Search

Difficulty with sustaining attention to a task is a hallmark of ADHD. It would be useful to know which measures of sustained attention best predict a diagnosis of ADHD. Participants were 129 children with a diagnosis of ADHD and 129 matched controls who completed the fixed Sustained Attention to Response Task (SART). The number of commission and omission errors, standard deviation of response time (SDRT), tau, fast and slow frequency variability, d-prime, and mu were able to successfully classify children with and without ADHD. The mean response time, criterion, and sigma were not able to classify participants. The best classifiers were d-prime (0.75 Area Under the Receiver Operated Characteristic), tau (.74), SDRT (0.74), omission errors (0.72), commission errors (0.71), and SFAUS (0.70). This list of the best classifier measures derived from the SART may prove useful for the planning of future studies.

The capacity to learn and memorize is a key determinant for the quality of life but is known to decline to varying degrees with age. However, neural correlates of memory formation and the critical features that determine the extent to which aging affects learning are still not well understood. By employing a visual sequence learning task, we were able to track the behavioral and neurophysiological markers of gradual learning over several repetitions, which is not possible in traditional approaches that utilize a remember vs. forgotten comparison. On a neurophysiological level, we focused on two learning-related centro-parietal event-related potential (ERP) components: the expectancy-driven P300 and memory-related broader positivity (BP). Our results revealed that although both age groups showed significant learning progress, young individuals learned faster and remembered more stimuli than older participants. Successful learning was directly linked to a decrease of P300 and BP amplitudes. However, young participants showed larger P300 amplitudes with a sharper decrease during the learning, even after correcting for an observed age-related longer P300 latency and increased P300 peak variability. Additionally, the P300 amplitude predicted learning success in both age groups and showed good test–retest reliability. On the other hand, the memory formation processes, reflected by the BP amplitude, revealed a similar level of engagement in both age groups. However, this engagement did not translate into the same learning progress in the older participants. We suggest that the slower and more variable timing of the stimulus identification process reflected in the P300 means that despite the older participants engaging the memory formation process, there is less time for it to translate the categorical stimulus location information into a solidified memory trace. The results highlight the important role of the P300 and BP as a neurophysiological marker of learning and may enable the development of preventive measures for cognitive decline.

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. Presurgical epilepsy patients judged the direction of random-dot stimuli and responded either with a speeded button press (N=23), or vocally, after a randomized delay (N=11). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual build-up that was modulated by the strength of the sensory evidence, and an amplitude that predicted subjects’ choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision making.

Background/ Objectives DRAKO (NCT02850263) was a 24-month, prospective, observational, multi-centre cohort study that enrolled patients diagnosed with diabetic macular oedema (DMO) including central involvement. The study aimed to evaluate standard of care intravitreal aflibercept (IVT-AFL) treatment in the UK. This analysis describes the 12-month outcomes for patients with prior anti–vascular endothelial growth factor (VEGF) treatment for DMO other than IVT-AFL (C2), and 2-year outcomes for both anti-VEGF treatment–naïve patients (C1) and C2 patients. Methods Study eyes were treated with IVT-AFL as per local standard of care. Mean changes in best-corrected visual acuity (BCVA) in ETDRS letters and central subfield thickness (CST) were stratified by baseline factors. Changes in diabetic retinopathy assessments, glycated haemoglobin A1c levels and vision-related quality of life (QoL) were evaluated alongside numbers of injections administered and safety outcomes. Results For C1, mean (SD) changes from baseline in BCVA of +0.7 (12.7) letters and CST of –123.3 (104.3) µm were observed at Month 24. For C2, mean (SD) changes from baseline for BCVA of + 0.2 (10.2) letters and –0.3 (13.0) letters, and CST of –79.1 (137.6) µm and −91.6 (132.9) µm, were observed at 12 and 24 months, respectively. In Year 2, C1 and C2 patients received a mean of 3.7 and 4.3 injections, respectively. Conclusions Year 2 results indicate that IVT-AFL is an effective treatment for DMO in real-world UK clinical practice, despite relatively low injection numbers. The high baseline visual acuity and QoL scores were maintained and there was further improvement in anatomical outcomes.

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, or when reported 1-second after the initial direction decision. When additional evidence was presented during the post-choice delay period, the CPP continued to evolve after the initial choice, with a more prolonged build-up on trials with lower confidence in the alternative that was finally endorsed, irrespective of whether this entailed a change-of-mind. Further investigation established that this pattern was accompanied by earlier post-choice CPP peak latency, earlier lateralisation of motor preparation signals toward the ultimately chosen response, and faster confidence reports when participants indicated high certainty that they had made a correct or incorrect initial choice. These observations are consistent with confidence-dependent stopping theories according to which post-choice evidence accumulation ceases when a criterion level of confidence in a choice alternative has been reached. Our findings have implications for current models of choice confidence, and predictions they may make about EEG signatures.

