Decisions are expedited through multiple neural adjustments spanning the sensorimotor hierarchy

The respiratory cycle modulates distinct dynamics of affective and perceptual decision-making

Breathing plays a critical role not only in homeostatic survival, but also in modulating other non-interoceptive perceptual and affective processes. Recent evidence from both human and rodent models indicates that neural and behavioural oscillations are influenced by respiratory state as breathing cycles from inspiration to expiration. To explore the mechanisms behind these effects, we carried out a psychophysical experiment where 41 participants categorised dot motion and facial emotion stimuli in a standardised discrimination task. When comparing behaviour across respiratory states, we found that inspiration accelerated responses in both domains. We applied a hierarchical evidence accumulation model to determine which aspects of the latent decision process best explained this acceleration. Computational modelling showed that inspiration reduced evidential decision boundaries, such that participants prioritised speed over accuracy in the motion task. In contrast, inspiration shifted the starting point of affective evidence accumulation, inducing a bias towards categorising facial expressions as more positive. These findings provide a novel computational account of how breathing modulate distinct aspects of perceptual and affective decision-dynamics.

Transcutaneous vagus nerve stimulation boosts accuracy during perceptual decision-making

BACKGROUND

The locus coeruleus-norepinephrine (LC-NE) system is a well-established regulator of behavior, yet its precise role remains unclear. Animal studies predominantly support a "gain" hypothesis, suggesting that the LC-NE system enhances sensory processing. In contrast, human studies have proposed an alternative "urgency" hypothesis, postulating that LC-NE primarily accelerates responses.

METHOD

To address this discrepancy, we administered transcutaneous vagus nerve stimulation (tVNS) in two experiments. In the first experiment (n = 22), we showed that 4-s tVNS trains reliably induced greater pupil dilation compared to SHAM condition, indicating increased LC-NE activity. In the second experiment (n = 21), we applied tVNS during a random dot motion task to assess its impact on perceptual decision-making.

RESULT

tVNS improved accuracy without affecting reaction times, which appears inconsistent with the "urgency" hypothesis. Exploratory drift-diffusion model analyses further support the "gain" hypothesis, revealing that tVNS increased the drift rate, indicative of enhanced evidence accumulation. Both accuracy and drift-rate improvements were most prominent following errors and especially pronounced in participants who exhibited post-error declines in these measures under SHAM.

CONCLUSION

Our findings align with the "gain" hypothesis, with tentative evidence suggesting that the impact of LC-NE activity adapts to task demands. Accordingly, tVNS showed the strongest effects in contexts prone to accuracy declines, possibly reflecting attentional disengagement, which points to a role of LC in mitigating lapses of attention.

Disentangling sources of variability in decision-making

Even the most highly-trained observers presented with identical choice-relevant stimuli will reliably exhibit substantial trial-to-trial variability in the timing and accuracy of their choices. Despite being a pervasive feature of choice behaviour and a prominent phenotype for numerous clinical disorders, the capability to disentangle the sources of such intra-individual variability (IIV) remains limited. In principle, computational models of decision-making offer a means of parsing and estimating these sources, but methodological limitations have prevented this potential from being fully realized in practice. In this Review, we first discuss current limitations of algorithmic models for understanding variability in decision-making behaviour. We then highlight recent advances in behavioural paradigm design, novel analyses of cross-trial behavioural and neural dynamics, and the development of neurally grounded computational models that are now making it possible to link distinct components of IIV to well-defined neural processes. Taken together, we demonstrate how these methods are opening up new avenues for systematically analysing the neural origins of IIV, paving the way for a more refined, holistic understanding of decision-making in health and disease.

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory

Subcortical nuclei of the ascending arousal system (AAS) play an important role in regulating brain and cognition. However, functional MRI (fMRI) of these nuclei in humans involves unique challenges due to their size and location deep within the brain. Here, we used ultra-high-field MRI and other methodological advances to investigate the activity of 6 subcortical nuclei during reward anticipation and memory encoding: the locus coeruleus (LC), basal forebrain, median and dorsal raphe nuclei, substantia nigra, and ventral tegmental area. Participants performed a monetary incentive delay task, which successfully induced a state of reward anticipation, and a 24-h delayed surprise memory test. Region-of-interest analyses revealed that activity in all subcortical nuclei increased in anticipation of potential rewards as opposed to neutral outcomes. In contrast, activity in none of the nuclei predicted memory performance 24 h later. These findings provide new insights into the cognitive functions that are supported by the human AAS.

Limited Evidence for Probabilistic Cueing Effects on Grating-Evoked Event-Related Potentials and Orientation Decoding Performance

We can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature-selective neurons in the visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesized effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus-evoked responses in the visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n = 48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating-evoked event-related potentials. Multivariate classifiers trained to discriminate between grating orientations performed better when classifying 10% compared to 90% probability gratings. However, classification performance did not substantively differ across any other stimulus expectancy conditions. Our findings provide very limited evidence for modulations of prediction error signaling by probabilistic expectations as specified in contemporary predictive coding models.

Dissociable encoding of evolving beliefs and momentary belief updates in distinct neural decision signals

Making accurate decisions in noisy environments requires integrating evidence over time. Studies of simple perceptual decisions in static environments have identified two human neurophysiological signals that evolve with similar integration dynamics, with one - the centroparietal positivity - appearing to compute the running integral and continuously feed it to the other - motor beta lateralisation. However, it remains unknown whether and how these signals serve more distinct functional roles in more complex scenarios. Here, we use a volatile expanded judgement task that dissociates raw sensory information, belief updates, and the evolving belief itself. We find that motor beta lateralisation traces the evolving belief across stimuli, while the centroparietal positivity locally encodes the belief updates associated with each individual stimulus. These results suggest a flexible computational hierarchy where context-dependent belief updates can be computed sample-by-sample at an intermediate processing level to modify downstream belief representations for protracted decisions about discrete stimuli.

