The role of premature evidence accumulation in making difficult perceptual decisions under temporal uncertainty

Predicting time, shaping control: Unveiling age-related effects of temporal predictability on the dynamics of cognitive control in 5- to 14-year-old children

Understanding how individuals learn to synchronize actions with the temporal structure of their environment is crucial for understanding goal-directed behavior. This study investigated the effects of temporal predictability on cognitive control and action regulation in children aged 5 to 14 years. In our temporally cued version of the Simon task, children were explicitly informed that visual cues would either predict (temporal cues) or not predict (neutral cues) the onset of a target. They used this information to respond to lateralized targets when the target position was either compatible or incompatible with the response hand. Temporal cues speeded reaction times (RTs) to compatible targets in the older (11- to 14-year-old) children and induced a greater number of fast impulsive errors to incompatible targets across all age groups. This pattern replicates previous results in adults and demonstrates that knowing when an event is likely to occur induces a fast, although impulsive, response style. Surprisingly, in the youngest age group (5- and 6-year-olds), temporal cues speeded RTs to incompatible, as well as compatible, targets and helped children to inhibit fast impulsive errors to incompatible targets more efficiently. In summary, the youngest children appeared to effectively leverage the information conveyed by temporal cues to mitigate impulsive response tendencies. However, the benefits of temporal cues on impulse control started to diminish from 7 years of age, when children begin to show more mature inhibitory patterns. Nevertheless, by 11 years of age children achieve performance comparable to that of adults, with faster responses to compatible targets and impulsive responses to incompatible targets.

The illusion of orientation repulsion is weakened in a temporally more predictable visual target

Anticipating the occurrence of future events enables our adaptive behavior by facilitating processing at various stages from perception to action. While the functional benefits of temporal expectation are well acknowledged, its phenomenological effects remain unknown. Focusing on the phenomenon of orientation repulsion, wherein a vertical target is perceived as tilted against surrounding stimuli, we examined how the size of the illusion varies with developing temporal expectation. In Experiment 1, a multimodal cue predicted impending target onset through its validity and rhythmicity. We found that repulsion decreased when the target appeared at or later than the moment predicted by the cue. In Experiment 2, rhythmic cues did not significantly influence repulsion without explicit instruction or subjective awareness of the cue-target contingency. In Experiment 3, a single cue was provided, and the target appeared after one of three foreperiods. The occurrence probability of the target was equalized across foreperiods to isolate the effect of the conditional probability given that the target had not yet occurred (hazard rate). Repulsion decreased as the hazard rate increased with the foreperiod. Heightened temporal expectations inevitably produce a phenomenological change in orientation repulsion by reducing perceptual latency, whereby a premature target representation that has not completely undergone contextual modulation is brought upon one's perception.

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.

Leveraging time for better impulse control: Longer intervals help ADHD children inhibit impulsive responses

Children diagnosed with an Attention Deficit Hyperactivity Disorder (ADHD) often exhibit impulsivity and timing difficulties. Here, we investigated whether children (mean age =  9.9 years) with combined type ADHD, comprising both hyperactive-impulsive and inattentive symptoms, could use the temporal predictability of an event to help inhibit impulsive behaviour. In an adapted Simon task, we measured the effects of temporal predictability on the speed and accuracy of choice reaction times (RT) to targets appearing after short or long intervals. Temporally predictive information was conveyed either explicitly (visual cues) or implicitly (cue-target interval). Analysis of RT distributions allowed us to decompose impulsive behaviour into two key elements: the initial urge to react impulsively, and the subsequent ability to inhibit any impulsive erroneous behaviour. Both healthy controls and ADHD children could use temporal predictability conveyed by temporal cues and the length of the trial to speed their RT. However, in healthy children both explicit and implicit temporal predictability impaired inhibition of impulsive responses. In turn, although children with ADHD had stronger tendency for impulsive responding and abnormal patterns of inhibition as compared to controls, the temporal predictability of the target did not exacerbate these effects. Indeed, responding to targets appearing after long, rather than short, intervals improved inhibition in ADHD children. Taken together, our results suggest that children with ADHD can make use of longer preparatory intervals to help inhibit impulsive behaviour.