Background/Objectives DRAKO (NCT02850263) was a 24-month, prospective, non-interventional, multi-centre cohort study enrolling patients with diabetic macular oedema (DMO) including central involvement. The study evaluated UK standard-of-care intravitreal aflibercept (IVT-AFL) treatment. This analysis describes the treatment pathway and service provision for the anti–vascular endothelial growth factor (VEGF) treatment-naïve (C1) and non-naïve patients (C2) who received prior anti-VEGF treatment for DMO other than IVT-AFL. Methods Mean changes in best-corrected visual acuity and central subfield thickness were measured and stratified by baseline factors, including ethnicity and administration of five initial monthly injections within predefined windows. Clinic visits were classified as treatment only (T1), monitoring assessment only (T2), combined visits (T3) or post-injection visits with no treatment or assessment (T4). Results Median time from decision to treat to treatment was 6 days. As a percentage of total visits, T1, T2, T3 and T4 were 7%, 42%, 48% and 3% for C1 and 11%, 39%, 48% and 2% for C2. Most IVT-AFL injections were administered by healthcare professionals (HCPs) other than doctors (C1, 57.4%; C2, 58.5%). The percentage of treatments associated with a procedure-related adverse event where at least 75% of injections were completed by the same injector role were similar for doctors and other HCPs (C1, 1.1% and 0.8%; C2, 0.7%, and 1.0%). Conclusions Results indicate that upon DMO diagnosis, patients were treated promptly, and most visits were combined (treatment and assessment) or monitoring only. Most IVT-AFL was administered by non-physicians with a similar treatment-related safety profile as IVT-AFL administered by physicians.

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-second 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 importance of neurally-informed modelling.

Objectives DRAKO (NCT02850263) is a 24-month, prospective, non-interventional, multi-centre cohort study which enroled patients diagnosed with centre-involving diabetic macular oedema (DMO). The study aims to evaluate standard of care with intravitreal aflibercept (IVT-AFL) treatment in the UK. This analysis describes the anti-vascular endothelial growth factor (anti-VEGF) treatment-naive patient cohort after 12-month follow-up. Methods Study eyes were treated with IVT-AFL as per local standard of care. The mean change in best-corrected visual acuity (BCVA) and central subfield thickness (CST) from baseline at 12 months were measured and stratified by baseline factors. The number of injections and safety data were also evaluated. Results A total of 507 patients were enroled from 35 centres. Mean (SD) baseline BCVA was 71.4 (12.0) letters and CST was 448.7 (88.7) µm, with 63.1% of patients presenting with baseline BCVA ≥ 70 letters (mean 78.1). Mean (SD) change in BCVA of 2.5 (12.2) letters and CST of −119.1 (116.4) µm was observed at month 12. A 7.3 letter gain was observed in patients with baseline BCVA Conclusion Year one results indicated that IVT-AFL was an effective treatment for DMO in standard of care UK clinical practice, maintaining or improving visual acuity in treatment-naive patients with good baseline visual acuity, despite some patients being undertreated versus the summary of product characteristics. These results also demonstrated the clinical importance and meaningful impact of diabetic retinopathy screening in the UK.

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.

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.

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. European Commission Horizon 2020 Irish Research Council Science Foundation Ireland U.S. National Science Foundation

Freezing of gait in people with Parkinson’s disease (PwP) is associated with executive dysfunction and motor preparation deficits. We have recently shown that electrophysiological markers of motor preparation, rather than decision-making, differentiate PwP with freezing of gait (FOG +) and without (FOG −) while sitting. To examine the effect of locomotion on these results, we measured behavioural and electrophysiological responses in PwP with and without FOG during a target response time task while sitting (single-task) and stepping-in-place (dual-task). Behavioural and electroencephalographic data were acquired from 18 PwP (eight FOG +) and seven young controls performing the task while sitting and stepping-in-place. FOG + had slower response times while stepping compared with sitting. However, response times were significantly faster while stepping compared with sitting for controls. Electrophysiological responses showed no difference in decision-making potentials (centroparietal positivity) between groups or conditions but there were differences in neurophysiological markers of response inhibition (N2) and motor preparation (lateralized readiness potential, LRP) in FOG + while performing a dual-task. This suggests that the addition of a second complex motor task (stepping-in-place) impacts automatic allocation of resources in FOG +, resulting in delayed response times. The impact of locomotion on the generation of the N2 and LRP potentials, particularly in freezers, indirectly implies that these functions compete with locomotion for resources. In the setting of multiple complex tasks or cognitive impairment, severe motor dysfunction may result, leading to freezing of gait.