Neurophysiology of Perceptual Decision-Making and Its Alterations in Attention-Deficit Hyperactivity Disorder

Despite the prevalence of attention-deficit hyperactivity disorder (ADHD), efforts to develop a detailed understanding of the neuropsychology of this neurodevelopmental condition are complicated by the diversity of interindividual presentations and the inability of current clinical tests to distinguish between its sensory, attentional, arousal, or motoric contributions. Identifying objective methods that can explain the diverse performance profiles across individuals diagnosed with ADHD has been a long-held goal. Achieving this could significantly advance our understanding of etiological processes and potentially inform the development of personalized treatment approaches. Here, we examine key neuropsychological components of ADHD within an electrophysiological (EEG) perceptual decision-making paradigm that is capable of isolating distinct neural signals of several key information processing stages necessary for sensory-guided actions from attentional selection to motor responses. Using a perceptual decision-making task (random dot motion), we evaluated the performance of 79 children (aged 8-17 years) and found slower and less accurate responses, along with a reduced rate of evidence accumulation (drift rate parameter of drift diffusion model), in children with ADHD (n = 37; 13 female) compared with typically developing peers (n = 42; 18 female). This was driven by the atypical dynamics of discrete electrophysiological signatures of attentional selection, the accumulation of sensory evidence, and strategic adjustments reflecting urgency of response. These findings offer an integrated account of decision-making in ADHD and establish discrete neural signals that might be used to understand the wide range of neuropsychological performance variations in individuals with ADHD.

Decisional components of motor responses are not related to online response control: Evidence from lexical decision and speed-accuracy tradeoff manipulations

Evidence suggests that decision processes can propagate to motor-response execution. However, the functional characterization of motor decisional components is not yet fully understood. By combining a classic lexical decision experiment with manipulations of speed-accuracy tradeoff (SAT), the present experiment assessed the hypothesis that decisional effects on chronometric measures of motor-response execution are related to online response control. The electromyographic (EMG) signal associated with manual button-press responses was used to dissociate the premotor component (from stimulus onset until the onset of the EMG activity) from the motor component (from EMG onset until the button-press), thus enabling the assessment of decision-related effects in terms of motor-response duration within single-trial reaction times. Other than replicating all the previously reported SAT effects, the experiment revealed hindered control processes when the instructions emphasized speed over accuracy, as indicated by measures of response control such as partial errors, fast errors, and correction likelihood. Nonetheless, the lexicality effect on motor responses, consisting of slower motor times for pseudowords compared to words, was impervious to any SAT modulation. The results suggest that SAT-induced variations in decision and response control policies may not be the prominent determinant of decision-related effects on motor times, highlighting the multiple "cognitive" components that affect peripheral response execution.

Motor preparation tracks decision boundary crossing rather than accumulated evidence in temporal decision-making

Interval timing, the ability of animals to estimate the passage of time, is thought to involve diverse neural processes rather than a single central "clock" (Paton & Buonomano, 2018). Each of the different processes engaged in interval timing follows a different dynamic path, according to its specific function. For example, attention tracks anticipated events, such as offsets of intervals (Rohenkohl & Nobre, 2011), while motor processes control the timing of the behavioral output (De Lafuente et al., 2024). However, which processes are involved and how they are orchestrated over time to produce a temporal decision remains unknown. Here, we study motor preparation in the temporal bisection task, in which Human (Female and male) participants categorized intervals as "long" or "short". In contrast to typical perceptual decisions, where motor plans for all response alternatives are prepared simultaneously (Shadlen & Kiani, 2013), we find that temporal bisection decisions develop sequentially. While preparation for "long" responses was already underway before interval offset, no preparation was found for "short" responses. Furthermore, within intervals categorized as "long", motor preparation was stronger at interval offset for faster responses. Our findings support the two-stage model of temporal decisions, where "long" decisions are considered during the interval itself, while "short" decisions are only considered after the interval is over. Viewed from a wider perspective, our study offers methods to study the neural mechanisms of temporal decisions, by studying the multiple processes that produce them.Significance Statement Interval timing is thought to rely on multiple neural processes, yet little is known about which processes are involved, and how they are organized in time. We recorded the EEG of Human participants while they performed a simple temporal decision task, and focused on mu-beta activity, a signature of motor preparation. In typical non-temporal perceptual decisions, mu-beta activity reflects the accumulation of evidence. We find that in temporal decision-making, mu-beta reflects the commitment of the decision instead. This distinction stems from the uniqueness of temporal decisions, in which alternatives are considered sequentially rather than simultaneously. Studying temporal decisions as the dynamic orchestration of multiple neural processes offers a new approach to study the neural mechanisms underlying the perception of time.

Neural mechanisms of metacognitive improvement under speed pressure

The ability to accurately monitor the quality of one's choices, or metacognition, improves under speed pressure, possibly due to changes in post-decisional evidence processing. Here, we investigate the neural processes that regulate decision-making and metacognition under speed pressure using time-resolved analyses of brain activity recorded using electroencephalography. Participants performed a motion discrimination task under short and long response deadlines and provided a metacognitive rating following each response. Behaviourally, participants were faster, less accurate, and showed superior metacognition with short deadlines. These effects were accompanied by a larger centro-parietal positivity (CPP), a neural correlate of evidence accumulation. Crucially, post-decisional CPP amplitude was more strongly associated with participants' metacognitive ratings following errors under short relative to long response deadlines. Our results suggest that superior metacognition under speed pressure may stem from enhanced metacognitive readout of post-decisional evidence.

Task goals shape the relationship between decision and movement speed

The speed at which we move is linked to the speed at which we decide to make these movements. Yet the principles guiding such relationship remain unclear: whereas some studies point toward a shared invigoration process boosting decision and movement speed jointly, others rather indicate a trade-off between both levels of control, with slower movements accompanying faster decisions. Here, we aimed 1) at further investigating the existence of a shared invigoration process linking decision and movement and 2) at testing the hypothesis that such a link is masked when detrimental to the reward rate. To this aim, we tested 62 subjects who performed the Tokens task in two experiments (separate sessions): experiment 1 evaluated how changing decision speed affects movement speed, whereas experiment 2 assessed how changing movement speed affects decision speed. In the latter experiment, subjects were encouraged to favor either decision speed (fast decision group) or decision accuracy (slow decision group). Various mixed model analyses revealed a coregulation of decision (urgency) and movement speed in experiment 1 and in the fast decision group of experiment 2 but not in the slow decision group, despite the fact that these same subjects displayed a coregulation effect in experiment 1. Altogether, our findings support the idea that coregulation occurs as a default mode but that this form of control is diminished or supplanted by a trade-off relationship, contingent on reward rate maximization. Drawing from these behavioral observations, we propose that multiple processes contribute to shaping the speed of decisions and movements.NEW & NOTEWORTHY The principles guiding the relationship between decision and movement speed are still unclear. In the present behavioral study involving two experiments conducted with 62 human subjects, we report findings indicating a relationship that varies as a function of the task goals. Coregulation emerges as a default mode of control that fades when detrimental to the reward rate, possibly because of the influence of other processes that can selectively shape the speed of our decisions or movements.

