminally in a perceptual decision task. During the task, subjects rated mask faces that varied in emotion intensity ranging from neutral to angry. Subjects tended to make more “angry” responses only when the subliminal stimulus was angry and had been previously paired with an aversive experience. These findings may have direct clinical relevance because similar mechanisms could account for cognitive biases in anxiety disorders.

Effect of decision confidence on the evaluation of conflicting decisions in a social context

Conflicts with others about decisions are reflected in the medial frontal negativity (MFN), which is a component of the event-related brain potential (ERP). The present study examined how decision confidence in a perceptual decision task modulated the ERP components elicited by decision conflicts with others. In a motion discrimination task, participants were randomly assigned to an easy or a difficult group that differed in coherence levels of the moving dots. Participants were paired with a confederate and presented the confederate's decision about the motion direction of the moving dots, which was either congruent or incongruent with the participants’ decision. MFN was elicited by the incongruent confederate's decision and its amplitude did not differ between groups. A larger P300 amplitude was elicited by incongruent decisions in the easy group, whereas the P300 amplitude did not differ between congruent and incongruent decisions in the difficult group. These results indicate the functional dissociation between MFN and P300 in the evaluation of social feedback. It is suggested that MFN might reflect automatic detection of conflicts about decisions, whereas the P300 might detect the deviation from internal expectations regarding other's decisions.

‘If you are good, I get better’: the role of social hierarchy in perceptual decision-making

So far, it was unclear if social hierarchy could influence sensory or perceptual cognitive processes. We evaluated the effects of social hierarchy on these processes using a basic visual perceptual decision task. We constructed a social hierarchy where participants performed the perceptual task separately with two covertly simulated players (superior, inferior). Participants were faster (better) when performing the discrimination task with the superior player. We studied the time course when social hierarchy was processed using event-related potentials and observed hierarchical effects even in early stages of sensory-perceptual processing, suggesting early top-down modulation by social hierarchy. Moreover, in a parallel analysis, we fitted a drift-diffusion model (DDM) to the results to evaluate the decision making process of this perceptual task in the context of a social hierarchy. Consistently, the DDM pointed to nondecision time (probably perceptual encoding) as the principal period influenced by social hierarchy.

Impairment in Flexible Regulation of Speed and Accuracy in Children with ADHD

Attention deficit hyperactivity disorder (ADHD) is characterized by poor adaptation of behavior to environmental demands, including difficulties in flexibly regulating behavior. To understand whether ADHD is associated with a reduction of strategic flexibility in modulating speed and accuracy, we used a perceptual decision-making task that required participants to randomly stress either fast or accurate responding. Thirty-one drug-free boys with ADHD combined-type (mean age: 10.2 years) and 33 healthy control boys (mean age: 10.7 years), matched for age and IQ, participated. Both reaction time and accuracy data were analyzed. Our findings demonstrated significantly lower accuracy in ADHD children than in controls when switching from speed to accuracy instructions. This deficit was directly associated with hyperactivity symptoms but not with inattention. Our results showed that ADHD is associated with a deficit in dynamically switching response strategy according to task demands on a trial-to-trial basis.

Choosing the rules: distinct and overlapping frontoparietal representations of task rules for perceptual decisions.

Behavior is governed by rules that associate stimuli with responses and outcomes. Human and monkey studies have shown that rule-specific information is widely represented in the frontoparietal cortex. However, it is not known how establishing a rule under different contexts affects its neural representation. Here, we use event-related functional MRI (fMRI) and multivoxel pattern classification methods to investigate the human brain's mechanisms of establishing and maintaining rules for multiple perceptual decision tasks. Rules were either chosen by participants or specifically instructed to them, and the fMRI activation patterns representing rule-specific information were compared between these contexts. We show that frontoparietal regions differ in the properties of their rule representations during active maintenance before execution. First, rule-specific information maintained in the dorsolateral and medial frontal cortex depends on the context in which it was established (chosen vs specified). Second, rule representations maintained in the ventrolateral frontal and parietal cortex are independent of the context in which they were established. Furthermore, we found that the rule-specific coding maintained in anticipation of stimuli may change with execution of the rule: representations in context-independent regions remain invariant from maintenance to execution stages, whereas rule representations in context-dependent regions do not generalize to execution stage. The identification of distinct frontoparietal systems with context-independent and context-dependent task rule representations, and the distinction between anticipatory and executive rule representations, provide new insights into the functional architecture of goal-directed behavior.