OBJECTIVE: To explore self-inflicted retinal burns from laser pointers in children.METHODS: Literature review of laser pointer retinal injuries in childhood and online survey of UK Consultant Ophthalmologists. A cohort of local children with self-inflicted injury is described. The matter is topical. We review progress in recent legislation and policy change in the UK.RESULTS: Four of 77 case reports of laser burns in childhood analysed reported psychological or behavioural issues. Three of four children in our cohort had such issues. Delay in diagnosis occurred in two of our patients. Structural retinal damage persisted for over 12 months in all four children (seven eyes). Our survey of UK ophthalmologists found 159 cases of injury (85% male), 80% under 20 years of age. The majority of the laser pointers were purchased online. Many patients (36%) suffered moderate vision loss (6/18 to 6/60 Snellen), while 17% (at least 11 patients) suffered severe vision loss (CONCLUSION: We highlight the risk of macular damage and vision loss from handheld lasers specifically in children with behavioural, learning or mental health issues. The diagnosis may be difficult or delayed in such children. In children with uncertain macular changes, ophthalmologists should explore the history for possible instances of exposure to handheld lasers pointers. Regulatory authorities and manufacturers of handheld lasers need to be aware of the risk to children. Furthermore, there is a need to better inform parents, carers and teachers of the risk of ocular self-injury from such lasers pointers.

Ageing impacts on decision-making behaviour across a range of cognitive tasks and scenarios. Computational modelling has proved valuable in providing mechanistic interpretations of these age-related differences; however, the extent to which model parameter differences accurately reflect changes to the underlying neural computations remains unclear. Here, we report that age-related effects on neural signatures of decision formation are inconsistent with behavioural fits derived from a prominent accumulation-to-bound model. Most notably, model-predicted bound differences were absent neurophysiologically. However, constraining the model to match the decision-predictive elements of the brain signals provided more parsimonious fits to behaviour and generated predictions regarding the neural data that were empirically validated. These included a task-dependent slowing of evidence accumulation among older adults and reduced between-trial accumulation rate variability, which was linked to enhanced attentional engagement. Our findings highlight how combining neurophysiological measurements with computational modelling can yield unique insights into group differences in neural decision mechanisms.

Slotnick (this issue) provided a selective review of studies on the attentional modulation of the C1 component of the visual evoked potential, and offers a number of guidelines to maximize the like...

Purpose To define the incidence of cystoid macular edema (CME) and spectral-domain optical coherence tomography–detectable (SD-OCT) subclinical changes in central retinal thickness in patients using prostaglandin analog (PGA) eyedrops after phacoemulsification. Setting Manchester Royal Eye Hospital, Manchester, United Kingdom. Design Prospective case series. Methods A consecutive analysis of the incidence of postoperative CME after phacoemulsification by a single surgeon was performed in eyes of patients using PGA eyedrops between March 2010 and January 2014. The presence of CME was determined using SD-OCT (Cirrus) 3 weeks and 6 weeks postoperatively. Exclusion criteria included preexisting pathology known to predispose to CME and previous ophthalmic surgery. The paired Wilcoxon signed-rank test was used to compare central retinal thickness measurements at baseline and 3 weeks and 6 weeks postoperatively. Results All 48 patients (mean age 78.4 years; 60 eyes) had uneventful surgery. There were no cases of clinically significant CME. Subclinical CME detected by SD-OCT was confirmed in 2 eyes of different patients (3.3% of eyes), 1 eye 3 weeks postoperatively and another eye at 6 weeks. Subclinical CME resolved in both cases within 8 weeks. In both cases, the difference in central retinal thickness at baseline and 6 weeks postoperatively was statistically significant ( P Conclusions The incidence of subclinical CME detectable on SD-OCT after routine phacoemulsification in patients using PGA eyedrops throughout the perioperative period was 3.3%. There were no cases of clinical CME. These findings might guide clinicians in their decision to use PGAs perioperatively.

Impaired awareness of errors is common following traumatic brain injury (TBI) and can be a barrier to successful rehabilitation. The objective of this study was to develop and evaluate a computer-based intervention programme aimed at improving error awareness in individuals with TBI. A further aim was to explore its effects on metacognitive awareness and variability of performance. Participants were 11 individuals with TBI and impaired error awareness who performed a sustained attention task twice-weekly for four weeks. The intervention consisted of audio-visual feedback-on-errors during the sustained attention task. Six participants received audio-visual feedback-on-error, five did not receive feedback. Emergent and metacognitive awareness were measured pre- and post-intervention. Between-groups comparisons of emergent awareness from pre- to post-intervention showed that audio-visual feedback-on-error improved emergent awareness compared to no feedback-on-error. Some changes in metacognitive awareness of executive behaviours as a result of feedback were observed. Audio-visual feedback-on-error improved emergent awareness in individuals with TBI following a four-week/eight-session intervention. This improvement was not observed in the no-feedback group. This pilot intervention is not a stand-alone treatment but it has potential to be usefully incorporated into cognitive or clinical rehabilitation programmes to improve emergent awareness.

