Association among childhood adversity and susceptibility to interference during varying salience: two studies in healthy males.

Childhood adversity, a prevalent experience, is related to a higher risk for externalizing and internalizing psychopathology. Alterations in the development of cognitive processes, for example in the attention-interference domain may link childhood adversity and psychopathology. Interfering stimuli can vary in their salience, i.e. ability to capture attentional focus, and valence. However, it is not known if interference by salience or valence is associated with self-reported adversity. In two independent study samples of healthy men (Study 1: n = 44; mean age [standard deviation (SD)] = 25.9 [3.4] years; Study 2: n = 37; 43.5 [9.7] years) we used the attention modulation task (AMT) that probed interference by two attention-modulating conditions, salience and valence separately across repeated target stimuli. The AMT measures the effects of visual distractors (pictures) on the performance of auditory discrimination tasks (target stimuli). We hypothesized that participants reporting higher levels of childhood adversity, measured with the childhood trauma questionnaire, would show sustained interference in trials with lower salience. Due to conflicting reports on the valence-modulation, we tested the valence condition in an exploratory manner. Linear mixed models revealed an interaction between reported childhood adversity and the salience condition across tone presentations in both study samples (Sample 1: p = .03; Sample 2: p = .04), while there were no effects for the valence condition across both studies. Our study suggests that higher self-reported childhood adversity is related to faster processing of target cues during high salience, but slower during low salience conditions. These results hint to the mechanisms linking childhood adversity and psychopathological symptoms in the attentional domain.

Effects of mobile phone electromagnetic fields on brain waves in healthy volunteers.

The interaction between biological tissue and electromagnetic fields (EMF) is a topic of increasing interest due to the rising prevalence of background EMF in the past decades. Previous studies have attempted to measure the effects of EMF on brainwaves using EEG recordings, but are typically hampered by experimental and environmental factors. In this study, we present a framework for measuring the impact of EMF on EEG while controlling for these factors. A Bayesian statistical approach is employed to provide robust statistical evidence of the observed EMF effects. This study included 32 healthy participants in a double-blinded crossover counterbalanced design. EEG recordings were taken from 63 electrodes across 6 brain regions. Participants underwent a measurement protocol comprising two 18-min sessions with alternating blocks of eyes open (EO) and eyes closed (EC) conditions. Group 1 (n = 16) had EMF during the first session and sham during the second session; group 2 (n = 16) had the opposite. Power spectral density plots were generated for all sessions and brain regions. The Bayesian analysis provided statistical evidence for the presence of an EMF effect in the alpha band power density in the EO condition. This measurement protocol holds potential for future research on the impact of novel transmission protocols.

Posttraumatic growth EEG neuromarkers: translational neural comparisons with resilience and PTSD in trauma-exposed healthy adults.

Background: Supporting wellbeing beyond symptom reduction is necessary in trauma care. Research suggests increased posttraumatic growth (PTG) may promote wellbeing more effectively than posttraumatic stress disorder (PTSD) symptom reduction alone. Understanding neurobiological mechanisms of PTG would support PTG intervention development. However, most PTG research to-date has been cross-sectional data self-reported through surveys or interviews.Objective: Neural evidence of PTG and its coexistence with resilience and PTSD is limited. To advance neural PTG literature and contribute translational neuroscientific knowledge necessary to develop future objectively measurable neural-based PTG interventions.Method: Alpha frequency EEG and validated psychological inventories measuring PTG, resilience, and PTSD symptoms were collected from 30 trauma-exposed healthy adults amidst the COVID-19 pandemic. EEG data were collected using custom MNE-Python software, and a wireless OpenBCI 16-channel dry electrode EEG headset. Psychological inventory scores were analysed in SPSS Statistics and used to categorise the EEG data. Power spectral density analyses, t-tests and ANOVAs were conducted within EEGLab to identify brain activity differentiating high and low PTG, resilience, and PTSD symptoms.Results: Higher PTG was significantly differentiated from low PTG by higher alpha power in the left centro-temporal brain area around EEG electrode C3. A trend differentiating high PTG from PTSD was also indicated in this same location. Whole-scalp spectral topographies revealed alpha power EEG correlates of PTG, resilience and PTSD symptoms shared limited, but potentially meaningful similarities.Conclusion: This research provides the first comparative neural topographies of PTG, resilience and PTSD symptoms in the known literature. Results provide objective neural evidence supporting existing theory depicting PTG, resilience and PTSD as independent, yet co-occurring constructs. PTG neuromarker alpha C3 significantly delineated high from low PTG and warrants further investigation for potential clinical application. Findings provide foundation for future neural-based interventions and research for enhancing PTG in trauma-exposed individuals.

