The speed of sight: Individual variation in critical flicker fusion thresholds.

The critical flicker fusion threshold is a psychophysical measure commonly used to quantify visual temporal resolution; the fastest rate at which a visual system can discriminate visual signals. Critical flicker fusion thresholds vary substantially among species, reflecting different ecological niches and demands. However, it is unclear how much variation exists in flicker fusion thresholds between healthy individuals of the same species, or how stable this attribute is over time within individuals. In this study, we assessed both inter- and intra-individual variation in critical flicker fusion thresholds in a cohort of healthy human participants within a specific age range, using two common psychophysical methods and three different measurements during each session. The resulting thresholds for each method were highly correlated. We found a between-participant maximum difference of roughly 30 Hz in flicker fusion thresholds and we estimated a 95% prediction interval of 21 Hz. We used random-effects models to compare between- and within-participant variance and found that approximately 80% of variance was due to between-individual differences, and about 10% of the variance originated from within-individual differences over three sessions. Within-individual thresholds did not differ significantly between the three sessions in males, but did in females (P<0.001 for two methods and P<0.05 for one method), indicating that critical flicker fusion thresholds may be more variable in females than in males.

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.

Confidence is predicted by pre- and post-choice decision signal dynamics.

It is well established that one's confidence in a choice can be influenced by new evidence encountered after commitment has been reached, but the processes through which post-choice evidence is sampled remain unclear. To investigate this, we traced the pre- and post-choice dynamics of electrophysiological signatures of evidence accumulation (Centro-parietal Positivity, CPP) and motor preparation (mu/beta band) to determine their sensitivity to participants' confidence in their perceptual discriminations. Pre-choice CPP amplitudes scaled with confidence both when confidence was reported simultaneously with choice, and when reported 1 second after the initial direction decision with no intervening evidence. When additional evidence was presented during the post-choice delay period, the CPP exhibited sustained activation after the initial choice, with a more prolonged build-up on trials with lower certainty in the alternative that was finally endorsed, irrespective of whether this entailed a change-of-mind from the initial choice or not. Further investigation established that this pattern was accompanied by later lateralisation of motor preparation signals toward the ultimately chosen response and slower confidence reports when participants indicated low certainty in this response. These observations are consistent with certainty-dependent stopping theories according to which post-choice evidence accumulation ceases when a criterion level of certainty in a choice alternative has been reached, but continues otherwise. Our findings have implications for current models of choice confidence, and predictions they may make about EEG signatures.

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.

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.

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.

Pharmacological Manipulations of Physiological Arousal and Sleep-Like Slow Waves Modulate Sustained Attention.

Sustained attention describes our ability to keep a constant focus on a given task. This ability is modulated by our physiological state of arousal. Although lapses of sustained attention have been linked with dysregulations of arousal, the underlying physiological mechanisms remain unclear. An emerging body of work proposes that the intrusion during wakefulness of sleep-like slow waves, a marker of the transition toward sleep, could mechanistically account for attentional lapses. This study aimed to expose, via pharmacological manipulations of the monoamine system, the relationship between the occurrence of sleep-like slow waves and the behavioral consequences of sustained attention failures. In a double-blind, randomized-control trial, 32 healthy human male participants received methylphenidate, atomoxetine, citalopram or placebo during four separate experimental sessions. During each session, electroencephalography (EEG) was used to measure neural activity while participants completed a visual task requiring sustained attention. Methylphenidate, which increases wake-promoting dopamine and noradrenaline across cortical and subcortical areas, improved behavioral performance whereas atomoxetine, which increases dopamine and noradrenaline predominantly over frontal cortices, led to more impulsive responses. Additionally, citalopram, which increases sleep-promoting serotonin, led to more missed trials. Based on EEG recording, citalopram was also associated with an increase in sleep-like slow waves. Importantly, compared with a classical marker of arousal such as α power, only slow waves differentially predicted both misses and faster responses in a region-specific fashion. These results suggest that a decrease in arousal can lead to local sleep intrusions during wakefulness which could be mechanistically linked to impulsivity and sluggishness.SIGNIFICANCE STATEMENT We investigated whether the modulation of attention and arousal could not only share the same neuromodulatory pathways but also rely on similar neuronal mechanisms; for example, the intrusion of sleep-like activity within wakefulness. To do so, we pharmacologically manipulated noradrenaline, dopamine, and serotonin in a four-arm, randomized, placebo-controlled trial and examined the consequences on behavioral and electroencephalography (EEG) indices of attention and arousal. We showed that sleep-like slow waves can predict opposite behavioral signatures: impulsivity and sluggishness. Slow waves may be a candidate mechanism for the occurrence of attentional lapses since the relationship between slow-wave occurrence and performance is region-specific and the consequences of these local sleep intrusions are in line with the cognitive functions carried by the underlying brain regions.

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.

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 (ß) 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.

Model-Based Planning Deficits in Compulsivity Are Linked to Faulty Neural Representations of Task Structure.