Inhibitory control and sustained attention are important cognitive abilities; however, their developmental trajectories remain unclear. In total, 35 6-year-olds, 32 8-year-olds, and 37 10-year-olds performed a Go/No-Go task; this required frequent responding to stimuli with infrequent inhibition to a target that appeared unpredictably. Children performed this task three times over 12months. Response time variability and accuracy measures, linked to inhibition and sustained attention, were assessed. Specifically, fast Fourier transform and ex-Gaussian analyses of response time data provided several measures of response time variability; these measures are thought to represent different components of sustained attention. The 6-year-olds performed less well than the older groups on most measures. The 8-year-olds exhibited greater momentary fluctuations in response time and made more long responses than the 10-year-olds; otherwise, there were few differences between the two older groups. Response inhibition and sustained attention developed significantly between 6 and 8years of age, with subtle changes in attentional control between 8 and 11years of age.

Penetrating ocular injuries from writing instruments that are thrown, especially by children, in the community can result in significant ocular morbidity. Often these cases present to the accident and emergency department. Accurate and prompt assessment is key in saving sight. We present a case of one such injury and how it was surgically managed.

When selecting actions in response to noisy sensory stimuli, the brain can exploit prior knowledge of time constraints, stimulus discriminability and stimulus probability to hone the decision process. Although behavioral models typically explain such effects through adjustments to decision criteria only, the full range of underlying neural process adjustments remains to be established. Here, we draw on human neurophysiological signals reflecting decision formation to construct and constrain a multi-tiered model of prior-informed motion discrimination, in which a motor-independent representation of cumulative evidence feeds build-to-threshold motor signals that receive additional dynamic urgency and bias signal components. The neurally-informed model not only provides a superior quantitative fit to prior-biased behavior across three distinct task regimes (easy, time-pressured and weak evidence), but also reveals adjustments to evidence accumulation rate, urgency rate, and the timing of accumulation onset and motor execution which go undetected or are discrepant in more standard diffusion-model analysis of behavior.

Freezing of gait in people with Parkinson's disease (PwP) is associated with executive dysfunction and motor preparation deficits. We have recently shown that electrophysiological markers of motor preparation, rather than decision-making, differentiate PwP with freezing of gait (FOG +) and without (FOG -) while sitting. To examine the effect of locomotion on these results, we measured behavioural and electrophysiological responses in PwP with and without FOG during a target response time task while sitting (single-task) and stepping-in-place (dual-task). Behavioural and electroencephalographic data were acquired from 18 PwP (eight FOG +) and seven young controls performing the task while sitting and stepping-in-place. FOG + had slower response times while stepping compared with sitting. However, response times were significantly faster while stepping compared with sitting for controls. Electrophysiological responses showed no difference in decision-making potentials (centroparietal positivity) between groups or conditions but there were differences in neurophysiological markers of response inhibition (N2) and motor preparation (lateralized readiness potential, LRP) in FOG + while performing a dual-task. This suggests that the addition of a second complex motor task (stepping-in-place) impacts automatic allocation of resources in FOG +, resulting in delayed response times. The impact of locomotion on the generation of the N2 and LRP potentials, particularly in freezers, indirectly implies that these functions compete with locomotion for resources. In the setting of multiple complex tasks or cognitive impairment, severe motor dysfunction may result, leading to freezing of gait.

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 behavioral 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.

The neural correlates of memory formation in humans have long been investigated by exposing subjects to diverse material and comparing responses to items later remembered to those forgotten. Tasks requiring memorization of sensory sequences afford unique possibilities for linking neural memorization processes to behavior, because, rather than comparing across different items of varying content, each individual item can be examined across the successive learning states of being initially unknown, newly learned, and eventually, fully known. Sequence learning paradigms have not yet been exploited in this way, however. Here, we analyze the event-related potentials of subjects attempting to memorize sequences of visual locations over several blocks of repeated observation, with respect to pre- and post-block recall tests. Over centro-parietal regions, we observed a rapid P300 component superimposed on a broader positivity, which exhibited distinct modulations across learning states that were replicated in two separate experiments. Consistent with its well-known encoding of surprise, the P300 deflection monotonically decreased over blocks as locations became better learned and hence more expected. In contrast, the broader positivity was especially elevated at the point when a given item was newly learned, i.e., started being successfully recalled. These results implicate the Broad Positivity in endogenously-driven, intentional memory formation, whereas the P300, in processing the current stimulus to the degree that it was previously uncertain, indexes the cumulative knowledge thereby gained. The decreasing surprise/P300 effect significantly predicted learning success both across blocks and across subjects. This presents a new, neural-based means to evaluate learning capabilities independent of verbal reports, which could have considerable value in distinguishing genuine learning disabilities from difficulties to communicate the outcomes of learning, or perceptual impairments, in a range of clinical brain disorders.

