The Sustained Influence of an Error on Future Decision-Making

Post-error slowing (PES) is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants) of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants' response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters' role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error

Rapid adaptive adjustments of selective attention following errors revealed by the time course of steady-state visual evoked potentials

Funding This work was supported by a grant from the Biotechnology and Biological Sciences Research Council (BB/P002404/1 to S.K.A.). Acknowledgements Correspondence should be addressed to Marco Steinhauser, Catholic University of Eichstätt-Ingolstadt, Ostenstraße 25, 85072 Eichstätt, Germany.Peer reviewedPublisher PD

The cerebellum and motor dysfunction in neuropsychiatric disorders

The cerebellum is densely interconnected with sensory-motor areas of the cerebral cortex, and in man, the great expansion of the association areas of cerebral cortex is also paralleled by an expansion of the lateral cerebellar hemispheres. It is therefore likely that these circuits contribute to non-motor cognitive functions, but this is still a controversial issue. One approach is to examine evidence from neuropsychiatric disorders of cerebellar involvement. In this review, we narrow this search to test whether there is evidence of motor dysfunction associated with neuropsychiatric disorders consistent with disruption of cerebellar motor function. While we do find such evidence, especially in autism, schizophrenia and dyslexia, we caution that the restricted set of motor symptoms does not suggest global cerebellar dysfunction. Moreover, these symptoms may also reflect involvement of other, extra-cerebellar circuits and detailed examination of specific sub groups of individuals within each disorder may help to relate such motor symptoms to cerebellar morphology

Midbrain Dopamine Neurons Signal Belief in Choice Accuracy during a Perceptual Decision

Central to the organization of behavior is the ability to predict the values of outcomes to guide choices. The accuracy of such predictions is honed by a teaching signal that indicates how incorrect a prediction was (“reward prediction error,” RPE). In several reinforcement learning contexts, such as Pavlovian conditioning and decisions guided by reward history, this RPE signal is provided by midbrain dopamine neurons. In many situations, however, the stimuli predictive of outcomes are perceptually ambiguous. Perceptual uncertainty is known to influence choices, but it has been unclear whether or how dopamine neurons factor it into their teaching signal. To cope with uncertainty, we extended a reinforcement learning model with a belief state about the perceptually ambiguous stimulus; this model generates an estimate of the probability of choice correctness, termed decision confidence. We show that dopamine responses in monkeys performing a perceptually ambiguous decision task comply with the model’s predictions. Consequently, dopamine responses did not simply reflect a stimulus’ average expected reward value but were predictive of the trial-to-trial fluctuations in perceptual accuracy. These confidence-dependent dopamine responses emerged prior to monkeys’ choice initiation, raising the possibility that dopamine impacts impending decisions, in addition to encoding a post-decision teaching signal. Finally, by manipulating reward size, we found that dopamine neurons reflect both the upcoming reward size and the confidence in achieving it. Together, our results show that dopamine responses convey teaching signals that are also appropriate for perceptual decisions

Unraveling the influence of trial-based motivational changes on performance monitoring stages in a flanker task

Performance monitoring (PM) is a vital component of adaptive behavior and known to be influenced by motivation. We examined effects of potential gain (PG) and loss avoidance (LA) on neural correlates of PM at different processing stages, using a task with trial-based changes in these motivational contexts. Findings suggest more attention is allocated to the PG context, with higher amplitudes for respective correlates of stimulus and feedback processing. The PG context favored rapid responses, while the LA context emphasized accurate responses. Lower response thresholds in the PG context after correct responses derived from a drift–diffusion model also indicate a more approach-oriented response style in the PG context. This cognitive shift is mirrored in neural correlates: negative feedback in the PG context elicited a higher feedback-related negativity (FRN) and higher theta power, whereas positive feedback in the LA context elicited higher P3a and P3b amplitudes, as well as higher theta power. There was no effect of motivational context on response-locked brain activity. Given the similar frequency of negative feedback in both contexts, the elevated FRN and theta power in PG trials cannot be attributed to variations in reward prediction error. The observed variations in the FRN indicate that the effect of outcome valence is modulated by motivational salience

Alcohol Affects the P3 Component of an Adaptive Stop Signal Task ERP

BACKGROUND The P3 component of the event-related potential (ERP) has been particularly useful in alcohol research for identifying endophenotypes of alcohol use disorder (AUD) risk in sober subjects. However, practice and/or fatigue reduces P3 amplitude, limiting the ability to ascertain acute and adaptive effects of alcohol exposure. Here, we report acute alcohol effects on P3 amplitude and latency using an adaptive stop signal task (aSST). METHODS One hundred and forty eight nondependent moderate to heavy social drinkers, age 21 to 27, participated in 2 single-blind, alcohol or placebo, counterbalanced sessions approximately one week apart. During each session, subjects performed an adaptive stop signal task (aSST) at (1) baseline, (2) upon reaching the target 60 mg/dL breath alcohol concentration or at the equivalent time during the placebo session, and (3) approximately 135 minutes later while the breath alcohol concentration was clamped. Here, we report on differences between baseline and first subsequent measurements across the experimental sessions. During each aSST run, the stop signal delay (SSD, the time between stop and go signals) adjusted trial-by-trial based on the subject’s performance. RESULTS The aSST reliably generated a STOP P3 component that did not change significantly with repeated task performance. The pre-infusion SSD distribution was bimodal, with mean values several hundred msec apart (FAST: 153 msec and SLOW: 390 msec). This suggested different response strategies: FAST SSD favoring “going” over “stopping,” and SLOW SSD favoring “stopping” over “going”. Exposure to alcohol at 60 mg/dL differentially affected the amplitude and latency of the STOP P3 according to SSD group. Alcohol significantly reduced P3 amplitude in the SLOW SSD compared to FAST SSD group, but significantly increased P3 latency in the FAST SSD compared to SLOW SSD group. CONCLUSIONS The aSST is a robust and sensitive task for detecting alcohol induced changes in inhibition behavior as measured by the P3 component in a within subject design. Alcohol was associated with P3 component changes which varied by SSD group, suggesting a differential effect as a function of task strategy. Overall, the data support the potential utility of the aSST in the detection of alcohol response related AUD risk