Common neural choice signals can emerge artefactually amid multiple distinct value signals

Previous work has identified characteristic neural signatures of value-based decision-making, including neural dynamics that closely resemble the ramping evidence accumulation process believed to underpin choice. Here we test whether these signatures of the choice process can be temporally dissociated from additional, choice-'independent' value signals. Indeed, EEG activity during value-based choice revealed distinct spatiotemporal clusters, with a stimulus-locked cluster reflecting affective reactions to choice sets and a response-locked cluster reflecting choice difficulty. Surprisingly, 'neither' of these clusters met the criteria for an evidence accumulation signal. Instead, we found that stimulus-locked activity can 'mimic' an evidence accumulation process when aligned to the response. Re-analysing four previous studies, including three perceptual decision-making studies, we show that response-locked signatures of evidence accumulation disappear when stimulus-locked and response-locked activity are modelled jointly. Collectively, our findings show that neural signatures of value can reflect choice-independent processes and look deceptively like evidence accumulation.

Evidence for interacting but decoupled controls of decisions and movements in nonhuman primates

Many recent studies indicate that control of decisions and actions is integrated during interactive behavior. Among these, several carried out in humans and monkeys conclude that there is a coregulation of choices and movements. Another perspective, based on human data only, proposes a decoupled control of decision duration and movement speed, allowing, for instance, trading decision duration for movement duration when time pressure increases. Crucially, it is not currently known whether this ability to flexibly dissociate decision duration from movement speed is specific to humans, whether it can vary depending on the context in which a task is performed, and whether it is stable over time. These are important questions to address, especially to rely on monkey electrophysiology to infer the neural mechanisms of decision-action coordination in humans. To do so, we trained two macaque monkeys in a perceptual decision-making task and analyzed data collected over multiple behavioral sessions. Our findings reveal a strong and complex relationship between decision duration and movement vigor. Decision duration and action duration can covary but also "compensate" each other. Such integrated but decoupled control of decisions and actions aligns with recent studies in humans, validating the monkey model in electrophysiology as a means of inferring neural mechanisms in humans. Crucially, we demonstrate for the first time that this control can evolve with experience, in an adapted manner. Together, the present findings contribute to deepening our understanding of the integrated control of decisions and actions during interactive behavior.NEW & NOTEWORTHY The mechanism by which the integrated control of decisions and actions occurs, coupled or interactive but decoupled, is debated. In the present study, we show in monkeys that decisions and actions influence each other in a decoupled way. For the first time, we also demonstrate that this control can evolve depending the subject's experience, allowing the trade of movement time for decision time and limiting the temporal discounting of reward value.

The gated cascade diffusion model: An integrated theory of decision making, motor preparation, and motor execution

This article introduces an integrated and biologically inspired theory of decision making, motor preparation, and motor execution. The theory is formalized as an extension of the diffusion model, in which diffusive accumulated evidence from the decision-making process is continuously conveyed to motor areas of the brain that prepare the response, where it is smoothed by a mechanism that approximates a Kalman-Bucy filter. The resulting motor preparation variable is gated prior to reaching agonist muscles until it exceeds a particular level of activation. We tested this gated cascade diffusion model by continuously probing the electrical activity of the response agonists through electromyography in four choice tasks that span a variety of domains in cognitive sciences, namely motion perception, numerical cognition, recognition memory, and lexical knowledge. The model provided a good quantitative account of behavioral and electromyographic data and systematically outperformed previous models. This work represents an advance in the integration of processes involved in simple decisions and sheds new light on the interplay between decision and motor systems. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The late positive event-related potential component is time locked to the decision in recognition memory tasks

Two event-related potential (ERP) components are commonly observed in recognition memory tasks: the Frontal Negativity (FN400) and the Late Positive Component (LPC). These components are widely interpreted as neural correlates of familiarity and recollection, respectively. However, the interpretation of LPC effects is complicated by inconsistent results regarding the timing of ERP amplitude differences. There are also mixed findings regarding how LPC amplitudes covary with decision confidence. Critically, LPC effects have almost always been measured using fixed time windows relative to memory probe stimulus onset, yet it has not been determined whether LPC effects are time locked to the stimulus or the recognition memory decision. To investigate this, we analysed a large (n = 132) existing dataset recorded during recognition memory tasks with old/new decisions followed by post-decisional confidence ratings. We used ERP deconvolution to disentangle contributions to LPC effects (defined as differences between hits and correct rejections) that were time locked to either the stimulus or the vocal old/new response. We identified a left-lateralised parietal LPC effect that was time locked to the vocal response rather than probe stimulus onset. We also isolated a response-locked, midline parietal ERP correlate of confidence that influenced measures of LPC amplitudes at left parietal electrodes. Our findings demonstrate that, contrary to widespread assumptions, the LPC effect is time locked to the recognition memory decision and is best measured using response-locked ERPs. By extension, differences in response time distributions across conditions of interest may lead to substantial measurement biases when analysing stimulus-locked ERPs. Our findings highlight important confounding factors that further complicate the interpretation of existing stimulus-locked LPC effects as neural correlates of recollection. We recommend that future studies adopt our analytic approach to better isolate LPC effects and their sensitivity to manipulations in recognition memory tasks.

Prioritized neural processing of social threats during perceptual decision-making

Emotional signals, notably those signaling threat, benefit from prioritized processing in the human brain. Yet, it remains unclear whether perceptual decisions about the emotional, threat-related aspects of stimuli involve specific or similar neural computations compared to decisions about their non-threatening/non-emotional components. We developed a novel behavioral paradigm in which participants performed two different detection tasks (emotion vs. color) on the same, two-dimensional visual stimuli. First, electroencephalographic (EEG) activity in a cluster of central electrodes reflected the amount of perceptual evidence around 100 ms following stimulus onset, when the decision concerned emotion, not color. Second, participants' choice could be predicted earlier for emotion (240 ms) than for color (380 ms) by the mu (10 Hz) rhythm, which reflects motor preparation. Taken together, these findings indicate that perceptual decisions about threat-signaling dimensions of facial displays are associated with prioritized neural coding in action-related brain regions, supporting the motivational value of socially relevant signals.