Compulsive individuals have deficits in model-based planning, but the mechanisms that drive this have not been established. We examined two candidates-that compulsivity is linked to (1) an impaired model of the task environment and/or (2) an inability to engage cognitive control when making choices. To test this, 192 participants performed a two-step reinforcement learning task with concurrent EEG recordings, and we related the neural and behavioral data to their scores on a self-reported transdiagnostic dimension of compulsivity. To examine subjects' internal model of the task, we used established behavioral and neural responses to unexpected events [reaction time (RT) slowing, P300 wave, and parietal-occipital alpha band power] measured when an unexpected transition occurred. To assess cognitive control, we probed theta power at the time of initial choice. As expected, model-based planning was linked to greater behavioral (RT) and neural (alpha power, but not P300) sensitivity to rare transitions. Critically, the sensitivities of both RT and alpha to task structure were weaker in those high in compulsivity. This RT-compulsivity effect was tested and replicated in an independent pre-existing dataset (N = 1413). We also found that mid-frontal theta power at the time of choice was reduced in highly compulsive individuals though its relation to model-based planning was less pronounced. These data suggest that model-based planning deficits in compulsive individuals may arise, at least in part, from having an impaired representation of the environment, specifically how actions lead to future states.SIGNIFICANCE STATEMENT Compulsivity is linked to poorer performance on tasks that require model-based planning, but it is unclear what precise mechanisms underlie this deficit. Do compulsive individuals fail to engage cognitive control at the time of choice? Or do they have difficulty in building and maintaining an accurate representation of their environment, the foundation needed to behave in a goal-directed manner? With reaction time and EEG measures in 192 individuals who performed a two-step decision-making task, we found that compulsive individuals are less sensitive to surprising action-state transitions, where they slow down less and show less alpha band suppression following a rare transition. These findings implicate failures in maintaining an accurate model of the world in model-based planning deficits in compulsivity.

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.

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.

Can Neuroscience Change the Way We View Morality?

Neuroscience has cast new light on the nature of human morality by exploiting simplified paradigms. To enhance our understanding of everyday moral decisions, the field should complement computational approaches with naturalistic paradigms and a focus on narratives and stories.

Impaired error awareness in healthy older adults: an age group comparison study.

Aging is associated with reduced conscious error detection but the brain regions mediating these changes have yet to be clarified. The present study examined the neural correlates of error awareness in healthy older adults. Sixteen older participants (mean age = 75.5 years) and sixteen younger controls (mean age = 27.9 years) were administered the error awareness task, a go/no-go response inhibition paradigm, in which participants were required to signal commission errors. Compared with young adults, older adults were significantly poorer at consciously detecting performance errors, despite both groups being matched for overall accuracy. This age-related behavioral effect was associated with differences in error-related dorsal anterior cingulate cortex and insula activation, with younger adults showing significant differences between errors made with versus without awareness compared with older adults. By contrast, an age-specific modulation in right inferior parietal lobule activation emerged, with increased right inferior parietal lobule activity occurring in older adults during errors made with awareness compared with younger adults. These findings are consistent with theories of age-related deterioration in error processing mechanisms.

Evidence accumulation during perceptual decisions in humans varies as a function of dorsal frontoparietal organization.

Animal neurophysiological studies have identified neural signals within dorsal frontoparietal areas that trace a perceptual decision by accumulating sensory evidence over time and trigger action upon reaching a threshold. Although analogous accumulation-to-bound signals are identifiable on extracranial human electroencephalography, their cortical origins remain unknown. Here neural metrics of human evidence accumulation, predictive of the speed of perceptual reports, were isolated using electroencephalography and related to dorsal frontoparietal network (dFPN) connectivity using diffusion and resting-state functional magnetic resonance imaging. The build-up rate of evidence accumulation mediated the relationship between the white matter macrostructure of dFPN pathways and the efficiency of perceptual reports. This association between steeper build-up rates of evidence accumulation and the dFPN was recapitulated in the resting-state networks. Stronger connectivity between dFPN regions is thus associated with faster evidence accumulation and speeded perceptual decisions. Our findings identify an integrated network for perceptual decisions that may be targeted for neurorehabilitation in cognitive disorders.

Evaluating the neurophysiological evidence for predictive processing as a model of perception.

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.

Contralateral delay activity is not a robust marker of cognitive function in older adults at risk of mild cognitive impairment.

Contralateral delay activity (CDA) has been proposed as a pre-clinical neural marker for mild cognitive impairment (MCI). However, existing evidence is limited to one study with a small sample size (n = 24). Our aim was to extend previous work by investigating the relationship between the CDA and MCI risk in a large sample of older adults (n = 76). We used a regression approach to determine whether (and when) CDA amplitude predicted MCI risk, as indexed by the Montreal Cognitive Assessment (MoCA). CDA amplitude from ~300-500 and ~800-900 ms predicted MoCA performance. However, significant effects were only observed for specific electrodes (P5/P6 and CP3/CP4, but not PO7/PO8) and the nature of the relationship between the CDA and MoCA scores differed across time and according to set size. Bayesian regression analysis indicated partial evidence in favour of the null hypothesis (BF10 values = 4-1.18). Contrary to previous results, our findings suggest that the CDA may not a robust marker of MCI risk. More broadly, our results highlight the difficulty in identifying at-risk individuals, particularly as MCI is a heterogeneous, unstable condition. Future research should prioritise longitudinal approaches in order to track the progression of the CDA and its association with cognitive decline in later life.

Neuropsychological Deficits in Adult ADHD: Evidence for Differential Attentional Impairments, Deficient Executive Functions, and High Self-Reported Functional Impairments.

Objective: This study is aimed to investigate neuropsychological deficits in adult ADHD. Method: Neuropsychological deficits in terms of executive functions, divided, selective, and sustained attention, were investigated in a group of adults with ADHD using a series of neuropsychological tests as well as electroencephalography (EEG). Subjective ratings of everyday life attention and memory problems were also collected. Results: Adults with ADHD showed impairments in executive functions, divided attention and sustained attention, compared with adult controls. Performance on selective attention tasks in adults with ADHD was instead no different from control participants' performance. EEG results confirmed neuropsychological findings by showing a selective impairment on P3 event-related potential (ERP) amplitude indicative of sustained attention deficits. Higher subjective ratings of everyday attentional and memory problems were also found in the ADHD group compared with the control group. Conclusion: This pattern of results suggests differential impairments of attentional skills. Impaired executive functions and higher subjective functional impairments were also found.

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.