Objective translational study designed to increase neural understanding of posttraumatic growth (PTG) and provide a basis for future neural-based interventions to enhance PTG.Results provide neural evidence of PTG as an independent construct that coexists, and shares limited neural relatedness with resilience and PTSD symptoms.Increased PTG was significantly related to higher alpha power in the left centro-temporal brain area around EEG electrode C3: This finding warrants further investigation for potential clinical application.

A Quantum Model of Trust Calibration in Human-AI Interactions.

This exploratory study investigates a human agent's evolving judgements of reliability when interacting with an AI system. Two aims drove this investigation: (1) compare the predictive performance of quantum vs. Markov random walk models regarding human reliability judgements of an AI system and (2) identify a neural correlate of the perturbation of a human agent's judgement of the AI's reliability. As AI becomes more prevalent, it is important to understand how humans trust these technologies and how trust evolves when interacting with them. A mixed-methods experiment was developed for exploring reliability calibration in human-AI interactions. The behavioural data collected were used as a baseline to assess the predictive performance of the quantum and Markov models. We found the quantum model to better predict the evolving reliability ratings than the Markov model. This may be due to the quantum model being more amenable to represent the sometimes pronounced within-subject variability of reliability ratings. Additionally, a clear event-related potential response was found in the electroencephalographic (EEG) data, which is attributed to the expectations of reliability being perturbed. The identification of a trust-related EEG-based measure opens the door to explore how it could be used to adapt the parameters of the quantum model in real time.

Altered brain dynamic in major depressive disorder: state and trait features.

Temporal neural synchrony disruption can be linked to a variety of symptoms of major depressive disorder (MDD), including mood rigidity and the inability to break the cycle of negative emotion or attention biases. This might imply that altered dynamic neural synchrony may play a role in the persistence and exacerbation of MDD symptoms. Our study aimed to investigate the changes in whole-brain dynamic patterns of the brain functional connectivity and activity related to depression using the hidden Markov model (HMM) on resting-state functional magnetic resonance imaging (rs-fMRI) data. We compared the patterns of brain functional dynamics in a large sample of 314 patients with MDD (65.9% female; age (mean ± standard deviation): 35.9 ± 13.4) and 498 healthy controls (59.4% female; age: 34.0 ± 12.8). The HMM model was used to explain variations in rs-fMRI functional connectivity and averaged functional activity across the whole-brain by using a set of six unique recurring states. This study compared the proportion of time spent in each state and the average duration of visits to each state to assess stability between different groups. Compared to healthy controls, patients with MDD showed significantly higher proportional time spent and temporal stability in a state characterized by weak functional connectivity within and between all brain networks and relatively strong averaged functional activity of regions located in the somatosensory motor (SMN), salience (SN), and dorsal attention (DAN) networks. Both proportional time spent and temporal stability of this brain state was significantly associated with depression severity. Healthy controls, in contrast to the MDD group, showed proportional time spent and temporal stability in a state with relatively strong functional connectivity within and between all brain networks but weak averaged functional activity across the whole brain. These findings suggest that disrupted brain functional synchrony across time is present in MDD and associated with current depression severity.

Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes.

The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.

Trait anxiety is related to Nx4's efficacy on stress-induced changes in amygdala-centered resting state functional connectivity: a placebo-controlled cross-over trial in mildly to moderately stressed healthy volunteers.