Graded decisions in the human brain

Decision-makers objectively commit to a definitive choice, yet at the subjective level, human decisions appear to be associated with a degree of uncertainty. Whether decisions are definitive (i.e., concluding in all-or-none choices), or whether the underlying representations are graded, remains unclear. To answer this question, we recorded intracranial neural signals directly from the brain while human subjects made perceptual decisions. The recordings revealed that broadband gamma activity reflecting each individual's decision-making process, ramped up gradually while being graded by the accumulated decision evidence. Crucially, this grading effect persisted throughout the decision process without ever reaching a definite bound at the time of choice. This effect was most prominent in the parietal cortex, a brain region traditionally implicated in decision-making. These results provide neural evidence for a graded decision process in humans and an analog framework for flexible choice behavior.

Prior probability cues bias sensory encoding with increasing task exposure

When observers have prior knowledge about the likely outcome of their perceptual decisions, they exhibit robust behavioural biases in reaction time and choice accuracy. Computational modelling typically attributes these effects to strategic adjustments in the criterion amount of evidence required to commit to a choice alternative - usually implemented by a starting point shift - but recent work suggests that expectations may also fundamentally bias the encoding of the sensory evidence itself. Here, we recorded neural activity with EEG while participants performed a contrast discrimination task with valid, invalid, or neutral probabilistic cues across multiple testing sessions. We measured sensory evidence encoding via contrast-dependent steady-state visual-evoked potentials (SSVEP), while a read-out of criterion adjustments was provided by effector-selective mu-beta band activity over motor cortex. In keeping with prior modelling and neural recording studies, cues evoked substantial biases in motor preparation consistent with criterion adjustments, but we additionally found that the cues produced a significant modulation of the SSVEP during evidence presentation. While motor preparation adjustments were observed in the earliest trials, the sensory-level effects only emerged with extended task exposure. Our results suggest that, in addition to strategic adjustments to the decision process, probabilistic information can also induce subtle biases in the encoding of the evidence itself.

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants' choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.

Neural correlates of confidence during decision formation in a perceptual judgment task

When we make a decision, we also estimate the probability that our choice is correct or accurate. This probability estimate is termed our degree of decision confidence. Recent work has reported event-related potential (ERP) correlates of confidence both during decision formation (the centro-parietal positivity component; CPP) and after a decision has been made (the error positivity component; Pe). However, there are several measurement confounds that complicate the interpretation of these findings. More recent studies that overcome these issues have so far produced conflicting results. To better characterise the ERP correlates of confidence we presented participants with a comparative brightness judgment task while recording electroencephalography. Participants judged which of two flickering squares (varying in luminance over time) was brighter on average. Participants then gave confidence ratings ranging from "surely incorrect" to "surely correct". To elicit a range of confidence ratings we manipulated both the mean luminance difference between the brighter and darker squares (relative evidence) and the overall luminance of both squares (absolute evidence). We found larger CPP amplitudes in trials with higher confidence ratings. This association was not simply a by-product of differences in relative evidence (which covaries with confidence) across trials. We did not identify postdecisional ERP correlates of confidence, except when they were artificially produced by pre-response ERP baselines. These results provide further evidence for neural correlates of processes that inform confidence judgments during decision formation.

Cortical β Power Reflects a Neural Implementation of Decision Boundary Collapse in Speeded Decisions

A prominent account of decision-making assumes that information is accumulated until a fixed response threshold is crossed. However, many decisions require weighting of information appropriately against time. Collapsing response thresholds are a mathematically optimal solution to this decision problem. However, our understanding of the neurocomputational mechanisms underlying dynamic response thresholds remains significantly incomplete. To investigate this issue, we used a multistage drift-diffusion model (DDM) and also analyzed EEG β power lateralization (BPL). The latter served as a neural proxy for decision signals. We analyzed a large dataset (n = 863; 434 females and 429 males) from a speeded flanker task and data from an independent confirmation sample (n = 119; 70 females and 49 males). We showed that a DDM with collapsing decision thresholds, a process wherein the decision boundary reduces over time, captured participants' time-dependent decision policy more accurately than a model with fixed thresholds. Previous research suggests that BPL over motor cortices reflects features of a decision signal and that its peak, coinciding with the motor response, may serve as a neural proxy for the decision threshold. We show that BPL around the response decreased with increasing RTs. Together, our findings offer compelling evidence for the existence of collapsing decision thresholds in decision-making processes.

Decision-making processes in perceptual learning depend on effectors

Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.

Neural mechanisms for executive control of speed-accuracy trade-off

The medial frontal cortex (MFC) plays an important but disputed role in speed-accuracy trade-off (SAT). In samples of neural spiking in the supplementary eye field (SEF) in the MFC simultaneous with the visuomotor frontal eye field and superior colliculus in macaques performing a visual search with instructed SAT, during accuracy emphasis, most SEF neurons discharge less from before stimulus presentation until response generation. Discharge rates adjust immediately and simultaneously across structures upon SAT cue changes. SEF neurons signal choice errors with stronger and earlier activity during accuracy emphasis. Other neurons signal timing errors, covarying with adjusting response time. Spike correlations between neurons in the SEF and visuomotor areas did not appear, disappear, or change sign across SAT conditions or trial outcomes. These results clarify findings with noninvasive measures, complement previous neurophysiological findings, and endorse the role of the MFC as a critic for the actor instantiated in visuomotor structures.

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.

Evidence Accumulation Rate Moderates the Relationship between Enriched Environment Exposure and Age-Related Response Speed Declines

Older adults exposed to enriched environments (EEs) maintain relatively higher levels of cognitive function, even in the face of compromised markers of brain health. Response speed (RS) is often used as a simple proxy to measure the preservation of global cognitive function in older adults. However, it is unknown which specific selection, decision, and/or motor processes provide the most specific indices of neurocognitive health. Here, using a simple decision task with electroencephalography (EEG), we found that the efficiency with which an individual accumulates sensory evidence was a critical determinant of the extent to which RS was preserved in older adults (63% female, 37% male). Moreover, the mitigating influence of EE on age-related RS declines was most pronounced when evidence accumulation rates were shallowest. These results suggest that the phenomenon of cognitive reserve, whereby high EE individuals can better tolerate suboptimal brain health to facilitate the preservation of cognitive function, is not just applicable to neuroanatomical indicators of brain aging but can be observed in markers of neurophysiology. Our results suggest that EEG metrics of evidence accumulation may index neurocognitive vulnerability of the aging brain.Significance Statement Response speed in older adults is closely linked with trajectories of cognitive aging. Here, by recording brain activity while individuals perform a simple computer task, we identify a neural metric that is a critical determinant of response speed. Older adults exposed to greater cognitive and social stimulation throughout a lifetime could maintain faster responding, even when this neural metric was impaired. This work suggests EEG is a useful technique for interrogating how a lifetime of stimulation benefits brain health in aging.

