The neural processes underlying perceptual decision making in humans: Recent progress and future directions

Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.

Parsing the neural signatures of reduced error detection in older age

Recent work has demonstrated that explicit error detection relies on a neural evidence accumulation process that can be traced in the human electroencephalogram (EEG). Here, we sought to establish the impact of natural aging on this process by recording EEG from young (18-35 years) and older adults (65-88 years) during the performance of a Go/No-Go paradigm in which participants were required to overtly signal their errors. Despite performing the task with equivalent accuracy, older adults reported substantially fewer errors, and the timing of their reports were both slower and more variable. These behavioral differences were linked to three key neurophysiological changes reflecting distinct parameters of the error detection decision process: a reduction in medial frontal delta/theta (2-7 Hz) activity, indicating diminished top-down input to the decision process; a slower rate of evidence accumulation as indexed by the rate of rise of a centro-parietal signal, known as the error positivity; and a higher motor execution threshold as indexed by lateralized beta-band (16-30 Hz) activity. Our data provide novel insight into how the natural aging process affects the neural underpinnings of error detection.

Abstract and Effector-Selective Decision Signals Exhibit Qualitatively Distinct Dynamics before Delayed Perceptual Reports

Electrophysiological research has isolated neural signatures of decision formation in a variety of brain regions. Studies in rodents and monkeys have focused primarily on effector-selective signals that translate the emerging decision into a specific motor plan, but, more recently, research on the human brain has identified an abstract signature of evidence accumulation that does not appear to play any direct role in action preparation. The functional dissociations between these distinct signal types have only begun to be characterized, and their dynamics during decisions with deferred actions with or without foreknowledge of stimulus-effector mapping, a commonly studied task scenario in single-unit and functional imaging investigations, have not been established. Here we traced the dynamics of distinct abstract and effector-selective decision signals in the form of the broad-band centro-parietal positivity (CPP) and limb-selective β-band (8-16 and 18-30 Hz) EEG activity, respectively, during delayed-reported motion direction decisions with and without foreknowledge of direction-response mapping. With foreknowledge, the CPP and β-band signals exhibited a similar gradual build-up following evidence onset, but whereas choice-predictive β-band activity persisted up until the delayed response, the CPP dropped toward baseline after peaking. Without foreknowledge, the CPP exhibited identical dynamics, whereas choice-selective β-band activity was eliminated. These findings highlight qualitative functional distinctions between effector-selective and abstract decision signals and are of relevance to the assumptions founding functional neuroimaging investigations of decision-making.

SIGNIFICANCE STATEMENT

Neural signatures of evidence accumulation have been isolated in numerous brain regions. Although animal neurophysiology has largely concentrated on effector-selective decision signals that translate the emerging decision into a specific motor plan, recent research on the human brain has isolated abstract neural signatures of decision formation that are independent of specific sensory and motor requirements. Here, we examine the functional distinctions between the two distinct classes of decision variable signal during decisions with deferred actions with and without foreknowledge of stimulus-effector mapping. We find salient distinctions in the dynamics of abstract versus effector-selective decision signals in the human brain, in terms of sustainment through response delays and contingency on foreknowledge of stimulus-response mapping.

Decision ambiguity is mediated by a late positive potential originating from cingulate cortex

People often make decisions in the face of ambiguous information, but it remains unclear how ambiguity is represented in the brain. We used three types of ambiguous stimuli and combined EEG and fMRI to examine the neural representation of perceptual decisions under ambiguity. We identified a late positive potential, the LPP, which differentiated levels of ambiguity, and which was specifically associated with behavioral judgments about choices that were ambiguous, rather than passive perception of ambiguous stimuli. Mediation analyses together with two further control experiments confirmed that the LPP was generated only when decisions are made (not during mere perception of ambiguous stimuli), and only when those decisions involved choices on a dimension that is ambiguous. A further control experiment showed that a stronger LPP arose in the presence of ambiguous stimuli compared to when only unambiguous stimuli were present. Source modeling suggested that the LPP originated from multiple loci in cingulate cortex, a finding we further confirmed using fMRI and fMRI-guided ERP source prediction. Taken together, our findings argue for a role of an LPP originating from cingulate cortex in encoding decisions based on task-relevant perceptual ambiguity, a process that may in turn influence confidence judgment, response conflict, and error correction.