Neural dynamics of selective attention to speech in noise

This thesis investigates how the neural system instantiates selective attention to speech in challenging acoustic conditions, such as spectral degradation and the presence of background noise. Four studies using behavioural measures, magneto- and electroencephalography (M/EEG) recordings were conducted in younger (20–30 years) and older participants (60–80 years). The overall results can be summarized as follows. An EEG experiment demonstrated that slow negative potentials reflect participants’ enhanced allocation of attention when they are faced with more degraded acoustics. This basic mechanism of attention allocation was preserved at an older age. A follow-up experiment in younger listeners indicated that attention allocation can be further enhanced in a context of increased task-relevance through monetary incentives. A subsequent study focused on brain oscillatory dynamics in a demanding speech comprehension task. The power of neural alpha oscillations (~10 Hz) reflected a decrease in demands on attention with increasing acoustic detail and critically also with increasing predictiveness of the upcoming speech content. Older listeners’ behavioural responses and alpha power dynamics were stronger affected by acoustic detail compared with younger listeners, indicating that selective attention at an older age is particularly dependent on the sensory input signal. An additional analysis of listeners’ neural phase-locking to the temporal envelopes of attended speech and unattended background speech revealed that younger and older listeners show a similar segregation of attended and unattended speech on a neural level. A dichotic listening experiment in the MEG aimed at investigating how neural alpha oscillations support selective attention to speech. Lateralized alpha power modulations in parietal and auditory cortex regions predicted listeners’ focus of attention (i.e., left vs right). This suggests that alpha oscillations implement an attentional filter mechanism to enhance the signal and to suppress noise. A final behavioural study asked whether acoustic and semantic aspects of task-irrelevant speech determine how much it interferes with attention to task-relevant speech. Results demonstrated that younger and older adults were more distracted when acoustic detail of irrelevant speech was enhanced, whereas predictiveness of irrelevant speech had no effect. All findings of this thesis are integrated in an initial framework for the role of attention for speech comprehension under demanding acoustic conditions

Adaptation and the Perception of Radiological Images

Radiologists must classify and interpret medical images on the basis of visual inspection. We examined how an observer's visual sensitivity and perception might change as they view and thus adapt to the characteristic properties of radiological scans. Measurements were focused on the effects of adaptation to images of normal mammograms, and were tested primarily in observers who were not trained radiologists. Mammograms have steeper power spectra (slopes of ~-3) than natural images (~-2) and thus are physically blurry. Adapting to them produced shifts in the perceived spectrum of filtered noise consistent with adaptation to blur, even though this adaptation does not lead to measurable changes in the contrast sensitivity function. Strong aftereffects in the appearance of the images were also found when observers judged the perceived texture of the images. For example, tissue density in mammograms is routinely classified and ranges from "dense" to "fatty." Adaptation to dense images caused an intermediate image to appear more fatty and vice versa. Our results thus suggest that observers can selectively adapt to the properties of radiological images, and this could potentially be an important factor in the perception and learning of radiological images. In a further study we explored whether adaptation could enhance visual inspection of radiological images, specifically to aid observers in identifying abnormalities by adapting out or discounting the expected visual characteristics of the background. Observers searched for simulated lesions (Gaussian targets) added at random locations in the images. Prior adaptation to the images allowed the targets to be located more quickly, and this performance gain was selective for the tissue type and thus the visual texture defining the background. These improvements in visual search provide a novel demonstration of the advantages of spatial pattern adaptation within contexts that closely mimic routine visual tasks and settings. Finally, we explored the neural correlates of these adaptation aftereffects by measuring ERP's while observers adapted to the different textural properties of the mammogram images (dense or fatty). There was no significant difference of adapt condition in the component waveforms when tasked with categorizing the scans based upon their density classifications. In contrast, there was a significant effect of adaptation when observers were signaling target presence or absence. This significant difference was characterized by an enhancement of the neural response at early timepoints in occipital areas. Additionally, following adaptation we observed a divergence in the target present and absent waveforms at approximately 370 ms post-stimulus onset in frontal recording sites. These results suggest that target detection involves a form of the P300 component. Taken together these studies represent the first comprehensive analysis of the influence of adaption on the critically important visual judgments involved in interpreting and inspecting medical images. &#8195