EEG-neurofeedback as a tool to modulate cognition and behaviour: a review tutorial

Neurofeedback is attracting renewed interest as a method to self-regulate one’s own brain activity to directly alter the underlying neural mechanisms of cognition and behaviour. It promises new avenues as a method for cognitive enhancement in healthy subjects, but also as a therapeutic tool. In the current article, we present a review tutorial discussing key aspects relevant to the development of EEG neurofeedback studies. In addition, the putative mechanisms underlying neurofeedback learning are considered. We highlight both aspects relevant for the practical application of neurofeedback as well as rather theoretical considerations related to the development of new generation protocols. Important characteristics regarding the set-up of a neurofeedback protocol are outlined in a step-by-step way. All these practical and theoretical considerations are illustrated based on a protocol and results of a frontal-midline theta up-regulation training for the improvement of executive functions. Not least, assessment criteria for the validation of neurofeedback studies as well as general guidelines for the evaluation of training efficacy are discussed

On the effects of multimodal information integration in multitasking

There have recently been considerable advances in our understanding of the neuronal mechanisms underlying multitasking, but the role of multimodal integration for this faculty has remained rather unclear. We examined this issue by comparing different modality combinations in a multitasking (stop-change) paradigm. In-depth neurophysiological analyses of event-related potentials (ERPs) were conducted to complement the obtained behavioral data. Specifically, we applied signal decomposition using second order blind identification (SOBI) to the multi-subject ERP data and source localization. We found that both general multimodal information integration and modality-specific aspects (potentially related to task difficulty) modulate behavioral performance and associated neurophysiological correlates. Simultaneous multimodal input generally increased early attentional processing of visual stimuli (i.e. P1 and N1 amplitudes) as well as measures of cognitive effort and conflict (i.e. central P3 amplitudes). Yet, tactile-visual input caused larger impairments in multitasking than audio-visual input. General aspects of multimodal information integration modulated the activity in the premotor cortex (BA 6) as well as different visual association areas concerned with the integration of visual information with input from other modalities (BA 19, BA 21, BA 37). On top of this, differences in the specific combination of modalities also affected performance and measures of conflict/effort originating in prefrontal regions (BA 6)

Filling the void - enriching the feature space of successful stopping

The ability to inhibit behavior is crucial for adaptation in a fast changing environment and is commonly studied with the stop signal task. Current EEG research mainly focuses on the N200 and P300 ERPs and corresponding activity in the theta and delta frequency range, thereby leaving us with a limited understanding of the mechanisms of response inhibition. Here, 15 functional networks were estimated from time-frequency transformed EEG recorded during processing of a visual stop signal task. Cortical sources underlying these functional networks were reconstructed, and a total of 45 features, each representing spectrally and temporally coherent activity, were extracted to train a classifier to differentiate between go and stop trials. A classification accuracy of 85.55% for go and 83.85% for stop trials was achieved. Features capturing fronto-central delta- and theta activity, parieto-occipital alpha, fronto-central as well as right frontal beta activity were highly discriminating between trial-types. However, only a single network, comprising a feature defined by oscillatory activity below 12 Hz, was associated with a generator in the opercular region of the right inferior frontal cortex and showed the expected associations with behavioral inhibition performance. This study pioneers by providing a detailed ranking of neural features regarding their information content for stop and go differentiation at the single-trial level, and may further be the first to identify a scalp EEG marker of the inhibitory control network. This analysis allows for the characterization of the temporal dynamics of response inhibition by matching electrophysiological phenomena to cortical generators and behavioral inhibition performanc

Event-Related Potential Correlates of Performance-Monitoring in a Lateralized Time-Estimation Task

Performance-monitoring as a key function of cognitive control covers a wide range of diverse processes to enable goal directed behavior and to avoid maladjustments. Several event-related brain potentials (ERP) are associated with performance-monitoring, but their conceptual background differs. For example, the feedback-related negativity (FRN) is associated with unexpected performance feedback and might serve as a teaching signal for adaptational processes, whereas the error-related negativity (ERN) is associated with error commission and subsequent behavioral adaptation. The N2 is visible in the EEG when the participant successfully inhibits a response following a cue and thereby adapts to a given stop-signal. Here, we present an innovative paradigm to concurrently study these different performance-monitoring-related ERPs. In 24 participants a tactile time-estimation task interspersed with infrequent stop-signal trials reliably elicited all three ERPs. Sensory input and motor output were completely lateralized, in order to estimate any hemispheric processing preferences for the different aspects of performance monitoring associated with these ERPs. In accordance with the literature our data suggest augmented inhibitory capabilities in the right hemisphere given that stop-trial performance was significantly better with left- as compared to right-hand stop-signals. In line with this, the N2 scalp distribution was generally shifted to the right in addition to an ipsilateral shift in relation to the response hand. Other than that, task lateralization affected neither behavior related to error and feedback processing nor ERN or FRN. Comparing the ERP topographies using the Global Map Dissimilarity index, a large topographic overlap was found between all considered components.With an evenly distributed set of trials and a split-half reliability for all ERP components ≥.85 the task is well suited to efficiently study N2, ERN, and FRN concurrently which might prove useful for group comparisons, especially in clinical populations

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.</p

A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task.

Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis

On the effects of multimodal information integration in multitasking

There have recently been considerable advances in our understanding of the neuronal mechanisms underlying multitasking, but the role of multimodal integration for this faculty has remained rather unclear. We examined this issue by comparing different modality combinations in a multitasking (stop-change) paradigm. In-depth neurophysiological analyses of event-related potentials (ERPs) were conducted to complement the obtained behavioral data. Specifically, we applied signal decomposition using second order blind identification (SOBI) to the multi-subject ERP data and source localization. We found that both general multimodal information integration and modality-specific aspects (potentially related to task difficulty) modulate behavioral performance and associated neurophysiological correlates. Simultaneous multimodal input generally increased early attentional processing of visual stimuli (i.e. P1 and N1 amplitudes) as well as measures of cognitive effort and conflict (i.e. central P3 amplitudes). Yet, tactile-visual input caused larger impairments in multitasking than audio-visual input. General aspects of multimodal information integration modulated the activity in the premotor cortex (BA 6) as well as different visual association areas concerned with the integration of visual information with input from other modalities (BA 19, BA 21, BA 37). On top of this, differences in the specific combination of modalities also affected performance and measures of conflict/effort originating in prefrontal regions (BA 6)