Large-scale network dynamics of beta-band oscillations underlie auditory perceptual decision-making

Perceptual decisions vary in the speed at which we make them. Evidence suggests that translating sensory information into perceptual decisions relies on distributed interacting neural populations, with decision speed hinging on power modulations of the neural oscillations. Yet the dependence of perceptual decisions on the large-scale network organization of coupled neural oscillations has remained elusive. We measured magnetoencephalographic signals in human listeners who judged acoustic stimuli composed of carefully titrated clouds of tone sweeps. These stimuli were used in two task contexts, in which the participants judged the overall pitch or direction of the tone sweeps. We traced the large-scale network dynamics of the source-projected neural oscillations on a trial-by-trial basis using power-envelope correlations and graph-theoretical network discovery. In both tasks, faster decisions were predicted by higher segregation and lower integration of coupled beta-band (∼16-28 Hz) oscillations. We also uncovered the brain network states that promoted faster decisions in either lower-order auditory or higher-order control brain areas. Specifically, decision speed in judging the tone sweep direction critically relied on the nodal network configurations of anterior temporal, cingulate, and middle frontal cortices. Our findings suggest that global network communication during perceptual decision-making is implemented in the human brain by large-scale couplings between beta-band neural oscillations.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects' decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings.NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making.

Global gain modulation generates time-dependent urgency during perceptual choice in humans

Decision-makers must often balance the desire to accumulate information with the costs of protracted deliberation. Optimal, reward-maximizing decision-making can require dynamic adjustment of this speed/accuracy trade-off over the course of a single decision. However, it is unclear whether humans are capable of such time-dependent adjustments. Here, we identify several signatures of time-dependency in human perceptual decision-making and highlight their possible neural source. Behavioural and model-based analyses reveal that subjects respond to deadline-induced speed pressure by lowering their criterion on accumulated perceptual evidence as the deadline approaches. In the brain, this effect is reflected in evidence-independent urgency that pushes decision-related motor preparation signals closer to a fixed threshold. Moreover, we show that global modulation of neural gain, as indexed by task-related fluctuations in pupil diameter, is a plausible biophysical mechanism for the generation of this urgency. These findings establish context-sensitive time-dependency as a critical feature of human decision-making.

Decision-making balances the benefits of additional information with the cost of time, but it is unclear whether humans adjust this balance within individual decisions. Here, authors show that we do make such adjustments to suit contextual demands and suggest that these are driven by modulation of neural gain.

Preventing (impulsive) errors: Electrophysiological evidence for online inhibitory control over incorrect responses

In a rich environment, with multiple action affordances, selective action inhibition is critical in preventing the execution of inappropriate responses. Here, we studied the origin and the dynamics of incorrect response inhibition and how it can be modulated by task demands. We used EEG in a conflict task where the probability of compatible and incompatible trials was varied. This allowed us to modulate the strength of the prepotent response, and hence to increase the risk of errors, while keeping the probability of the two responses equal. The correct response activation and execution was not affected by compatibility or by probability. In contrast, incorrect response inhibition in the primary motor cortex ipsilateral to the correct response was more pronounced on incompatible trials, especially in the condition where most of the trials were compatible, indicating a modulation of inhibitory strength within the course of the action. Two prefrontal activities, one medial and one lateral, were also observed before the response, and their potential links with the observed inhibitory pattern observed are discussed.