PurposeTo identify the causal factors in wrong intraocular lens (IOL) events from a national data set and to compare with similar historical data (2003-2010) prior to mandatory checklist use, for the purpose of developing strategies to prevent never events.MethodsData from wrong IOL patient safety incidents (PSIs) submitted to the National Reporting and Learning System (2010-2014) were reviewed by thematic analysis and compared with the data previously collected by the group using the same methodology.ResultsOne hundred and seventy eight wrong IOL PSIs were identified. The contributory factors included: transcription errors (n=26); wrong patient biometry (n=21); wrong IOL selection (n=16); changes in planned procedure (n=16); incorrect IOL brought into theatre (n=11); left/right eye selection errors (n=9); communication errors (n=9); and positive/negative IOL power errors (n=9). In 44 PSIs, no causal factor was reported, limiting the learning value of such reports. Compared with the data from previous years, biometry errors were much reduced but IOL transcription and documentation errors were greater, particularly if further checks did not refer to the original source documentation. IOL exchange surgery was reported in 45 cases.ConclusionsThe selection and implantation of the correct IOL is a complex process which is not adequately addressed by existing checking procedures. Despite the introduction of surgical checklists, wrong IOL incidents continue to occur and are probably under-reported. Human or behavioural factors are heavily implicated in these errors and need to be addressed by novel approaches, including simulation training. There is also scope to further improve the quality and detail of incident reporting and analysis to enhance patient safety.

In Kelly, Gomez-Ramirez and Foxe (2008), we demonstrated strong spatial attentional modulation of initial afferent activity in human area V1 reflected in the C1 visual evoked potential (VEP) component. Using the same task and analysis strategy, Baumgartner and colleagues provide compelling evidence that there is no such modulation in their data. Here, we examine differences in task conditions between this new study and our original study, speculate on how they may account for the discrepant findings, and discuss the broader theoretical implications.

Parkinson’s disease (PD) is a neurological disorder characterized by motor deficits as a result of progressive degeneration of dopaminergic neurons. Patients often report visual impairments and exhibit deficits of visual acuity, contrast sensitivity and color vision, suggesting abnormal processing of visual information. Although electrophysiological studies indicate amplitude and latency differences in patients, one of the major challenges is the lack of a conclusive, accurate, non-invasive biomarker for diagnosis and monitoring of therapeutic efficacy. In this study, we used machine learning to model and identify the most relevant signs from the EEG spectra over the span of visual stimulation. First, we used human electroencephalography (EEG) to measure visual evoked responses during steady state (ssVEP) in a visual surround suppression paradigm, in which measures of gain control and temporal aspects of the visual response are simultaneously tracked. We found an excessive response gain profile of the contrast response function, and an abnormally greater background noise level in PD patients compared to healthy controls. Second, performance of three learning models was tested: logistic regression, decision tree and extra tree. Together, these provide powerful insights about the most relevant features that allow classifying patients from controls. These models contribute with new hints on the interpretation of functional abnormalities in PD based on spectral EEG during visual stimulation. Machine learning provides a promising tool for accurate and robust prediction in PD diagnosis, based on EEG signatures during visual information processing.