The role of neural correlations in a decision-making task

Simultaneous recordings of the firing activity of pairs of cortical neurons have shown that spike-count correlation coefficients (CCs) cover a wide range of values. According to recent theoretical and experimental work [1,2] recurrent cortical networks decorrelate neural activity producing very low CCs. However little is known about the origin of correlations and data analysis based on recordings of cortical activity of awake, behaving animals performing non-trivial tasks are scarce. In this study, we aim to understand the role of neural correlations in perceptual decision-making tasks and its relationship with the covariation between neural firing activity and behavior. We examine spike-count correlations obtained from pairs of simultaneously recorded premotor cortex (PC) neurons while trained monkeys performed a vibrotactile detection task in which the stimulus was often absent or weak, and the time of its application was variable [3,4]. By analyzing firing rates and correlated variability we show that behavioral outcomes are crucially affected by the state of cortical networks before stimulus onset times. Our results suggest that sensory detection is partly due to a purely internal signal whereas the stimulus, if finally applied, adds a contribution to this initial processing later on [5]. Noise correlations can be weak; their smallest values are attained at the end of the delay period of the task. Importantly, we found that small CCs are compatible with high firing rates. Although the firing rate in hit trials is higher than in correct rejections, the distributions of CCs over the population of pairs are similar, presenting mean values of 0.06. Moreover, the CCs do not covary with the geometrical mean of the firing rate of the pair. The observation that single neurons covary with the subject's response (characterized by the choice probability index, CP) is usually explained by the existence of variability correlations among the cells in a neuronal population [6]. Here we show a simple approximate expression that explicitly relates the population-averaged CP index and the CCs. This expression shows that the CP index is different from 0.5 when CCs evaluated using all trials differ from choice-conditioned correlations. Neurons could covary significantly with behavior even if the latter are very small. Thus, we show that there is no contradiction between the correlated activity required for the non-chance CP index and the small correlations produced by decorrelation in recurrent networks. Although the CP index is useful to study the role of single neurons in decision-making tasks, in reality, the decision is formed through the coordinated action of several pools of neurons. Hence, the relevant quantities to investigate the elaboration of the choice are population variables combining the activity of several pools. By extending the notion of CP from single neurons to neural pools, we defined the CPN index to quantify the amount of covariation with behavior of arbitrary linear combinations of oppositely-tuned neural pools. We found that pools of PC neurons exhibiting persistent activity become fully correlated with the subject's choice soon after stimulus onset and during the entire delay period of the task.

Distinct patterns of functional brain connectivity correlate with objective performance and subjective beliefs.

The degree of correspondence between objective performance and subjective beliefs varies widely across individuals. Here we demonstrate that functional brain network connectivity measured before exposure to a perceptual decision task covaries with individual objective (type-I performance) and subjective (type-II performance) accuracy. Increases in connectivity with type-II performance were observed in networks measured while participants directed attention inward (focus on respiration), but not in networks measured during states of neutral (resting state) or exogenous attention. Measures of type-I performance were less sensitive to the subjects' specific attentional states from which the networks were derived. These results suggest the existence of functional brain networks indexing objective performance and accuracy of subjective beliefs distinctively expressed in a set of stable mental states.

Corticostriatal neurons in auditory cortex drive decisions during auditory discrimination

The neural pathways by which information about the acoustic world reaches the auditory cortex are well characterised, but how auditory representations are transformed into motor commands is not known. Here we have used a perceptual decision-making task to study this transformation. We directly demonstrate the role of corticostriatal projection neurones in auditory decisions by specifically manipulating the activity of these neurones in rats performing an auditory frequency discrimination task. Targeted Channelrhodopsin-21,2 (ChR2)-mediated stimulation of corticostriatal neurones during the task biased decisions in the direction predicted by the frequency tuning of the stimulated neurones, whereas archaerhodopsin-33 (Arch)-mediated inactivation biased decisions in the opposite direction. Striatal projections are widespread in cortex and may provide a general mechanism for the control of motor decisions by sensory cortex.

Cortico-subthalamic connection predicts individual differences in value-driven choice bias

It has been suggested that a connection between the STN and value-sensitive areas of the prefrontal cortex might mediate value-based actions in perceptual decision making. In this study, we first seek to quantify a structural connection between the STN and a cortical region that was associated with mechanisms underlying bias in choice behavior (vmPFC). Next, we tested whether individual differences in the probabilistic tract-strength of this connection were predictive for individual differences in the magnitude of bias in a perceptual decision-making task. Probabilistic tractography was used to measure the tract-strength between the STN and the vmPFC. Bias was quantified using an accumulation-to-bound model where a shift in the starting point of the accumulation of sensory evidence causes faster and more choices for an alternative that is more likely or more valuable. Results show that vmPFC is structurally connected with the STN and that the strength of this connection is predictive for choice bias towards an alternative that is more valuable, but not for choice bias towards an alternative that is more likely. These findings confirm the involvement of the cortico-subthalamic circuit in mechanisms underlying value-based actions in perceptual decision making.