BACKGROUND: The multicomponent drug Neurexan (Nx4) was shown to reduce the neural stress network activation. We now investigated its effects on stress-induced resting state functional connectivity (RSFC) in dependence of trait anxiety (TA), an acknowledged vulnerability factor for stress-induced psychopathologies. METHODS: Nx4 was tested in a randomized placebo-controlled crossover trial. Resting state fMRI scans were performed before and after a psychosocial stress task and exploratively analyzed for amygdala centered RSFC. Effects of Nx4 on stress-induced RSFC changes were evaluated and correlated to TA levels. A subgroup analysis based on TA scores was performed. RESULTS: Multiple linear regression analysis revealed a significant correlation between TA and Nx4 effect on stress-induced RSFC changes between right amygdala and pregenual anterior cingulate cortex (pgACC) and ventro-medial prefrontal cortex (vmPFC). For participants with above average TA, a significant amelioration of the stress-induced RSFC changes was observed. CONCLUSIONS: The data add evidence to the hypothesis that Nx4's clinical efficacy is based on a dampened activation of the neural stress network, with a greater neural response in subjects with anxious personality traits. Further studies assessing clinically relevant outcome measures in parallel to fMRI are encouraged to evaluate the real-world benefit of Nx4. Trial registration NCT02602275.

Enhanced Visual Cortex Activation in People With Narcolepsy Type 1 During Active Sleep Resistance: An fMRI-EEG Study.

The brain activation patterns related to sleep resistance remain to be discovered in health and disease. The maintenance of wakefulness test (MWT) is an objective neuropsychological assessment often used to assess an individual's ability to resist sleep. It is frequently used in narcolepsy type 1, a disorder characterized by impaired sleep-wake control and the inability to resist daytime sleep. We investigated the neural correlates of active sleep resistance in 12 drug-free people with narcolepsy type 1 and 12 healthy controls. Simultaneous fMRI-EEG measurements were recorded during five cycles of two alternating conditions of active sleep resistance and waking rest. Cleaned EEG signals were used to verify wakefulness and task adherence. Pooling both subject groups, significantly higher fMRI activation when actively resisting sleep was seen in the brainstem, superior cerebellum, bilateral thalamus and visual cortices. In controls the activation clusters were generally smaller compared to patients and no significant activation was seen in the brainstem. Formal comparison between groups only found a significantly higher left primary visual cortex activation in patients during active sleep resistance. The active sleep resistance paradigm is a feasible fMRI task to study sleep resistance and induces evident arousal- and visual-related activity. Significantly higher left primary visual cortical activation in patients could be caused by an enhanced need of visual focus to resist sleep, or reflecting a more rapid descent in their level of alertness when resting.

Nx4 Modulated Resting-State Functional Connectivity Between Amygdala and Prefrontal Cortex in a Placebo-Controlled, Crossover Trial.

Background: The basic functional organization of the resting brain, assessed as resting-state functional connectivity (rsFC), can be affected by previous stress experience and it represents the basis on which subsequent stress experience develops. Notably, the rsFC between the amygdala and the cortical regions associated with emotion regulation and anxiety are affected during stress. The multicomponent drug Neurexan® (Nx4) has previously demonstrated a reduction in amygdala activation in an emotional face matching task and it ameliorated stress-related symptoms. We, thus, investigated the effect of Nx4 on rsFC of the amygdala before stress induction compared with baseline in mildly to moderately stressed participants. Methods: In a randomized, placebo-controlled, double-blind, crossover trial 39 participants received a single dose of placebo or Nx4. Resting-state functional magnetic resonance imaging scans were performed pre-dose and 40 to 60 min post-dose, before any stress induction. First, highly connected functional hubs were identified by global functional connectivity density (gFCD) analysis. Second, by using a seed-based approach, rsFC maps of the left centromedial amygdala (CeMA) were created. The effect of Nx4 on both was evaluated. Results: The medial prefrontal cortex was identified as a relevant functional hub affected by Nx4 in an explorative whole brain gFCD analysis. Using the seed-based approach, we then demonstrated that Nx4 significantly enhanced the negative connectivity between the left CeMA and two cortical regions: the dorsolateral and medial prefrontal cortices. Conclusions: In a resting-state condition, Nx4 reduced the prefrontal cortex gFCD and strengthened the functional coupling between the amygdala and the prefrontal cortex that is relevant for emotion regulation and the stress response. Further studies should elaborate whether this mechanism represents enhanced regulatory control of the amygdala at rest and, consequently, to a diminished susceptibility to stress. ClinicalTrials.gov ID: NCT02602275.

