K. Richard Ridderinkhof

Error-related brain potentials are differentially related to awareness of response errors : Evidence from an antisaccade task

The error negativity (Ne/ERN) and error positivity (Pe) are two components of the event-related brain potential (ERP) that are associated with action monitoring and error detection. To investigate the relation between error processing and conscious self-monitoring of behavior, the present experiment examined whether an Ne and Pe are observed after response errors of which participants are unaware. Ne and Pe measures, behavioral accuracy, and trial-to-trial subjective accuracy judgments were obtained from participants performing an antisaccade task, which elicits many unperceived, incorrect reflex-like saccades. Consistent with previous research, subjectively unperceived saccade errors were almost always immediately corrected, and were associated with faster correction times and smaller saccade sizes than perceived errors. Importantly, irrespective of whether the participant was aware of the error or not, erroneous saccades were followed by a sizable Ne. In contrast, the Pe was much more pronounced for perceived than for unperceived errors. Unperceived errors were characterized by the absence of posterror slowing. These and other results are consistent with the view that the Ne and Pe reflect the activity of two separate error monitoring processes, of which only the later process, reflected by the Pe, is associated with conscious error recognition and remedial action.

Dissociable Components of Error Processing

Abstract: We conducted a literature review to examine the functional significance of the error positivity (Pe), an error-related electrophysiological brain potential often observed in combination with the error negativity (Ne). The review revealed many dissociations between documented effects on the Ne and Pe, suggesting that these components reflect different aspects of error processing. We found little support for the proposed hypotheses that the Pe is associated with the affective processing of errors or with posterror behavioral adaptation. Some support was found for the hypothesis that the Pe reflects conscious recognition of an error. Finally, we discuss the notion that the Pe may reflect a P3b associated with the motivational significance of the error. We conclude that more research is needed to test predictions of the various Pe hypotheses, and that more rigorous investigation of the neural generators of the Pe may contribute to a better understanding of the neurocognitive processes involved in er...

Striatum and pre-SMA facilitate decision-making under time pressure

Human decision-making almost always takes place under time pressure. When people are engaged in activities such as shopping, driving, or playing chess, they have to continually balance the demands for fast decisions against the demands for accurate decisions. In the cognitive sciences, this balance is thought to be modulated by a response threshold, the neural substrate of which is currently subject to speculation. In a speed decision-making experiment, we presented participants with cues that indicated different requirements for response speed. Application of a mathematical model for the behavioral data confirmed that cueing for speed lowered the response threshold. Functional neuroimaging showed that cueing for speed activates the striatum and the pre-supplementary motor area (pre-SMA), brain structures that are part of a closed-loop motor circuit involved in the preparation of voluntary action plans. Moreover, activation in the striatum is known to release the motor system from global inhibition, thereby facilitating faster but possibly premature actions. Finally, the data show that individual variation in the activation of striatum and pre-SMA is selectively associated with individual variation in the amplitude of the adjustments in the response threshold estimated by the mathematical model. These results demonstrate that when people have to make decisions under time pressure their striatum and pre-SMA show increased levels of activation.

A computational account of altered error processing in older age: Dopamine and the error-related negativity

When participants commit errors or receive feedback signaling that they have made an error, a negative brain potential is elicited. According to Holroyd and Coles’s (in press) neurocomputational model of error processing, this error-related negativity (ERN) is elicited when the brain first detects that the consequences of an action are worse than expected. To study age-related changes in error processing, we obtained performance and ERN measures of younger and high-functioning older adults. Experiment 1 demonstrated reduced ERN amplitudes in older adults in the context of otherwise intact brain potentials. This result could not be attributed to uncertainty about the required response in older adults. Experiment 2 revealed impaired performance and reduced response- and feedback-related ERNs of older adults in a probabilistic learning task. These age changes could be simulated by manipulation of a single parameter of the neurocomputational model, this manipulation corresponding to weakened phasic activity of the mesencephalic dopamine system.

Conscious perception of errors and its relation to the anterior insula

To detect erroneous action outcomes is necessary for flexible adjustments and therefore a prerequisite of adaptive, goal-directed behavior. While performance monitoring has been studied intensively over two decades and a vast amount of knowledge on its functional neuroanatomy has been gathered, much less is known about conscious error perception, often referred to as error awareness. Here, we review and discuss the conditions under which error awareness occurs, its neural correlates and underlying functional neuroanatomy. We focus specifically on the anterior insula, which has been shown to be (a) reliably activated during performance monitoring and (b) modulated by error awareness. Anterior insular activity appears to be closely related to autonomic responses associated with consciously perceived errors, although the causality and directions of these relationships still needs to be unraveled. We discuss the role of the anterior insula in generating versus perceiving autonomic responses and as a key player in balancing effortful task-related and resting-state activity. We suggest that errors elicit reactions highly reminiscent of an orienting response and may thus induce the autonomic arousal needed to recruit the required mental and physical resources. We discuss the role of norepinephrine activity in eliciting sufficiently strong central and autonomic nervous responses enabling the necessary adaptation as well as conscious error perception.

Cognitive Bias Modification and Cognitive Control Training in Addiction and Related Psychopathology Mechanisms, Clinical Perspectives, and Ways Forward

The past decade has witnessed a surge in research on training paradigms aimed at directly influencing cognitive processes in addiction and other psychopathology. Broadly, two avenues have been explored: In the first, the aim was to change maladaptive cognitive motivational biases (cognitive bias modification); in the second, the aim was to increase general control processes (e.g., working memory capacity). These approaches are consistent with a dual-process perspective in which psychopathology is related to a combination of disorder-specific impulsive processes and weak general abilities to control these impulses in view of reflective longer-term considerations. After reviewing the evidence for dual-process models in addiction, we discuss a number of critical issues, along with suggestions for further research. We argue that theoretical advancement, along with a better understanding of the underlying neurocognitive processes, is crucial for adequately responding to recent criticisms on dual-process models and for optimizing training paradigms for use in clinical practice.