The timing and accuracy of perceptual decision-making is exquisitely sensitive to fluctuations in arousal. Although extensive research has highlighted the role of various neural processing stages in forming decisions, our understanding of how arousal impacts these processes remains limited. Here we isolated electrophysiological signatures of decision-making alongside signals reflecting target selection, attentional engagement and motor output and examined their modulation as a function of tonic and phasic arousal, indexed by baseline and task-evoked pupil diameter, respectively. Reaction times were shorter on trials with lower tonic, and higher phasic arousal. Additionally, these two pupil measures were predictive of a unique set of EEG signatures that together represent multiple information processing steps of decision-making. Finally, behavioural variability associated with fluctuations in tonic and phasic arousal, indicative of neuromodulators acting on multiple timescales, was mediated by its effects on the EEG markers of attentional engagement, sensory processing and the variability in decision processing., eLife digest Driving along a busy street requires you to constantly monitor the behavior of other road users. You need to be able to spot and avoid the car that suddenly changes lane, or the pedestrian who steps out in front of you. How fast you can react to such events depends in part on your brain's level of alertness, or 'arousal'. This in turn depends on chemicals within the brain called neuromodulators. Neuromodulators are a type of neurotransmitter. But whereas other neurotransmitters enable brain cells to signal to each other, neuromodulators turn the volume of these signals up or down. The activity of brain regions that produce neuromodulators varies over time, leading to changes in brain arousal. These changes take place over different time scales. Sudden unexpected events, such as those on the busy street above, trigger sub-second changes in arousal. But arousal levels also show spontaneous fluctuations over minutes to hours. We can follow these changes in real-time by looking into a participant’s eyes. This is because the brain regions that produce neuromodulators also control pupil size. Van Kempen et al. have now combined measurements of pupil size with recordings of electrical brain activity. Healthy volunteers learned to press a button as soon as a target appeared on a screen. The larger a volunteer’s pupils were before the target appeared, the more slowly the volunteer responded on that trial. Large baseline pupil size is thought to indicate a high baseline level of brain arousal. By contrast, the larger the increase in pupil size in response to the target, the faster the volunteer responded on that trial. This increase in pupil size is thought to reflect an increase in brain arousal. The recordings of brain activity provided clues to the underlying mechanisms. In trials with large baseline pupil size – and therefore high baseline arousal – the volunteers’ brains showed more variable responses to the target. But in trials with a large increase in pupil size – and a large increase in arousal – the volunteers’ brains showed less variable responses, as well as stronger signals related to attention. Neuromodulators thus act on different timescales to influence different aspects of cognitive performance, including attention and target detection. Fluctuating levels of neuromodulator activity may help explain the variability in our behavior. Monitoring pupil size is one way to gain insights into the mechanisms that bring about these changes in neuromodulator activity.

The timing and accuracy of perceptual decision making is exquisitely sensitive to fluctuations in arousal. Although extensive research has highlighted the role of neural evidence accumulation in forming decisions, our understanding of how arousal impacts these processes remains limited. Here we isolated electrophysiological signatures of evidence accumulation alongside signals reflecting target selection, attentional engagement and motor output and examined their modulation as a function of both tonic and phasic arousal, indexed by baseline and task-evoked pupil diameter, respectively. For both pupillometric measures, the relationship with reaction time was best described by a second-order, U-shaped, polynomial. Additionally, the two pupil measures were predictive of a unique set of EEG signatures that together represent multiple information processing steps of perceptual decision-making, including evidence accumulation. Finally, we found that behavioural variability associated with fluctuations in both tonic and phasic arousal was largely mediated by variability in evidence accumulation.

Computational and neurophysiological research has highlighted neural processes that accumulate sensory evidence for perceptual decisions [1]. These processes have been studied in the context of highly simplified perceptual discrimination paradigms in which the physical evidence appears at times and locations that are either entirely predictable or exogenously cued (e.g., by the onset of the stimulus itself). Yet, we are rarely afforded such certainty in everyday life. For example, when driving along a busy motorway, we must continually monitor the movements of surrounding vehicles for events that call for a lane change. In such scenarios, it is unknown which of the continuously present information sources will become relevant or when. Although it is well established that evidence integration provides an effective mechanism for countering the impact of noise [2], the question of how this mechanism is implemented in the face of uncertain evidence onsets has yet to be answered. Here, we show that when monitoring two potential sources of information for evidence occurring unpredictably in both time and space, the human brain employs discrete, early target selection signals that significantly modulate the onset and rate of neural evidence accumulation, and thereby the timing and accuracy of perceptual reports. These selection signals share many of the key characteristics of the N2pc component highlighted in the literature on visual search [3, 4] yet are present even in the absence of distractors and under situations of low temporal and spatial uncertainty. These data provide novel insights into how target selection supports decision making in uncertain environments.

Gyrate atrophy is a rare autosomal recessive disorder caused by a mutation in the ornithine-δ-amino transferase gene. We present an interesting case of a 33-year-old woman who presented with increasing myopia, nyctalopia and failing vision. Examination revealed posterior subscapsular cataracts, narrowed peripheral visual fields and scalloped atrophic peripheral chorioretinal lesions. Blood investigations showed a raised plasma ornithine level at 917 μmol/L (normal range: 32-88 μmol/L) confirming the diagnosis of gyrate atrophy. The patient, despite not tolerating dietary treatment, had retained central vision over a follow-up period of 18 years. The electroretinogram, which normally diminishes with disease progression, was still nearly normal when last tested at 16 years follow-up. Genetic testing did not reveal any novel mutation that could account for this variation.