Nx4 attenuated stress-induced activity of the anterior cingulate cortex-A post-hoc analysis of a randomized placebo-controlled crossover trial.

OBJECTIVE: Stress-related symptoms are associated with significant health and economic burden. Several studies suggest Nx4 for the pharmacological management of the stress response and investigated the underlying neural processes. Here we hypothesized that Nx4 can directly affect the stress response in a predefined stress network, including the anterior cingulate cortex (ACC), which is linked to various stress-related symptoms in patients. METHODS: In a randomized, placebo-controlled, double-blind, crossover trial, 39 healthy males took a single dose of placebo or Nx4. Psychosocial stress was induced by the ScanSTRESS paradigm inside an MRI scanner, and stress network activation was analyzed in brain regions defined a priori. RESULTS: Using the placebo data only, we could validate the activation of a distinct neural stress pattern by the ScanSTRESS paradigm. For Nx4, we provide evidence of an attenuating effect on this stress response. A statistically significant reduction in differential stress-induced activation in the right supracallosal ACC was observed for the rotation stress task of the ScanSTRESS paradigm. The results add to previously published results of Nx4 effects on emotion regulation. CONCLUSIONS: Our results strengthen the hypothesis that Nx4 modulates the stress response by reducing the activation in parts of the neural stress network, particularly in the ACC. TRIAL REGISTRATION: NCT02602275; ClinicalTrials.gov.

Corrigendum to "EEG revealed improved vigilance regulation after stress exposure under Nx4 - A randomized, placebo-controlled, double-blind, cross-over trial" [IBRO Neurosci. Rep. 11C (2021) 175-182].

[This corrects the article DOI: 10.1016/j.ibneur.2021.09.002.].

Nx4 Reduced Susceptibility to Distraction in an Attention Modulation Task.

Background: Stress adversely affects the attentional focus, the active concentration on stimuli, and increases susceptibility to distraction. To experimentally explore the susceptibility to distraction, the Attention Modulation by Salience Task (AMST) is a validated paradigm measuring reaction times (RT) for processing auditory information while presenting task-irrelevant visual distractors of high or low salience. We extended the AMST by an emotional dimension of distractors and an EEG-based evaluation. We then investigated the effect of the stress-relieving medication Neurexan (Nx4) on the participants' susceptibility to distraction. Methods: Data from a randomized, placebo-controlled, crossover trial (NEURIM study; ClinicalTrials.gov: NCT02602275) were exploratively reanalyzed post-hoc. In this trial, 39 participants received a single dose of placebo or Nx4 immediately before the AMST. Participants had to discriminate two different tone modulations (ascending or descending) while simultaneously perceiving task-irrelevant pictures of different salience (high or low) or valence (negative or positive) as distractors. Using EEG recordings, RT and the event-related potential (ERP) components N1, N2, and N3 were analyzed as markers for susceptibility to distraction. Results: In the placebo condition, we could replicate the previously reported task effects of salient distractors with longer RT for high salient distractors on the behavioral level. On the electrophysiological level, we observed significantly increased amplitudes of the N2 and N3 ERP components for positive emotional pictures. In terms of drug effect, we found evidence that Nx4 reduced distractibility by emotional distractors. The effect was shown by significantly reduced amplitudes of N2 and N3 ERP components and reduced RT for the positive valence domain under Nx4 compared to placebo. The Nx4 effects on RT and ERP components also showed a significant correlation. Conclusion: Emotional distractors in addition to the previously used salience distractors and the EEG based evaluation of ERPs valuably complement the AMST. Salient distractors were affecting attentional processes earlier, while valent distractors show modulatory effects later. Our results suggest that Nx4 has beneficial effects on attention by inhibiting the effect of task-irrelevant information and reducing susceptibility to emotionally distracting stimuli. The observation of a beneficial impact of Nx4 on attention regulation is supportive of Nx4's claim as a stress-relieving medication.

EEG revealed improved vigilance regulation after stress exposure under Nx4 - A randomized, placebo-controlled, double-blind, cross-over trial.