Electrophysiological evidence of discontinuities in the propagation of lexical decision processes across the motor hierarchy

This research assessed the propagation of decisional effects across multiple electrophysiological indexes related to motor-response implementation within a lexical decision task, a paradigmatic case of a 2-alternative choice task on linguistic stimuli. By co-registering electroencephalographic and electromyographic data, we focused on the lexicality effect (i.e., the difference between responses to words and nonwords), and we tracked its influence across indexes of motor-response planning (indexed by effector-selective lateralization of beta-frequency desynchronizations), programming (indexed by the lateralized readiness potential) and execution (indexed by the chronometric durations of muscular responses). In addition, we explored corticomuscular coherence as the potential physiological underpinning of a continuous mapping of information between stimulus evaluation and response channels. The results revealed lexicality effects only on indexes of motor planning and execution, with no reliable involvement of the other measures. This pattern is discussed with reference to the hypothesis of multiple decisional components exerting different influences across the motor-hierarchy.

Balancing true and false detection of intermittent sensory targets by adjusting the inputs to the evidence accumulation process

Decisions about noisy stimuli are widely understood to be made by accumulating evidence up to a decision bound that can be adjusted according to task demands. However, relatively little is known about how such mechanisms operate in continuous monitoring contexts requiring intermittent target detection. Here, we examined neural decision processes underlying detection of 1 s coherence targets within continuous random dot motion, and how they are adjusted across contexts with weak, strong, or randomly mixed weak/strong targets. Our prediction was that decision bounds would be set lower when weak targets are more prevalent. Behavioural hit and false alarm rate patterns were consistent with this, and were well captured by a bound-adjustable leaky accumulator model. However, beta-band EEG signatures of motor preparation contradicted this, instead indicating lower bounds in the strong-target context. We thus tested two alternative models in which decision-bound dynamics were constrained directly by beta measurements, respectively, featuring leaky accumulation with adjustable leak, and non-leaky accumulation of evidence referenced to an adjustable sensory-level criterion. We found that the latter model best explained both behaviour and neural dynamics, highlighting novel means of decision policy regulation and the value of neurally informed modelling.

Movement characteristics impact decision-making and vice versa

Previous studies suggest that humans are capable of coregulating the speed of decisions and movements if promoted by task incentives. It is unclear however whether such behavior is inherent to the process of translating decisional information into movements, beyond posing a valid strategy in some task contexts. Therefore, in a behavioral online study we imposed time constraints to either decision- or movement phases of a sensorimotor task, ensuring that coregulating decisions and movements was not promoted by task incentives. We found that participants indeed moved faster when fast decisions were promoted and decided faster when subsequent finger tapping movements had to be executed swiftly. These results were further supported by drift diffusion modelling and inspection of psychophysical kernels: Sensorimotor delays related to initiating the finger tapping sequence were shorter in fast-decision as compared to slow-decision blocks. Likewise, the decisional speed-accuracy tradeoff shifted in favor of faster decisions in fast-tapping as compared to slow-tapping blocks. These findings suggest that decisions not only impact movement characteristics, but that properties of movement impact the time taken to decide. We interpret these behavioral results in the context of embodied decision-making, whereby shared neural mechanisms may modulate decisions and movements in a joint fashion.

Pupillary dynamics reflect the impact of temporal expectation on detection strategy

Everyday life's perceptual decision-making is informed by experience. In particular, temporal expectation can ease the detection of relevant events in noisy sensory streams. Here, we investigated if humans can extract hidden temporal cues from the occurrences of probabilistic targets and utilize them to inform target detection in a complex acoustic stream. To understand what neural mechanisms implement temporal expectation influence on decision-making, we used pupillometry as a proxy for underlying neuromodulatory activity. We found that participants' detection strategy was influenced by the hidden temporal context and correlated with sound-evoked pupil dilation. A model of urgency fitted on false alarms predicted detection reaction time. Altogether, these findings suggest that temporal expectation informs decision-making and could be implemented through neuromodulatory-mediated urgency signals.

Multiphasic value biases in fast-paced decisions

Perceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision process dynamically evolves through distinct phases of growing anticipation, detection, and discrimination, but how value biases are exerted through these phases remains unknown. Here, by parsing motor preparation dynamics in human electrophysiology, we uncovered a multiphasic pattern of countervailing biases operating in speeded decisions. Anticipatory preparation of higher-value actions began earlier, conferring a 'starting point' advantage at stimulus onset, but the delayed preparation of lower-value actions was steeper, conferring a value-opposed buildup-rate bias. This, in turn, was countered by a transient deflection toward the higher-value action evoked by stimulus detection. A neurally-constrained process model featuring anticipatory urgency, biased detection, and accumulation of growing stimulus-discriminating evidence, successfully captured both behavior and motor preparation dynamics. Thus, an intricate interplay of distinct biasing mechanisms serves to prioritise time-constrained perceptual decisions.

Motor speed does not impact the drift rate: a computational HDDM approach to differentiate cognitive and motor speed

The drift diffusion model (DDM) is a widely applied computational model of decision making that allows differentiation between latent cognitive and residual processes. One main assumption of the DDM that has undergone little empirical testing is the level of independence between cognitive and motor responses. If true, widespread incorporation of DDM estimation into applied and clinical settings could ease assessment of whether response disruption occurs due to cognitive or motor slowing. Across two experiments, we manipulated response force (motor speed) and set size to evaluate whether drift rates are independent of motor slowing or if motor slowing impacts the drift rate parameter. The hierarchical Bayesian drift diffusion model was used to quantify parameter estimates of drift rate, boundary separation, and non-decision time. Model comparison revealed changes in set size impacted the drift rate while changes in response force did not impact the drift rate, validating independence between drift rates and motor speed. Convergent validity between parameter estimates and traditional assessments of processing speed and motor function were weak or absent. Widespread application, including neurocognitive assessment where confounded changes in cognitive and motor slowing are pervasive, may provide a more process-pure measurement of information processing speed, leading to advanced disease-symptom management.