Ageing impacts on decision-making behaviour across a range of cognitive tasks and scenarios. Computational modelling has proved valuable in providing mechanistic interpretations of these age-related differences; however, the extent to which model parameter differences accurately reflect changes to the underlying neural computations remains unclear. Here, we report that age-related effects on neural signatures of decision formation are inconsistent with behavioural fits derived from a prominent accumulation-to-bound model. Most notably, model-predicted bound differences were absent neurophysiologically. However, constraining the model to match the decision-predictive elements of the brain signals provided more parsimonious fits to behaviour and generated predictions regarding the neural data that were empirically validated. These included a task-dependent slowing of evidence accumulation among older adults and reduced between-trial accumulation rate variability, which was linked to enhanced attentional engagement. Our findings highlight how combining neurophysiological measurements with computational modelling can yield unique insights into group differences in neural decision mechanisms.

Summary In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1–6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation—and hence, rate of accumulation—is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions.

Despite their small size, microsaccades can impede stimulus detections if executed at inopportune times. Although it has been shown that microsaccades evoke both inhibitory and excitatory responses across different visual regions, their impact on the higher-level neural decision processes that bridge sensory responses to action selection has yet to be examined. Here, we show that when human observers monitor stimuli for subtle feature changes, the occurrence of microsaccades long after (up to 800 ms) change onset predicts slower reaction times and this is accounted for by momentary suppression of neural signals at each key stage of decision formation: visual evidence encoding, evidence accumulation, and motor preparation. Our data further reveal that, independent of the timing of the change events, the onset of neural decision formation coincides with a systematic inhibition of microsaccade production, persisting until the perceptual report is executed. Our combined behavioral and neural measures highlight antagonistic interactions between microsaccade occurrence and evidence accumulation during visual decision-making tasks.SIGNIFICANCE STATEMENTWhen fixating on a location in space, we frequently make tiny eye movements called microsaccades. In the present study, we show that these microsaccades impede our ability to make perceptual decisions about visual stimuli and this impediment specifically occurs via the disruption of several processing levels of the sensorimotor network: the encoding of visual evidence itself, the accumulation of visual evidence toward a response, and effector-selective motor preparation. Furthermore, we show that the production of microsaccades is inhibited during the perceptual decision, possibly as a counteractive measure to mitigate their negative effect on behavior in this context. The combined behavioral and neural measures used in this study provide strong and novel evidence for the interaction of fixational eye movements and the perceptual decision-making process.

Innovations in methods and technologies are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, there is growing enthusiasm about the prospect of achieving clinically useful tools that can assist in the diagnosis and management of mental health and learning disorders. For these ambitions to be realized, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. To this end, the Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank comprised of data from 10,000 New York City area children and adolescents (ages 5-21). The HBN has adopted a community-referred recruitment model. Specifically, study advertisements seek the participation of families who have concerns about one or more psychiatric symptoms in their child. The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle (e.g., fitness, diet) phenotypes, as well as multimodal brain imaging, electroencephalography, digital voice and video recordings, genetics, and actigraphy. In this paper, we present the motivation, rationale and design for the HBN along with the initial implementation and evolution of the HBN protocols. We describe the first major open data release (n = 664) containing descriptive, electroencephalography, and multimodal brain imaging data (resting state and naturalistic viewing functional MRI, diffusion MRI and morphometric MRI). Beyond accelerating transdiagnostic research, we discuss the potential of the HBN Biobank to advance related areas, such as biophysical modeling, voice and speech analysis, natural viewing fMRI and EEG, and methods optimization.

Response time variability (RTV) is a useful measure of sustained attention; however, little is known about developmental changes in RTV at different temporal frequencies. Thirty-five 6-year-olds, 31 8-year-olds, and 37 10-year-olds completed the fixed-sequence Sustained Attention to Response Task on three occasions, six months apart. Fast Fourier Transform and ex-Gaussian analyses of response time (RT) data assessed momentary fluctuations in RT, gradual changes in RT, and very long responses, thought to reflect attentional control fluctuations, slow-shifting arousal, and infrequent lapses in attention, respectively. A half-by-half analysis measured within-occasion time-on-task effects. The 10-to 11-year-olds performed with less momentary fluctuations in RT, fewer long responses, and fewer commission and omission errors than the younger groups. This group performed well in the first half of the task but showed time-on-task effects on measures of momentary fluctuations in RT, very long responses, target sensitivity (d'), and commission errors. The 6- to 7-year-olds performed less well than the older groups, and showed time-on-task effects, on almost all measures. The 8- to- 9-year-olds mostly performed at an intermediate level compared with the other groups; however, this group performed with a similar level of momentary fluctuations in RT and very long responses as the 6- to 7-year-olds. These findings indicate that there is ongoing maturation of various aspects of sustained attention on a predictable task, with a period of relative stability in performance between 8 and 9 years of age.