OBJECTIVES: Vigilance is characterized by alertness and sustained attention. The hyper-vigilance states are indicators of stress experience in the resting brain. Neurexan (Nx4) has been shown to modulate the neuroendocrine stress response. Here, we hypothesized that the intake of Nx4 would alter brain vigilance states at rest. METHOD: In this post-hoc analysis of the NEURIM study, EEG recordings of three, 12 min resting-state conditions in 39 healthy male volunteers were examined in a randomized, placebo-controlled, double-blind, cross-over clinical trial. EEG was recorded at three resting-state sessions: at baseline (RS0), after single-dose treatment with Nx4 or placebo (RS1), and subsequently after a psychosocial stress task (RS2). During each resting-state session, each 2-s segment of the consecutive EEG epochs was classified into one of seven different brain states along a wake-sleep continuum using the VIGALL 2.1 algorithm. RESULTS: In the post-stress resting-state, subjects exhibited a hyper-stable vigilance regulation characterized by an increase in the mean vigilance level and by more rigidity in the higher vigilance states for a longer period of time. Importantly, Nx4-treated participants exhibited significantly lower mean vigilance level compared to placebo-treated ones. Also, Nx4- compared to placebo-treated participants spent comparably less time in higher vigilance states and more time in lower vigilance states in the post-stress resting-state. CONCLUSION: Study participants showed a significantly lower mean vigilance level in the post-stress resting-state condition and tended to stay longer in lower vigilance states after treatment with Nx4. These findings support the known stress attenuation effect of Nx4.

Evidence for modulation of EEG microstate sequence by vigilance level.

The momentary global functional state of the brain is reflected in its electric field configuration and cluster analytical approaches have consistently shown four configurations, referred to as EEG microstate classes A to D. Changes in microstate parameters are associated with a number of neuropsychiatric disorders, task performance, and mental state establishing their relevance for cognition. However, the common practice to use eye-closed resting state data to assess the temporal dynamics of microstate parameters might induce systematic confounds related to vigilance levels. Here, we studied the dynamics of microstate parameters in two independent data sets and showed that the parameters of microstates are strongly associated with vigilance level assessed both by EEG power analysis and fMRI global signal. We found that the duration and contribution of microstate class C, as well as transition probabilities towards microstate class C were positively associated with vigilance, whereas the sign was reversed for microstate classes A and B. Furthermore, in looking for the origins of the correspondence between microstates and vigilance level, we found Granger-causal effects of vigilance levels on microstate sequence parameters. Collectively, our findings suggest that duration and occurrence of microstates have a different origin and possibly reflect different physiological processes. Finally, our findings indicate the need for taking vigilance levels into consideration in resting-sate EEG investigations.

Intracranial-EEG evidence for medial temporal pole driving amygdala activity induced by multi-modal emotional stimuli.

The temporal pole (TP) is an associative cortical region required for complex cognitive functions such as social and emotional cognition. However, mapping the TP with functional magnetic resonance imaging is technically challenging and thus understanding its interaction with other key emotional circuitry, such as the amygdala, remains elusive. We exploited the unique advantages of stereo-electroencephalography (sEEG) to assess the responses of the TP and the amygdala during the perception of emotionally salient stimuli of pictures, music and movies. These stimuli consistently elicited high gamma responses (70-140 Hz) in both the TP and the amygdala, accompanied by functional connectivity in the low frequency range (2-12 Hz). Computational analyses suggested that the TP drove this effect in the theta frequency range, modulated by the emotional valence of the stimuli. Notably, cross-frequency analysis indicated the phase of theta oscillations in the TP modulated the amplitude of high gamma activity in the amygdala. These results were reproducible across three types of sensory inputs including naturalistic stimuli. Our results suggest that multimodal emotional stimuli induce a hierarchical influence of the TP over the amygdala.

Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks.