The Effect of Congruent versus Incongruent Distractor Positioning on Electrophysiological Signals during Perceptual Decision-Making

Key event-related potentials (ERPs) of perceptual decision-making such as centroparietal positivity (CPP) elucidate how evidence is accumulated toward a given choice. Furthermore, this accumulation can be impacted by visual target selection signals such as the N2 contralateral (N2c). How these underlying neural mechanisms of perceptual decision-making are influenced by the spatial congruence of distractors relative to target stimuli remains unclear. Here, we used electroencephalography (EEG) in humans of both sexes to investigate the effect of distractor spatial congruency (same vs different hemifield relative to targets) on perceptual decision-making. We confirmed that responses for perceptual decisions were slower for spatially incongruent versus congruent distractors of high salience. Similarly, markers of target selection (N2c peak amplitude) and evidence accumulation (CPP slope) were found to be lower when distractors were spatially incongruent versus congruent. To evaluate the effects of congruency further, we applied drift diffusion modeling to participant responses, which showed that larger amplitudes of both ERPs were correlated with shorter nondecision times when considering the effect of congruency. The modeling also suggested that congruency's effect on behavior occurred prior to and during evidence accumulation when considering the effects of the N2c peak and CPP slope. These findings point to spatially incongruent distractors, relative to congruent distractors, influencing decisions as early as the initial sensory processing phase and then continuing to exert an effect as evidence is accumulated throughout the decision-making process. Overall, our findings highlight how key electrophysiological signals of perceptual decision-making are influenced by the spatial congruence of target and distractor.

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.

Obstetric Outcomes in Women on Lithium: A Systematic Review and Meta-Analysis

Background/Objectives: Lithium taken during pregnancy was linked in the past with increased risk for foetal/newborn malformations, but clinicians believe that it is worse for newborn children not to treat the mothers' underlying psychiatric illness. We set to review the available evidence of adverse foetal outcomes in women who received lithium treatment for some time during their pregnancy. Methods: We searched four databases and a register to seek papers reporting neonatal outcomes of women who took lithium during their pregnancy by using the appropriate terms. We adopted the PRISMA statement and used Delphi rounds among all the authors to assess eligibility and the Cochrane Risk-of-Bias tool to evaluate the RoB of the included studies. Results: We found 28 eligible studies, 10 of which met the criteria for inclusion in the meta-analysis. The studies regarded 1402 newborn babies and 2595 women exposed to lithium. Overall, the systematic review found slightly increased adverse pregnancy outcomes for women taking lithium for both the first trimester only and any time during pregnancy, while the meta-analysis found increased odds for cardiac or other malformations, preterm birth, and a large size for gestational age with lithium at any time during pregnancy. Conclusions: Women with BD planning a pregnancy should consider discontinuing lithium when euthymic; lithium use during the first trimester and at any time during pregnancy increases the odds for some adverse pregnancy outcomes. Once the pregnancy has started, there is no reason for discontinuing lithium; close foetal monitoring and regular blood lithium levels may obviate some disadvantages of lithium administration during pregnancy.

Social and non-social feedback stimuli lead to comparable levels of reward learning and reward responsiveness in an online probabilistic reward task

Social stimuli seem to be processed more easily and efficiently than non-social stimuli. The current study tested whether social feedback stimuli improve reward learning in a probabilistic reward task (PRT), in which one response option is usually rewarded more often than the other via presentation of non-social reward stimuli. In a pre-registered online study with 305 participants, 75 participants were presented with a non-social feedback stimulus (a star) and information about gains, which is typically used in published PRT studies. Three other groups (with 73-82 participants each) were presented with one of three social feedback stimuli: verbal praise, an attractive happy face, or a "thumbs up"-picture. The data were analysed based on classical signal detection theory, drift diffusion modelling, and Bayesian analyses of null effects. All PRT variants yielded the expected behavioural preference for the more frequently rewarded response. There was no processing advantage of social over non-social feedback stimuli. Bayesian analyses further supported the observation that social feedback stimuli neither increased nor decreased behavioural preferences in the PRT. The current findings suggest that the PRT is a robust experimental paradigm independent of the applied feedback stimuli. They also suggest that the occurrence of a processing advantage for social feedback stimuli is dependent on the experimental task and design.

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.

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.

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.