In situations in which impending sensory events demand fast action choices, we must be ready to prioritize higher-value courses of action to avoid missed opportunities. When such a situation first presents itself, stimulus–action contingencies and their relative value must be encoded to establish a value-biased state of preparation for an impending sensorimotor decision. Here, we sought to identify neurophysiological signatures of such processes in the human brain (both female and male). We devised a task requiring fast action choices based on the discrimination of a simple visual cue in which the differently valued sensory alternatives were presented 750–800 ms before as peripheral “targets” that specified the stimulus–action mapping for the upcoming decision. In response to the targets, we identified a discrete, transient, spatially selective signal in the event-related potential (ERP), which scaled with relative value and strongly predicted the degree of behavioral bias in the upcoming decision both across and within subjects. This signal is not compatible with any hitherto known ERP signature of spatial selection and also bears novel distinctions with respect to characterizations of value-sensitive, spatially selective activity found in sensorimotor areas of nonhuman primates. Specifically, a series of follow-up experiments revealed that the signal was reliably invoked regardless of response laterality, response modality, sensory feature, and reward valence. It was absent, however, when the response deadline was relaxed and the strategic need for biasing removed. Therefore, more than passively representing value or salience, the signal appears to play a versatile and active role in adaptive sensorimotor prioritization.SIGNIFICANCE STATEMENTIn many situations such as fast-moving sports, we must be ready to act fast in response to sensory events and, in our preparation, prioritize courses of action that lead to greater rewards. Although behavioral effects of value biases in sensorimotor decision making have been widely studied, little is known about the neural processes that set these biases in place beforehand. Here, we report the discovery of a transient, spatially selective neural signal in humans that encodes the relative value of competing decision alternatives and strongly predicts behavioral value biases in decisions made ∼500 ms later. Follow-up manipulations of value differential, reward valence, response modality, sensory features, and time constraints establish that the signal reflects an active, feature- and effector-general preparatory mechanism for value-based prioritization.

In natural behavior, animals have access to multiple sources of information, but only a few of these sources are relevant for learning and actions. Beyond choosing an appropriate action, making good decisions entails the ability to choose the relevant information, but fundamental questions remain about the brain's information sampling policies. Recent studies described the neural correlates of seeking information about a reward, but it remains unknown whether, and how, neurons encode choices of instrumental information, in contexts in which the information guides subsequent actions. Here we show that parietal cortical neurons involved in oculomotor decisions encode, before an information sampling saccade, the reduction in uncertainty that the saccade is expected to bring for a subsequent action. These responses were distinct from the neurons' visual and saccadic modulations and from signals of expected reward or reward prediction errors. Therefore, even in an instrumental context when information and reward gains are closely correlated, individual cells encode decision variables that are based on informational factors and can guide the active sampling of action-relevant cues.

Healthy subjects typically exhibit a subtle bias of visuospatial attention favouring left space that is commonly termed ‘pseudoneglect’. This bias is attenuated, or shifted rightwards, with decreasing alertness over time, consistent with theoretical models proposing that pseudoneglect is a result of the right hemisphere׳s dominance in regulating attention. Although this ‘time-on-task effect’ for spatial bias is observed when averaging across whole samples of healthy participants, Benwell, C. S. Y., Thut, G., Learmonth, G., & Harvey, M. (2013b). Spatial attention: differential shifts in pseudoneglect direction with time-on-task and initial bias support the idea of observer subtypes. Neuropsychologia, 51(13), 2747–2756 recently presented evidence that the direction and magnitude of bias exhibited by the participant early in the task (left biased, no bias, or right biased) were stable traits that predicted the direction of the subsequent time-on-task shift in spatial bias. That is, the spatial bias of participants who were initially left biased shifted in a rightward direction with time, whereas that of participants who were initially right biased shifted in a leftward direction. If valid, the data of Benwell et al. are potentially important and may demand a re-evaluation of current models of the neural networks governing spatial attention. Here we use two novel spatial attention tasks in an attempt to confirm the results of Benwell et al. We show that rather than being indicative of true participant subtypes, these data patterns are likely driven, at least in part, by ‘regression towards the mean’ arising from the analysis method employed. Although evidence supports the contention that trait-like individual differences in spatial bias exist within the healthy population, no clear evidence is yet available for participant/observer subtypes in the direction of time-on-task shift in spatial biases.