Decisions Made with Less Evidence Involve Higher Levels of Corticosubthalamic Nucleus Theta Band Synchrony

The switch between automatic action selection and more controlled forms of decision-making is a dynamic process thought to involve both cortical and subcortical structures. During sensory conflict, medial pFC oscillations in the theta band (<8 Hz) drive those of the subthalamic nucleus (STN), and this is thought to increase the threshold of evidence needed for one competing response to be selected over another. Here, we were interested in testing whether STN activity is also altered by the rate at which evidence is presented during a congruent dot motion task absent of any explicit sensory conflict. By having a series of randomly moving dots gradually transform to congruent motion at three different rates (slow, medium, fast), we were able to show that a slower rate increased the time it took participants to make a response but did not alter the total amount of evidence that was integrated before the response. Notably, this resulted in a decision being made with a lower amount of instantaneous evidence during the slow and medium trials. Consistent with the idea that medial pFC-STN activity is involved in executing cognitive control, the higher levels of ambiguity during these trials were associated with increased theta band synchrony between the cortex and the STN, with the cortical oscillations Granger-causal to those of the STN. These results further confirm the involvement of the STN in decision-making and suggest that the disruption of this network may underlie some of the unwanted cognitive deficits associated with STN deep brain stimulation.

Neural evidence accumulation persists after choice to inform metacognitive judgments

The ability to revise one’s certainty or confidence in a preceding choice is a critical feature of adaptive decision-making but the neural mechanisms underpinning this metacognitive process have yet to be characterized. In the present study, we demonstrate that the same build-to-threshold decision variable signal that triggers an initial choice continues to evolve after commitment, and determines the timing and accuracy of self-initiated error detection reports by selectively representing accumulated evidence that the preceding choice was incorrect. We also show that a peri-choice signal generated in medial frontal cortex provides a source of input to this post-decision accumulation process, indicating that metacognitive judgments are not solely based on the accumulation of feedforward sensory evidence. These findings impart novel insights into the generative mechanisms of metacognition.

DOI:http://dx.doi.org/10.7554/eLife.11946.001

Reflecting on our previous choices and accurately representing our confidence in their accuracy allows us to detect, correct and learn from our errors. Yet, it remains poorly understood how such “metacognition”, or thoughts about thoughts, occurs in the human brain. In particular, a long-standing debate in this area of research concerns whether metacognitive processes in the brain occur at the same time as those that determine the actual choice, or whether they develop after the choice has been made and rely on different information.

Now, Murphy et al. have recorded brain activity in human volunteers who were carrying out a simple task in order to explore metacognition. In short, the volunteers looked at colored words and decided if each word matched its color (e.g., is the word ‘RED’ also written in a red font?). At the same time, the volunteers chose whether or not to press a button depending on the specific color/word combination shown, and most importantly reported whenever they noticed that they made an error in the task.

This approach allowed Murphy et al. to chart the development of choices and detection of errors as they occurred in the volunteers’ brains. This revealed that the metacognitive judgement about each choice relied on information that was gathered after the point the initial choice was made. Further analysis then suggested that this process relies, at least in part, on a signal generated in a region at the front of the brain.

Together, these findings suggest that metacognitive decisions rely on processes that are similar to those behind other decisions, but with a few important differences. Namely, the metacognitive process plays out at a different point in time, and likely incorporates distinct sources of information. Further work should aim to clarify the nature of these sources of information and describe their specific contributions to the process.

DOI:http://dx.doi.org/10.7554/eLife.11946.002

The classic P300 encodes a build-to-threshold decision variable

The P300 component of the human event-related potential has been the subject of intensive experimental investigation across a five-decade period, owing to its apparent relevance to a wide range of cognitive functions and its sensitivity to numerous brain disorders, yet its exact contribution to cognition remains unresolved. Here, we carry out key analyses of the P300 elicited by transient auditory and visual targets to examine its potential role as a 'decision variable' signal that accumulates evidence to a decision bound. Consistent with the latter, we find that the P300 reaches a stereotyped amplitude immediately prior to response execution and that its rate of rise scales with target detection difficulty and accounts for trial-to-trial variance in RT. Computational simulations of an accumulation-to-bound decision process faithfully captured P300 dynamics when its parameters were set by model fits to the RT distributions. Thus, where the dominant explanatory accounts have conceived of the P300 as a unitary neural event, our data reveal it to be a dynamically evolving neural signature of decision formation. These findings place the P300 at the heart of a mechanistically principled framework for understanding decision-making in both the typical and atypical human brain.