Distinct mechanisms of attentional suppression: exploration of trait factors underlying cued- and learned-suppression.

Attention allows us to focus on relevant information while ignoring distractions. Effective suppression of distracting information is crucial for efficient visual search. Recent studies have developed two paradigms to investigate attentional suppression: cued-suppression which is based on top-down control, and learned-suppression which is based on selection history. While both types of suppression reportedly engage proactive control, it remains unclear whether they rely on shared mechanisms. This study aimed to determine the relationship between cued- and learned-suppression. In a within-subjects design, 54 participants performed a cued-suppression task where pre-cues indicated upcoming target or distractor colors, and a learned-suppression task where a salient color distractor was present or absent. No significant correlation emerged between performance in the two tasks, suggesting distinct suppression mechanisms. Cued-suppression correlated with visual working memory capacity, indicating reliance on explicit control. In contrast, learned-suppression correlated with everyday distractibility, suggesting implicit control based on regularities. These results provide evidence for heterogeneous proactive control mechanisms underlying cued- and learned-suppression. While both engage inhibition, cued-suppression relies on deliberate top-down control modulated by working memory, whereas learned-suppression involves implicit suppression shaped by selection history and distractibility traits.

Individual deviations from normative electroencephalographic connectivity predict antidepressant response.

BACKGROUND: Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo, partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment. Here we develop a novel normative modeling framework to quantify individual deviations in psychopathological dimensions that offers a promising avenue for the personalized treatment for psychiatric disorders. METHODS: We built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients (102 sertraline-medicated and 119 placebo-medicated). Hamilton depression rating scale (HAMD-17) was assessed at both baseline and after the eight-week antidepressant treatment. RESULTS: We successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between sertraline and placebo responses. CONCLUSIONS: Our findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective personalized MDD treatment. TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094.

Individual Deviations from Normative Electroencephalographic Connectivity Predict Antidepressant Response.

Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo. This modest efficacy is partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment - the approved antidepressants only benefit a portion of patients, calling for personalized psychiatry based on individual-level prediction of treatment responses. Normative modeling, a framework that quantifies individual deviations in psychopathological dimensions, offers a promising avenue for the personalized treatment for psychiatric disorders. In this study, we built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients. We successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between treatment responses. Our findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective MDD treatment.

Mind-wandering does not always rhyme with proactive functioning! Changes in the temporal dynamics of the mPFC-mediated theta oscillations during moments of mind-wandering.

The reduced engagement of the cognitive control network has been documented widely during mind-wandering (MW). However, it remains unknown how MW affects the neural dynamics of cognitive control processes. From this perspective, we explored neural dynamics mediated by the medial prefrontal cortex (mPFC). Their engagement can be both transient (or reactive) and anticipated (or proactive). A total of fortyseven healthy subjects (37 females) were engaged in a long-lasting sustained-attention Go/NoGo task. Subjective probes were used to detect MW episodes. Channel-based EEG time-frequency analysis was performed to measure the theta oscillations, an index of the mPFC activity. The theta oscillations were computed immediately after conflictual NoGo trials to explore the reactive engagement of the mPFC. Proactive control was measured on the Go trials preceded the NoGo. Behaviorally, periods of MW were associated with an increase in errors and in RT variability in comparison to on-task periods. The analysis of the frontal midline theta power (MFθ) revealed that MW periods were associated with lower anticipated/proactive engagement and similar transient/reactive engagement of mPFC-mediated processes. Moreover, the communication between the mPFC and the DLPFC, as revealed by the poorer theta synchronization between these two regions, was also impaired during MW periods. Our results provide new insights about performance impairment during MW. They could be an important step in improving the existing understanding of the altered performances that are reported for some disorders that are known to be associated with excessive MW.

Neurophysiological Measures of Proactive and Reactive Control in Negative Template Use.