Evidence accumulation relates to perceptual consciousness and monitoring

A fundamental scientific question concerns the neural basis of perceptual consciousness and perceptual monitoring resulting from the processing of sensory events. Although recent studies identified neurons reflecting stimulus visibility, their functional role remains unknown. Here, we show that perceptual consciousness and monitoring involve evidence accumulation. We recorded single-neuron activity in a participant with a microelectrode in the posterior parietal cortex, while they detected vibrotactile stimuli around detection threshold and provided confidence estimates. We find that detected stimuli elicited neuronal responses resembling evidence accumulation during decision-making, irrespective of motor confounds or task demands. We generalize these findings in healthy volunteers using electroencephalography. Behavioral and neural responses are reproduced with a computational model considering a stimulus as detected if accumulated evidence reaches a bound, and confidence as the distance between maximal evidence and that bound. We conclude that gradual changes in neuronal dynamics during evidence accumulation relates to perceptual consciousness and perceptual monitoring in humans.

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.

Neurocomputational mechanisms of prior-informed perceptual decision-making in humans

To interact successfully with diverse sensory environments, we must adapt our decision processes to account for time constraints and prior probabilities. The full set of decision-process parameters that undergo such flexible adaptation has proven to be difficult to establish using simplified models that are based on behaviour alone. Here, we utilize well-characterized human neurophysiological signatures of decision formation to construct and constrain a build-to-threshold decision model with multiple build-up (evidence accumulation and urgency) and delay components (pre- and post-decisional). The model indicates that all of these components were adapted in distinct ways and, in several instances, fundamentally differ from the conclusions of conventional diffusion modelling. The neurally informed model outcomes were corroborated by independent neural decision signal observations that were not used in the model's construction. These findings highlight the breadth of decision-process parameters that are amenable to strategic adjustment and the value in leveraging neurophysiological measurements to quantify these adjustments.

Confluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics

Although the decisions of our daily lives often occur in the context of temporal and reward structures, the impact of such regularities on decision-making strategy is poorly understood. Here, to explore how temporal and reward context modulate strategy, we trained 2 male rhesus monkeys to perform a novel perceptual decision-making task with asymmetric rewards and time-varying evidence reliability. To model the choice and response time patterns, we developed a computational framework for fitting generalized drift-diffusion models, which flexibly accommodate diverse evidence accumulation strategies. We found that a dynamic urgency signal and leaky integration, in combination with two independent forms of reward biases, best capture behavior. We also tested how temporal structure influences urgency by systematically manipulating the temporal structure of sensory evidence, and found that the time course of urgency was affected by temporal context. Overall, our approach identified key components of cognitive mechanisms for incorporating temporal and reward structure into decisions.SIGNIFICANCE STATEMENT In everyday life, decisions are influenced by many factors, including reward structures and stimulus timing. While reward and timing have been characterized in isolation, ecologically valid decision-making involves a multiplicity of factors acting simultaneously. This raises questions about whether the same decision-making strategy is used when these two factors are concurrently manipulated. To address these questions, we trained rhesus monkeys to perform a novel decision-making task with both reward asymmetry and temporal uncertainty. In order to understand their strategy and hint at its neural mechanisms, we used the new generalized drift diffusion modeling framework to model both reward and timing mechanisms. We found two of each reward and timing mechanisms are necessary to explain our data.

Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize task-relevant stimuli relative to irrelevant, potentially distracting stimuli. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel 'integrated' decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.

The role of premature evidence accumulation in making difficult perceptual decisions under temporal uncertainty

The computations and neural processes underpinning decision making have primarily been investigated using highly simplified tasks in which stimulus onsets cue observers to start accumulating choice-relevant information. Yet, in daily life we are rarely afforded the luxury of knowing precisely when choice-relevant information will appear. Here, we examined neural indices of decision formation while subjects discriminated subtle stimulus feature changes whose timing relative to stimulus onset ('foreperiod') was uncertain. Joint analysis of behavioural error patterns and neural decision signal dynamics indicated that subjects systematically began the accumulation process before any informative evidence was presented, and further, that accumulation onset timing varied systematically as a function of the foreperiod of the preceding trial. These results suggest that the brain can adjust to temporal uncertainty by strategically modulating accumulation onset timing according to statistical regularities in the temporal structure of the sensory environment with particular emphasis on recent experience.