A Common Neural Account for Social and Nonsocial Decisions

To date, social and nonsocial decisions have been studied largely in isolation. Consequently, the extent to which social and nonsocial forms of decision uncertainty are integrated using shared neurocomputational resources remains elusive. Here, we address this question using simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) in healthy human participants (young adults of both sexes) and a task in which decision evidence in social and nonsocial contexts varies along comparable scales. First, we identify time-resolved build-up of activity in the EEG, akin to a process of evidence accumulation (EA), across both contexts. We then use the endogenous trial-by-trial variability in the slopes of these accumulating signals to construct parametric fMRI predictors. We show that a region of the posterior-medial frontal cortex (pMFC) uniquely explains trial-wise variability in the process of evidence accumulation in both social and nonsocial contexts. We further demonstrate a task-dependent coupling between the pMFC and regions of the human valuation system in dorso-medial and ventro-medial prefrontal cortex across both contexts. Finally, we report domain-specific representations in regions known to encode the early decision evidence for each context. These results are suggestive of a domain-general decision-making architecture, whereupon domain-specific information is likely converted into a "common currency" in medial prefrontal cortex and accumulated for the decision in the pMFC.SIGNIFICANCE STATEMENT Little work has directly compared social-versus-nonsocial decisions to investigate whether they share common neurocomputational origins. Here, using combined electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) and computational modeling, we offer a detailed spatiotemporal account of the neural underpinnings of social and nonsocial decisions. Specifically, we identify a comparable mechanism of temporal evidence integration driving both decisions and localize this integration process in posterior-medial frontal cortex (pMFC). We further demonstrate task-dependent coupling between the pMFC and regions of the human valuation system across both contexts. Finally, we report domain-specific representations in regions encoding the early, domain-specific, decision evidence. These results suggest a domain-general decision-making architecture, whereupon domain-specific information is converted into a common representation in the valuation system and integrated for the decision in the pMFC.

Fronto—Parietal Regions Predict Transient Emotional States in Emotion Modulated Response Inhibition via Low Frequency and Beta Oscillations

The current study evaluated the impact of task-relevant emotion on inhibitory control while focusing on midline cortical regions rather than brain asymmetry. Single-trial time-frequency analysis of electroencephalography recordings linked with response execution and response inhibition was done while thirty-four participants performed the emotion modulated stop-signal task. To evaluate individual differences across decision-making processes involved in inhibitory control, a hierarchical drift-diffusion model was used to fit data from Go-trials for each of the 34 participants. Response threshold in the early processing stage for happy and disgust emotions could be distinguished from the later processing stage at the mid-parietal and mid-frontal regions, respectively, by the single-trial power increments in low frequency (delta and theta) bands. Beta desynchronization in the mid-frontal region was specific for differentiating disgust from neutral emotion in the early as well as later processing stages. The findings are interpreted based on the influence of emotional stimuli on early perceptual processing originating as a bottom-up process in the mid-parietal region and later proceeding to the mid-frontal region responsible for cognitive control processing, which resulted in enhanced inhibitory performance. The results show the importance of mid-frontal and mid-parietal regions in single-trial dynamics of inhibitory control processing.

The time-course of distractor-based activation modulates effects of speed-accuracy tradeoffs in conflict tasks

The cognitive processes underlying the ability of human performers to trade speed for accuracy is often conceptualized within evidence accumulation models, but it is not yet clear whether and how these models can account for decision-making in the presence of various sources of conflicting information. In the present study, we provide evidence that speed-accuracy tradeoffs (SATs) can have opposing effects on performance across two different conflict tasks. Specifically, in a single preregistered experiment, the mean reaction time (RT) congruency effect in the Simon task increased, whereas the mean RT congruency effect in the Eriksen task decreased, when the focus was put on response speed versus accuracy. Critically, distributional RT analyses revealed distinct delta plot patterns across tasks, thus indicating that the unfolding of distractor-based response activation in time is sufficient to explain the opposing pattern of congruency effects. In addition, a recent evidence accumulation model with the notion of time-varying conflicting information was successfully fitted to the experimental data. These fits revealed task-specific time-courses of distractor-based activation and suggested that time pressure substantially decreases decision boundaries in addition to reducing the duration of non-decision processes and the rate of evidence accumulation. Overall, the present results suggest that time pressure can have multiple effects in decision-making under conflict, but that strategic adjustments of decision boundaries in conjunction with different time-courses of distractor-based activation can produce counteracting effects on task performance with different types of distracting sources of information.

Temporal dynamics of decision making: A synthesis of computational and neurophysiological approaches

As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.

Hasty sensorimotor decisions rely on an overlap of broad and selective changes in motor activity

Humans and other animals are able to adjust their speed–accuracy trade-off (SAT) at will depending on the urge to act, favoring either cautious or hasty decision policies in different contexts. An emerging view is that SAT regulation relies on influences exerting broad changes on the motor system, tuning its activity up globally when hastiness is at premium. The present study aimed to test this hypothesis. A total of 50 participants performed a task involving choices between left and right index fingers, in which incorrect choices led either to a high or to a low penalty in 2 contexts, inciting them to emphasize either cautious or hasty policies. We applied transcranial magnetic stimulation (TMS) on multiple motor representations, eliciting motor-evoked potentials (MEPs) in 9 finger and leg muscles. MEP amplitudes allowed us to probe activity changes in the corresponding finger and leg representations, while participants were deliberating about which index to choose. Our data indicate that hastiness entails a broad amplification of motor activity, although this amplification was limited to the chosen side. On top of this effect, we identified a local suppression of motor activity, surrounding the chosen index representation. Hence, a decision policy favoring speed over accuracy appears to rely on overlapping processes producing a broad (but not global) amplification and a surround suppression of motor activity. The latter effect may help to increase the signal-to-noise ratio of the chosen representation, as supported by single-trial correlation analyses indicating a stronger differentiation of activity changes in finger representations in the hasty context.

Many have argued that the regulation of the speed-accuracy tradeoff relies on an urgency signal, which implements "collapsing decision thresholds" by tuning neural activity in a global manner in decision-related structures. This study indicates that the reality is more subtle, with several aspects of "urgency" being specifically targeted to particular corticospinal populations within the motor system.