In a visual search task, knowing features of distractors in advance leads to a more efficient visual search. Although previous studies suggested that the benefits of these negative cues rely on attentional control, it is unclear whether proactive or reactive control is involved. In this study, we analyzed the EEG data of participants performing a visual search task (n = 14). Participants searched for a shape-defined target after receiving a positive cue (target color), negative cue (distractor color), or neutral cue (non-informative). To examine proactive control, we measured EEG after the cue onset but before visual search. Our time-frequency analysis revealed a higher power of theta oscillations over frontoparietal regions after the negative cues compared with the positive and neutral cues, as well as higher theta phase synchronization within the prefrontal region, demonstrating negative cues rely more heavily on proactive control compared with other cue types. To examine reactive control, we measured EEG after the search onset. We found a lateralization of posterior alpha power toward the target side in both positive and negative cues conditions, with a later lateralization observed after negative cues. Interestingly, we observed a significant relationship between the increase of proactive theta power after negative cues and the decrease of reactive alpha power after the search. This suggests the coordination of proactive and reactive mechanisms lead to the most efficient search.

Enhanced temporal resolution of vision in action video game players.

Video game play has been suggested to improve visual and attention processing. Nevertheless, while action video game play is highly dynamic, there is scarce research on how information is temporally discriminated at the millisecond level. This cross-sectional study investigates whether temporal discrimination at the millisecond level in vision varies across action video game players (VGPs; N = 23) and non-video game players (NVGPs; N = 23). Participants discriminated synchronous from asynchronous onsets of two visual targets in virtual reality, while their EEG and oculomotor movements were recorded. Results show an increased sensitivity to short asynchronies (11, 33 and 66 ms) in VGPs compared with NVGPs, which was especially marked at the start of the task, suggesting better temporal discrimination abilities. Pre-targets oculomotor freezing - the inhibition of small fixational saccades - was associated with correct temporal discrimination, probably revealing attentional preparation. However, this parameter did not differ between groups. EEG and reconstruction analyses suggest that the enhancement of temporal discrimination in VGPs during temporal discrimination is related to parieto-occipital processing, and a reduction of alpha-band (8-14 Hz) power and inter-trial phase coherence. Overall, the study reveals an enhanced ability in action video game players to discriminate in time visual events in close temporal proximity combined with reduced alpha-band oscillatory activities. Consequently, playing action video games is associated with an improved temporal resolution of vision.

Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression.

Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication. In this study, we investigate whether individualized brain functional connectivity (FC) can define more predictable signatures of antidepressant and placebo treatment in MDD. The data used in the present work were collected by the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Patients (N = 296) were randomly assigned to antidepressant sertraline or placebo double-blind treatment for 8 weeks. The whole-brain FC networks were constructed from pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI). Then, FC was individualized by removing the common components extracted from the raw baseline FC to train regression-based connectivity predictive models. With individualized FC features, the established prediction models successfully identified signatures that explained 22% variance for the sertraline group and 31% variance for the placebo group in predicting HAMD17 change. Compared with the raw FC-based models, the individualized FC-defined signatures significantly improved the prediction performance, as confirmed by cross-validation. For sertraline treatment, predictive FC metrics were predominantly located in the left middle temporal cortex and right insula. For placebo, predictive FC metrics were primarily located in the bilateral cingulate cortex and left superior temporal cortex. Our findings demonstrated that through the removal of common FC components, individualization of FC metrics enhanced the prediction performance compared to raw FC. Associated with previous MDD clinical studies, our identified predictive biomarkers provided new insights into the neuropathology of antidepressant and placebo treatment.

Neurocognitive analyses reveal that video game players exhibit enhanced implicit temporal processing.

Winning in action video games requires to predict timed events in order to react fast enough. In these games, repeated waiting for enemies may help to develop implicit (incidental) preparation mechanisms. We compared action video game players and non-video game players in a reaction time task involving both implicit time preparations and explicit (conscious) temporal attention cues. Participants were immersed in virtual reality and instructed to respond to a visual target appearing at variable delays after a warning signal. In half of the trials, an explicit cue indicated when the target would occur after the warning signal. Behavioral, oculomotor and EEG data consistently indicate that, compared with non-video game players, video game players better prepare in time using implicit mechanisms. This sheds light on the neglected role of implicit timing and related electrophysiological mechanisms in gaming research. The results further suggest that game-based interventions may help remediate implicit timing disorders found in psychiatric populations.

Conjoint fluctuations of PFC-mediated processes and behavior: An investigation of error-related neural mechanisms in relation to sustained attention.