Function and Structure of the Right Inferior Frontal Cortex Predict Individual Differences in Response Inhibition: A Model-Based Approach

The ability to suppress ones impulses and actions constitutes a fundamental mechanism of cognitive control, thought to be subserved by the right inferior frontal cortex (rIFC). The neural bases of more selective inhibitory control when selecting between two actions have thus far remained articulated with less precision. Selective inhibition can be explored in detail by extracting parameters from response time (RT) distributions as derived from performance in the Simon task. Individual differences in RT distribution parameters not only can be used to probe the efficiency and temporal dynamics of selective response inhibition, but also allow a more detailed analysis of functional neuroimaging data. Such model-based analyses, which capitalize on individual differences, have demonstrated that selective response inhibition is subserved by the rIFC. The aim of the present study was to specify the relationship between model parameters of response inhibition and their functional and structural underpinnings in the brain. Functional magnetic resonance imaging (fMRI) data were obtained from healthy participants while performing a Simon task in which irrelevant information can activate incorrect responses that should be selectively inhibited in favor of selecting the correct response. In addition, structural data on the density of coherency of white matter tracts were obtained using diffusion tensor imaging (DTI). The analyses aimed at quantifying the extent to which RT distribution measures of response inhibition are associated with individual differences in both rIFC function and structure. The results revealed a strong correlation between the model parameters and both fMRI and DTI characteristics of the rIFC. In general, our results reveal that individual differences in inhibition are accompanied by differences in both brain function and structure.

Unconscious Activation of the Prefrontal No-Go Network

Cognitive control processes involving prefrontal cortex allow humans to overrule and inhibit habitual responses to optimize performance in new and challenging situations, and traditional views hold that cognitive control is tightly linked with consciousness. We used functional magnetic resonance imaging to investigate to what extent unconscious “no-go” stimuli are capable of reaching cortical areas involved in inhibitory control, particularly the inferior frontal cortex (IFC) and the pre-supplementary motor area (pre-SMA). Participants performed a go/no-go task that included conscious (weakly masked) no-go trials, unconscious (strongly masked) no-go trials, as well as go trials. Replicating typical neuroimaging findings, response inhibition on conscious no-go stimuli was associated with a (mostly right-lateralized) frontoparietal “inhibition network.” Here, we demonstrate, however, that an unconscious no-go stimulus also can activate prefrontal control networks, most prominently the IFC and the pre-SMA. Moreover, if it does so, it brings about a substantial slowdown in the speed of responding, as if participants attempted to inhibit their response but just failed to withhold it completely. Interestingly, overall activation in this “unconscious inhibition network” correlated positively with the amount of slowdown triggered by unconscious no-go stimuli. In addition, neural differences between conscious and unconscious control are revealed. These results expand our understanding of the limits and depths of unconscious information processing in the human brain and demonstrate that prefrontal cognitive control functions are not exclusively influenced by conscious information.

To PE or not to PE: A P3-like ERP component reflecting the processing of response errors

ERP studies have highlighted several electrocortical components that can be observed when people make errors. We propose that the P(E) reflects processes functionally similar to those reflected in the P3 and that the P(E) and P3 should covary. We speculate that these processes refer to the motivational significance of rare target stimuli in case of the P3 and of salient performance errors in case of the P(E). Here we investigated whether P(E) amplitude after errors in a Simon task is correlated specifically to varying target-target intervals in a visual oddball task, a factor known to parametrically affect P3 amplitude. The amplitude of the P(E), but not the N(E), was observed to covary with the effect of target-target interval on P3 amplitude. The specificity of this novel finding supports the notion that the P(E) and P3 reflect similar neurocognitive processes as possibly involved in the conscious processing of motivationally significant events.

Grey matter alterations associated with cannabis use: results of a VBM study in heavy cannabis users and healthy controls

Cannabis abuse is related to impairments in a broad range of cognitive functions. However, studies on cannabis abuse in relation to brain structure are sparse and results are inconsistent, probably due to differences in imaging methodology, severity of cannabis abuse, and use of other substances. The goal of the current MRI study was to investigate brain morphology related to current and lifetime severity of cannabis use and dependence in heavy cannabis users without intensive use of other illicit drugs. Voxel-based morphometry was used to assess differences in regional grey and white matter volume between 33 heavy cannabis users and 42 matched controls. Within heavy cannabis users, grey and white matter volume was correlated with measures of cannabis use and dependence. Analyses were focused a priori on the orbitofrontal cortex, anterior cingulate cortex, striatum, amygdala, hippocampus, and cerebellum, regions implicated in substance dependence and/or with high cannabinoid receptor-1 concentrations. Regional grey matter volume in the anterior cerebellum was larger in heavy cannabis users. Within the group of heavy cannabis users, grey matter volume in the amygdala and hippocampus correlated negatively with the amount of cannabis use or dependence. No associations were found between white matter volume and measures of cannabis use or dependence. These findings indicate that associations between heavy cannabis use and altered brain structure are complex. Differential patterns of structural changes for various cannabis use levels imply that alterations in brain structure are associated with specific characteristics of cannabis use and dependence.