Dynamics of Visual Perceptual Decision-Making in Freely Behaving Mice

The temporal dynamics of perceptual decisions offer a key window into the cognitive processes contributing to decision-making. Investigating perceptual dynamics in a genetically tractable animal model can facilitate the subsequent unpacking of the underlying neural mechanisms. Here, we investigated the time course as well as fundamental psychophysical constants governing visual perceptual decision-making in freely behaving mice. We did so by analyzing response accuracy against reaction time (RT), i.e., conditional accuracy, in a series of two-alternative forced choice (2-AFC) orientation discrimination tasks in which we varied target size, luminance, duration, and presence of a foil. Our results quantified two distinct stages in the time course of mouse visual decision-making: a "sensory encoding" stage in which conditional accuracy exhibits a classic trade-off with response speed, and a subsequent "short-term memory (STM)-dependent" stage in which conditional accuracy exhibits a classic asymptotic decay following stimulus offset. We estimated the duration of visual sensory encoding as 200-320 ms across tasks, the lower bound of the duration of STM as ∼1700 ms, and the briefest duration of visual stimulus input that is informative as ≤50 ms. Separately, by varying stimulus onset delay, we demonstrated that the conditional accuracy function (CAF) and RT distribution can be independently modulated, and found that the duration for which mice naturally withhold from responding is a quantitative metric of impulsivity. Taken together, our results establish a quantitative foundation for investigating the neural circuit bases of visual decision dynamics in mice.

Dynamics of Visual Perceptual Decision-Making in Freely Behaving Mice

The temporal dynamics of perceptual decisions offer a key window into the cognitive processes contributing to decision-making. Investigating perceptual dynamics in a genetically tractable animal model can facilitate the subsequent unpacking of the underlying neural mechanisms. Here, we investigated the time course as well as fundamental psychophysical constants governing visual perceptual decision-making in freely behaving mice. We did so by analyzing response accuracy against reaction time (RT), i.e., conditional accuracy, in a series of two-alternative forced choice (2-AFC) orientation discrimination tasks in which we varied target size, luminance, duration, and presence of a foil. Our results quantified two distinct stages in the time course of mouse visual decision-making: a “sensory encoding” stage in which conditional accuracy exhibits a classic trade-off with response speed, and a subsequent “short-term memory (STM)-dependent” stage in which conditional accuracy exhibits a classic asymptotic decay following stimulus offset. We estimated the duration of visual sensory encoding as 200–320 ms across tasks, the lower bound of the duration of STM as ∼1700 ms, and the briefest duration of visual stimulus input that is informative as ≤50 ms. Separately, by varying stimulus onset delay, we demonstrated that the conditional accuracy function (CAF) and RT distribution can be independently modulated, and found that the duration for which mice naturally withhold from responding is a quantitative metric of impulsivity. Taken together, our results establish a quantitative foundation for investigating the neural circuit bases of visual decision dynamics in mice.

Proactive and reactive accumulation-to-bound processes compete during perceptual decisions

Standard models of perceptual decision-making postulate that a response is triggered in reaction to stimulus presentation when the accumulated stimulus evidence reaches a decision threshold. This framework excludes however the possibility that informed responses are generated proactively at a time independent of stimulus. Here, we find that, in a free reaction time auditory task in rats, reactive and proactive responses coexist, suggesting that choice selection and motor initiation, commonly viewed as serial processes, are decoupled in general. We capture this behavior by a novel model in which proactive and reactive responses are triggered whenever either of two competing processes, respectively Action Initiation or Evidence Accumulation, reaches a bound. In both types of response, the choice is ultimately informed by the Evidence Accumulation process. The Action Initiation process readily explains premature responses, contributes to urgency effects at long reaction times and mediates the slowing of the responses as animals get satiated and tired during sessions. Moreover, it successfully predicts reaction time distributions when the stimulus was either delayed, advanced or omitted. Overall, these results fundamentally extend standard models of evidence accumulation in decision making by showing that proactive and reactive processes compete for the generation of responses.

Understanding neural signals of post-decisional performance monitoring: An integrative review

Performance monitoring is a key cognitive function, allowing to detect mistakes and adapt future behavior. Post-decisional neural signals have been identified that are sensitive to decision accuracy, decision confidence and subsequent adaptation. Here, we review recent work that supports an understanding of late error/confidence signals in terms of the computational process of post-decisional evidence accumulation. We argue that the error positivity, a positive-going centro-parietal potential measured through scalp electrophysiology, reflects the post-decisional evidence accumulation process itself, which follows a boundary crossing event corresponding to initial decision commitment. This proposal provides a powerful explanation for both the morphological characteristics of the signal and its relation to various expressions of performance monitoring. Moreover, it suggests that the error positivity -a signal with thus far unique properties in cognitive neuroscience - can be leveraged to furnish key new insights into the inputs to, adaptation, and consequences of the post-decisional accumulation process.

Alpha oscillations and event-related potentials reflect distinct dynamics of attribute construction and evidence accumulation in dietary decision making

How does regulatory focus alter attribute value construction (AVC) and evidence accumulation (EA)? We recorded electroencephalogram during food choices while participants responded naturally or regulated their choices by attending to health attributes or decreasing attention to taste attributes. Using a drift diffusion model, we predicted the time course of neural signals associated with AVC and EA. Results suggested that event-related potentials (ERPs) correlated with the time course of model-predicted taste-attribute signals, with no modulation by regulation. By contrast, suppression of frontal and occipital alpha power correlated with the time course of EA, tracked tastiness according to its goal relevance, and predicted individual variation in successful down-regulation of tastiness. Additionally, an earlier rise in frontal and occipital theta power represented food tastiness more strongly during regulation and predicted a weaker influence of food tastiness on behaviour. Our findings illuminate how regulation modifies the representation of attributes during the process of EA.

Trading accuracy for speed over the course of a decision

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales-that is, over the course of an ongoing decision-and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic cha*nges in accuracy criterion allow the regulation of the SAT within the timescale of a single decision.NEW & NOTEWORTHY Extensive research has been devoted to understanding the mechanisms allowing the regulation of the speed-accuracy tradeoff (SAT) from one context to another and from one decision to another. Here, we show that humans can voluntarily change their SAT on even shorter timescales-that is, over the course of a decision. These rapid SAT shifts are associated with dynamic adjustments in the accuracy criterion exploited for committing to a choice.

Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans

A successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, called urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. Forty females and 34 males took part (mean age, 23.4 years). We find that an evoked potential time locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathologic decision-making such as in impulse control and addictive disorders.SIGNIFICANCE STATEMENT Perceptual decisions are often described by a class of models that assumes that sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.