The ability to detect errors, which derives from the medial prefrontal cortex (mPFC), is crucial to maintain attention over a long period of time. While impairment of this ability has been reported in patients with sustained attention disruption, the role mPFC-mediated processes play in the intra-individual fluctuation of sustained attention remains an open question. In this context, we computed the variance time course of reaction time (RT) of 42 healthy individuals to distinguish intra-individual periods of low and high performance instability, assumed to represent optimal and suboptimal attentional states, when performing a sustained Go/NoGo task. Analysis of the neurophysiological mechanisms of response monitoring revealed a specific reduction in the error-related negativity (ERN) amplitude and frontal midline theta power during periods of high compared to low RT variability, but only in individuals with a higher standard deviation of reaction time (SD-RT). Concerning post-error adaptation, an increase in the correct-related negativity (CRN) amplitude as well as the frontal lateral theta power on trials following errors was observed in individuals with lower SD-RT but not in those with higher SD-RT. Our results thus show that individuals with poor sustained attention ability exhibit altered post-error adaptation and attentional state-dependent efficiency of error monitoring. Conversely, individuals with good sustained attention performances retained their post-error adaptation and response monitoring regardless of the attentional periods. These findings reveal the critical role of the action-monitoring system in intra-individual behavioral stability and highlight the importance of considering attentional states when studying mPFC-mediated processes, especially in subjects with low sustained attention ability.

Investigation of electrophysiological precursors of attentional errors in schizophrenia: Toward a better understanding of abnormal proactive control engagement.

Impaired cognitive control has been associated with the occurrence of attentional errors in those with schizophrenia. However, the extent of altered proactive or reactive control underlying such errors is still unknown. Twenty-two patients with schizophrenia and 21 healthy matched controls performed a detection task (i.e., the continuous temporal expectancy task). Electrophysiological measures of proactive and reactive control were based on two periods of interest: during the target presentation (the critical window) and four trials before the critical window. Regarding the proactive mode, patients with schizophrenia exhibited a specific decrease in frontal midline theta power during the critical window before a miss compared to a correct detection. In contrast, the contingent negative variation amplitude was altered regardless of the response type, four trials before the critical window. Regarding the reactive mode, a reduced P3 amplitude was revealed later before a miss than a correct detection with differences apparent only two trials before the critical window in patients with schizophrenia, whereas it was observable up to four trials prior in healthy controls. Moreover, only the P3 amplitude reduction in patients with schizophrenia predicted the miss rate and was anti-correlated with the clinical symptoms. Thus, our results revealed a specific impairment of the proactive goal-updating process before an error and an altered implementation of the endogenous proactive mode engagement regardless of the response type. The results also highlighted the strong relationship between the disrupted reactive mode and the increased rate of attentional errors and severity of the clinical symptoms of schizophrenia.

Impaired Frontal Midline Theta During Periods of High Reaction Time Variability in Schizophrenia.

BACKGROUND: Impairment in cognitive control is one of the most significant cognitive deficits in schizophrenia. Although it has generally been associated with altered engagement of lateral and medial prefrontal cortices, how attention fluctuations affect this engagement is still not known. In this context, we explored sustained (or proactive) and transient (or reactive) control engagement by investigating frontal theta-band oscillations during periods of low- and high-performance instability, assumed to represent intraindividual attentional fluctuations. METHODS: A total of 25 patients with schizophrenia (16 males) and 25 healthy matched control subjects (18 males) performed a long-sustained Go/NoGo task coupled with electroencephalographic recording. Proactive control was explored through frontal lateral theta during trial-by-trial conflict (Go N-1/Go N+1), whereas reactive control was explored through frontal midline theta and the N2 component during current-trial conflict (Go/NoGo). Variance in the time course of reaction time (RT) was computed to identify periods of low and high RT variability in each subject. RESULTS: Patients with schizophrenia exhibited no frontal lateral theta activity regardless of the RT variability periods, whereas in control subjects, this activity was preserved only during periods of low RT variability (less error prone). During these periods, patients exhibited preserved midline frontal theta activity and N2. However, during high RT variability periods (more error prone), the midline theta activity was impaired in patients but preserved in control subjects. CONCLUSIONS: Our results reveal that the efficient engagement of reactive control in patients with schizophrenia and of proactive control in control subjects was state dependent. The findings highlight the importance of accounting for attentional fluctuations when investigating cognitive control impairment in schizophrenia.