Pre-motor deficits in left spatial neglect: An EEG study on Contingent Negative Variation (CNV) and response-related beta oscillatory activity

Neglect symptoms are related to a prediction-hypersensitivity in ipsilesional space

The precise cognitive mechanisms underlying spatial neglect are not fully understood. Recent studies have provided the first evidence for aberrant behavioral and electrophysiological prediction and prediction error responses in patients with neglect, but also in right-hemispheric (RH) stroke patients without neglect. For prediction-dependent attention, as assessed with Posner-type cueing paradigms with volatile cue-target contingencies, studies in healthy volunteers point to a crucial role of the right temporo-parietal junction (rTPJ) - as part of a network commonly disrupted in neglect. In order to study altered prediction-dependent attention in patients with RH damage and neglect, the present study employed a spatial cueing paradigm with unsignalled changes in the cue's predictive value in 26 RH patients, 21 left-hemispheric (LH) patients, and 33 healthy elderly controls. The inference of the changing cue's predictive value was assessed with a Rescorla-Wagner learning model of response times (RTs) and participants' ratings. We tested for lesion-side-dependent relationships between the computational model parameters, ratings, and neuropsychological performance. Moreover, we investigated links between the behavioral signatures of predictive processing and lesion anatomy (lesion location and disconnection). The results provided no evidence for a predictive inference deficit, but revealed a correlation between a hypersensitivity of RTs to inferred predictions for ipsilesional stimuli and neglect symptoms in RH patients. Irrespective of symptoms of neglect, the rating of the cue's predictive value deviated more from the actual values in RH patients. RT hypersensitivity for ipsilesional targets was linked to disconnection within fronto-parietal, fronto-occipital, and temporo-parietal pathways. These findings provide novel insights into the role of altered prediction-dependent processing for neglect as assessed by different read-outs, highlighting an exaggerated response adaption to predictions of ipsilesional stimuli.

Electrophysiological measures of patients with unilateral spatial neglect after brain disease: A systematic review

INTRODUCTION

The investigation of brainwave changes during the recovery process of unilateral spatial neglect (USN) has garnered considerable attention in recent years. This paper presents an updated overview of the evolving brainwave patterns during USN rehabilitation, aiming to predict clinical outcomes and guide the selection of effective recovery strategies.

METHODS

A systematic review was conducted, encompassing English literature published up to June 2024. Databases including PubMed, Web of Science, and clinical trials were utilized. The included studies assessed brainwaves using electroencephalography (EEG) in at least one group with USN. However, the diverse nature of these studies posed challenges for a quantitative synthesis.

RESULTS

The final quantitative synthesis comprised 36 studies, incorporating a total of 4517 data points. The analysis revealed abnormalities in alpha, beta, and gamma brainwave activity, along with alterations in the functional monitoring of the alpha band during USN rehabilitation. Additionally, reductions were observed in specific brainwave components such as P1, N1, P2, P300, early directing attention negativity (EDAN), late directing attention positivity (LDAP), and contingent negative variation (CNV). However, findings regarding measures of synchrony, connectivity, and evoked responses across different frequency bands exhibited variability.

CONCLUSIONS

Various indicators of brainwave activity displayed changes at different stages of post-stroke neglect rehabilitation, highlighting the significance of neural network dysfunction in this process. Nonetheless, due to the diversity of the studies, further investigation is necessary to achieve a more comprehensive understanding in future research endeavors.

Risk-Taking Is Associated with Decreased Subjective Value Signals and Increased Prediction Error Signals in the Hot Columbia Card Task

It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.

The Neurophysiological Features Associated with Unilateral Spatial Neglect Recovery: A Scoping Review

The purpose of this scoping review is to provide updated information on the neural basis and neurophysiological features associated with unilateral spatial neglect (USN) recovery. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) framework and identified 16 relevant papers from the databases. Critical appraisal was performed by two independent reviewers using a standardized appraisal instrument developed by the PRISMA-ScR. We identified and categorized investigation methods for the neural basis and neurophysiological features of USN recovery after stroke using magnetic resonance imaging (MRI), functional MRI, and electroencephalography (EEG). This review found two brain-level mechanisms underlying USN recovery at the behavioral level. These include the absence of stroke-related damage to the right ventral attention network during the acute phase and compensatory recruitment of analogous areas of the undamaged opposite hemisphere and prefrontal cortex during visual search tasks in the subacute or later phases. However, the relationship between the neural and neurophysiological findings and improvements in USN-related activities of daily living remains unknown. This review adds to the growing body of evidence regarding the neural mechanisms underlying USN recovery.

Detection of Stroke-Induced Visual Neglect and Target Response Prediction Using Augmented Reality and Electroencephalography

We aim to build a system incorporating electroencephalography (EEG) and augmented reality (AR) that is capable of identifying the presence of visual spatial neglect (SN) and mapping the estimated neglected visual field. An EEG-based brain-computer interface (BCI) was used to identify those spatiospectral features that best detect participants with SN among stroke survivors using their EEG responses to ipsilesional and contralesional visual stimuli. Frontal-central delta and alpha, frontal-parietal theta, Fp1 beta, and left frontal gamma were found to be important features for neglect detection. Additionally, temporal analysis of the responses shows that the proposed model is accurate in detecting potentially neglected targets. These targets were predicted using common spatial patterns as the feature extraction algorithm and regularized discriminant analysis combined with kernel density estimation for classification. With our preliminary results, our system shows promise for reliably detecting the presence of SN and predicting visual target responses in stroke patients with SN.

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.