A neural index of inefficient evidence accumulation in dyslexia underlying slow perceptual decision making

Visual processing deficits have been widely reported in developmental dyslexia however the locus of cognitive dysfunction remains unclear. Here, we examined the neural correlates of perceptual decision-making using a dot-motion task and electroencephalography (EEG) and investigated whether presenting deficits were unique to children with dyslexia or if they were also evident in other, typically developing children with equally immature reading systems. Sixty-eight children participated: 32 with dyslexia (DD; 16 females); 21 age-matched controls (AM; 11 females) and 15 reading-matched controls (RM; 9 females). All participants completed a bilaterally presented random-dot-motion task while EEG was recorded. Neural signatures of low level sensory processing (steady state visual evoked potentials; SSVEPs), pre-target attentional bias (posterior α power), attentional orienting (N2), evidence accumulation (centro-parietal positive decision signal; CPP) and execution of a motor response (β) were obtained to dissect the temporal sequence of perceptual decision-making. Reading profile provided a score of relative lexical and sublexical skills for each participant. Although all groups performed comparably in terms of task accuracy and false alarm rate, the DD group were slower and demonstrated an earlier peak latency, reduced slope and lower amplitude of the CPP compared with both AM and RM controls. Reading profile was found to moderate the relationship between word reading ability, reaction time as well as CPP indices showing that lexical dyslexics responded more slowly and had a shallower slope, reduced amplitude and earlier latency of CPP waveforms than sublexical dyslexics. These findings suggest that children with dyslexia, particularly those with relatively poorer lexical abilities, have a reduced rate and peak of evidence accumulation as denoted by CPP markers yet remain slow in their overt response. This is in keeping with hypotheses that children with dyslexia have impairment in effectively sampling and processing evidence about visual motion stimuli.

Neurophysiology of Human Perceptual Decision-Making

The discovery of neural signals that reflect the dynamics of perceptual decision formation has had a considerable impact. Not only do such signals enable detailed investigations of the neural implementation of the decision-making process but they also can expose key elements of the brain's decision algorithms. For a long time, such signals were only accessible through direct animal brain recordings, and progress in human neuroscience was hampered by the limitations of noninvasive recording techniques. However, recent methodological advances are increasingly enabling the study of human brain signals that finely trace the dynamics of the unfolding decision process. In this review, we highlight how human neurophysiological data are now being leveraged to furnish new insights into the multiple processing levels involved in forming decisions, to inform the construction and evaluation of mathematical models that can explain intra- and interindividual differences, and to examine how key ancillary processes interact with core decision circuits.

Distractors Selectively Modulate Electrophysiological Markers of Perceptual Decisions

Current models of perceptual decision-making assume that choices are made after evidence in favor of an alternative accumulates to a given threshold. This process has recently been revealed in human EEG recordings, but an unresolved issue is how these neural mechanisms are modulated by competing, yet task-irrelevant, stimuli. In this study, we tested 20 healthy participants on a motion direction discrimination task. Participants monitored two patches of random dot motion simultaneously presented on either side of fixation for periodic changes in an upward or downward motion, which could occur equiprobably in either patch. On a random 50% of trials, these periods of coherent vertical motion were accompanied by simultaneous task-irrelevant, horizontal motion in the contralateral patch. Our data showed that these distractors selectively increased the amplitude of early target selection responses over scalp sites contralateral to the distractor stimulus, without impacting on responses ipsilateral to the distractor. Importantly, this modulation mediated a decrement in the subsequent buildup rate of a neural signature of evidence accumulation and accounted for a slowing of RTs. These data offer new insights into the functional interactions between target selection and evidence accumulation signals, and their susceptibility to task-irrelevant distractors. More broadly, these data neurally inform future models of perceptual decision-making by highlighting the influence of early processing of competing stimuli on the accumulation of perceptual evidence.

Evidence accumulation under uncertainty - a neural marker of emerging choice and urgency

To interact meaningfully with its environment, an agent must integrate external information with its own internal states. However, information about the environment is often noisy. In this study, we identify a neural correlate that tracks how asymmetries between competing alternatives evolve over the course of a decision. In our task participants had to monitor a stream of discrete visual stimuli over time and decide whether or not to act, on the basis of either strong or ambiguous evidence. We found that the classic P3 event-related potential evoked by sequential evidence items tracked decision-making processes and predicted participants' categorical choices on a single trial level, both when evidence was strong and when it was ambiguous. The P3 amplitudes in response to evidence supporting the eventually selected option increased over trial time as decisions evolved, being maximally different from the P3 amplitudes evoked by competing evidence at the time of decision. Computational modelling showed that both the neural dynamics and behavioural primacy and recency effects can be explained by a combination of (a) competition between mutually inhibiting accumulators for the two categorical choice outcomes, and (b) a context-dependant urgency signal. In conditions where evidence was presented at a low rate, urgency increased faster than in conditions when evidence was very frequent. We also found that the readiness potential, a classic marker of endogenously initiated actions, was observed preceding movements in all conditions - even when those were strongly driven by external evidence.

Temporal Expectation Hastens Decision Onset But Does Not Affect Evidence Quality

The ability to predict the timing of forthcoming events, known as temporal expectation, has a strong impact on human information processing. Although there is growing consensus that temporal expectations enhance the speed and accuracy of perceptual decisions, it remains unclear whether they affect the decision process itself, or non-decisional (sensory/motor) processes. Here, healthy human participants (N = 21; 18 female) used predictive auditory cues to anticipate the timing of low-contrast visual stimuli they were required to detect. Modeling of the behavioral data using a prominent sequential sampling model indicated that temporal expectations speeded up non-decisional processes but had no effect on decision formation. Electrophysiological recordings confirmed and extended this result: temporal expectations hastened the onset of a neural signature of decision formation but had no effect on its build-up rate. Anticipatory α band power was modulated by temporal expectation and co-varied with intrinsic trial-by-trial variability in behavioral and neural signatures of the onset latency of the decision process. These findings highlight how temporal predictions optimize our interaction with unfolding sensory events.SIGNIFICANCE STATEMENT Temporal expectation enhances performance, but the locus of this effect remains debated. Here, we contrasted the two dominant accounts: enhancement through (1) expedited decision onset, or (2) an increase in the quality of sensory evidence. We manipulated expectations about the onset of a dim visual target using a temporal cueing paradigm, and probed the locus of the expectation effect with two complementary approaches: drift diffusion modeling (DDM) of behavior, and estimation of the onset and progression of the decision process from a supramodal accumulation-to-bound signal in simultaneously measured EEG signals. Behavioral modeling and neural data provided strong, converging evidence for an account in which temporal expectations enhance perception by speeding up decision onset, without affecting evidence quality.