Electroencephalogram (EEG) microstates that represent quasi-stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dynamics that underlie various mental processes. Recent studies suggest that EEG microstate sequences are non-Markovian and nonstationary, highlighting the importance of the sequential flow of information between different brain states. These findings inspired us to model these sequences using Recurrent Neural Networks (RNNs) consisting of long-short-term-memory (LSTM) units to capture the complex temporal dependencies. Using an LSTM-based auto encoder framework and different encoding schemes, we modeled the microstate sequences at multiple time scales (200-2,000 ms) aiming to capture stably recurring microstate patterns within and across subjects. We show that RNNs can learn underlying microstate patterns with high accuracy and that the microstate trajectories are subject invariant at shorter time scales (≤400 ms) and reproducible across sessions. Significant drop in the reconstruction accuracy was observed for longer sequence lengths of 2,000 ms. These findings indirectly corroborate earlier studies which indicated that EEG microstate sequences exhibit long-range dependencies with finite memory content. Furthermore, we find that the latent representations learned by the RNNs are sensitive to external stimulation such as stress while the conventional univariate microstate measures (e.g., occurrence, mean duration, etc.) fail to capture such changes in brain dynamics. While RNNs cannot be configured to identify the specific discriminating patterns, they have the potential for learning the underlying temporal dynamics and are sensitive to sequence aberrations characterized by changes in metal processes. Empowered with the macroscopic understanding of the temporal dynamics that extends beyond short-term interactions, RNNs offer a reliable alternative for exploring system level brain dynamics using EEG microstate sequences.

The anterior insula channels prefrontal expectancy signals during affective processing.

Expectancy shapes our perception of impending events. Although such an interplay between cognitive and affective processes is often impaired in mental disorders, it is not well understood how top-down expectancy signals modulate future affect. We therefore track the information flow in the brain during cognitive and affective processing segregated in time using task-specific cross-correlations. Participants in two independent fMRI studies (N1 = 37 & N2 = 55) were instructed to imagine a situation with affective content as indicated by a cue, which was then followed by an emotional picture congruent with expectancy. To correct for intrinsic covariance of brain function, we calculate resting-state cross-correlations analogous to the task. First, using factorial modeling of delta cross-correlations (task-rest) of the first study, we find that the magnitude of expectancy signals in the anterior insula cortex (AIC) modulates the BOLD response to emotional pictures in the anterior cingulate and dorsomedial prefrontal cortex in opposite directions. Second, using hierarchical linear modeling of lagged connectivity, we demonstrate that expectancy signals in the AIC indeed foreshadow this opposing pattern in the prefrontal cortex. Third, we replicate the results in the second study using a higher temporal resolution, showing that our task-specific cross-correlation approach robustly uncovers the dynamics of information flow. We conclude that the AIC arbitrates the recruitment of distinct prefrontal networks during cued picture processing according to triggered expectations. Taken together, our study provides new insights into neuronal pathways channeling cognition and affect within well-defined brain networks. Better understanding of such dynamics could lead to new applications tracking aberrant information processing in mental disorders.

Neuroscience: Modeling the Brain on Acid.

A receptor map of serotonin distribution is integrated into a model of the dynamic activity of the brain under the effects of LSD. The approach opens new avenues to understand experimental manipulations of healthy brain activity and offers a novel drug-discovery platform.

Distinctive tics suppression network in Gilles de la Tourette syndrome distinguished from suppression of natural urges using multimodal imaging.

BACKGROUND AND OBJECTIVES: Gilles de la Tourette syndrome (GTS) is a neuropsychiatric disorder characterized by tics. A hallmark of GTS is the ability to voluntarily suppress tics. Our aim was to distinguish the neural circuits involved in the voluntary suppression of ocular tics in GTS patients from blink suppression in healthy subjects. METHODS: Fifteen GTS patients and 22 healthy control subjects were included in a multimodal study using eye-tracker recordings during functional MRI (fMRI). The ability to suppress tics/blinks was compared both on subjective (self-rating) and objective (eye-tracker) performance. For fMRI analysis we used a novel designed performance-adapted block design analysis of tic/blink suppression and release based on eye-tracker monitoring. RESULTS: We found that the subjective self-reported ability to suppress tics or blinks showed no significant correlation with objective task performance. In GTS during successful suppression of tics, the dorsal anterior cingulate cortex and associated limbic areas showed increased activation. During successful suppression of eye blinks in healthy subjects, the right ventrolateral prefrontal cortex and supplementary and cingulate motor areas showed increased activation. CONCLUSIONS: These findings demonstrate that GTS patients use a characteristic limbic suppression strategy. In contrast, control subjects use the voluntary sensorimotor circuits and the classical 'stop' network to suppress natural urges. The employment of different neural suppression networks provides support for cognitive behavioral therapy in GTS.