A high-density EEG investigation into the neurocognitive mechanisms underlying differences between personality profiles in social information processing.

This study investigated whether differences between personality styles in the processing of social stimuli reflect variability in underlying general-purpose or social-specific neurocognitive mechanisms. Sixty-five individuals classified previously into two distinct personality profiles underwent high-density electroencephalography whilst performing tasks that tap into both aspects of cognitive processing - namely, two distinct facets of general-purpose response inhibition (interference resolution and action withholding) during social information processing. To determine the stage of processing at which personality differences manifest, we assessed event-related components associated with the early visual discrimination of social stimuli (N170, N190) and later more general conflict-related processes (N2, P3). Although a performance index of interference resolution was comparable between the personality profiles, differences were detected in action withholding. Specifically, individuals expressing a wider repertoire of personality styles and more adaptive emotion regulation performed significantly better at withholding inappropriate actions to neutral faces presented in emotional contexts compared with those exhibiting stronger preferences for fewer and less adaptive personality styles and more ruminative affective tendencies. At the neurophysiological level, however, difference between the profiles was observed in brain responses elicited to the same stimuli within the N170. These results indicate that neural processes related to early visual discrimination might contribute to differences in the suppression of inappropriate responses towards social stimuli in populations with different personality dispositions.

Cortical network organization reflects clinical response to subthalamic nucleus deep brain stimulation in Parkinson's disease.

The degree of response to subthalamic nucleus deep brain stimulation (STN-DBS) is individual and hardly predictable. We hypothesized that DBS-related changes in cortical network organization are related to the clinical effect. Network analysis based on graph theory was used to evaluate the high-density electroencephalography (HDEEG) recorded during a visual three-stimuli paradigm in 32 Parkinson's disease (PD) patients treated by STN-DBS in stimulation "off" and "on" states. Preprocessed scalp data were reconstructed into the source space and correlated to the behavioral parameters. In the majority of patients (n = 26), STN-DBS did not lead to changes in global network organization in large-scale brain networks. In a subgroup of suboptimal responders (n = 6), identified according to reaction times (RT) and clinical parameters (lower Unified Parkinson's Disease Rating Scale [UPDRS] score improvement after DBS and worse performance in memory tests), decreased global connectivity in the 1-8 Hz frequency range and regional node strength in frontal areas were detected. The important role of the supplementary motor area for the optimal DBS response was demonstrated by the increased node strength and eigenvector centrality in good responders. This response was missing in the suboptimal responders. Cortical topologic architecture is modified by the response to STN-DBS leading to a dysfunction of the large-scale networks in suboptimal responders.

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging.

Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand-alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR-negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel-wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion-weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR-negative epilepsy patients.

Imitation or Polarity Correspondence? Behavioural and Neurophysiological Evidence for the Confounding Influence of Orthogonal Spatial Compatibility on Measures of Automatic Imitation.

During social interactions, humans tend to imitate one another involuntarily. To investigate the neurocognitive mechanisms driving this tendency, researchers often employ stimulus-response compatibility (SRC) tasks to assess the influence that action observation has on action execution. This is referred to as automatic imitation (AI). The stimuli used frequently in SRC procedures to elicit AI often confound action-related with other nonsocial influences on behaviour; however, in response to the rotated hand-action stimuli employed increasingly, AI partly reflects unspecific up-right/down-left biases in stimulus-response mapping. Despite an emerging awareness of this confounding orthogonal spatial-compatibility effect, psychological and neuroscientific research into social behaviour continues to employ these stimuli to investigate AI. To increase recognition of this methodological issue, the present study measured the systematic influence of orthogonal spatial effects on behavioural and neurophysiological measures of AI acquired with rotated hand-action stimuli in SRC tasks. In Experiment 1, behavioural data from a large sample revealed that complex orthogonal spatial effects exert an influence on AI over and above any topographical similarity between observed and executed actions. Experiment 2 reproduced this finding in a more systematic, within-subject design, and high-density electroencephalography revealed that electrocortical expressions of AI elicited also are modulated by orthogonal spatial compatibility. Finally, source localisations identified a collection of cortical areas sensitive to this spatial confound, including nodes of the multiple-demand and semantic-control networks. These results indicate that AI measured on SRC procedures with the rotated hand stimuli used commonly might reflect neurocognitive mechanisms associated with spatial associations rather than imitative tendencies.

Altered Spatiotemporal Dynamics of the Resting Brain in Mild Cognitive Impairment with Lewy Bodies.

BACKGROUND: Electrophysiological markers of prodromal dementia with Lewy bodies were described in the spectral domain. The sub-second temporal resolution may provide additional information. OBJECTIVE: To evaluate electroencephalography (EEG) microstates in patients with mild cognitive impairment with Lewy bodies and to assess the association between their temporal dynamics and the spectral marker. METHODS: Temporal parameters of microstates were compared between 21 patients with mild cognitive impairment with Lewy bodies and 21 healthy controls. The dominant alpha frequency was correlated with microstate parameters. RESULTS: Microstates A-D showed higher occurrence in the patient group. Microstate B additionally revealed shorter mean duration and increased time coverage; its occurrence correlated with the dominant alpha frequency in the patient group. CONCLUSIONS: Temporal dynamics of all EEG microstates were altered in medication-naïve subjects with prodromal dementia with Lewy bodies. Longitudinal follow-up may reveal how EEG microstates reflect progression of brain function deficits and effects of treatment manipulations. © 2021 International Parkinson and Movement Disorder Society.

Thalamic oscillatory activity may predict response to deep brain stimulation of the anterior nuclei of the thalamus.

We hypothesized that local/regional properties of stimulated structure/circuitry contribute to the effect of deep brain stimulation (DBS). We analyzed intracerebral electroencephalographic (EEG) recordings from externalized DBS electrodes targeted bilaterally in the anterior nuclei of the thalamus (ANT) in 12 patients (six responders, six nonresponders) with more than 1 year of follow-up care. In the bipolar local field potentials of the EEG, spectral power (PW) and power spectral entropy (PSE) were calculated in the passbands 1-4, 4-8, 8-12, 12-20, 20-45, 65-80, 80-200 and 200-500 Hz. The most significant differences between responders and nonresponders were observed in the BRIDGE area (bipolar recordings with one contact within the ANT and the second contact in adjacent tissue). In responders, PW was significantly decreased in the frequency bands of 65-80, 80-200, and 200-500 Hz (p < .05); PSE was significantly increased in all frequency bands (p < .05) except for 200-500 Hz (p = .06). The local EEG characteristics of ANT recorded after implantation may play a significant role in DBS response prediction.

Resting-State Phase-Amplitude Coupling Between the Human Subthalamic Nucleus and Cortical Activity: A Simultaneous Intracranial and Scalp EEG Study.

It has been suggested that slow oscillations in the subthalamic nucleus (STN) reflect top-down inputs from the medial prefrontal cortex, thus implementing behavior control. It is unclear, however, whether the STN oscillations are related to cortical activity in a bottom-up manner. To assess resting-state subcortico-cortical interactions, we recorded simultaneous scalp electroencephalographic activity and local field potentials in the STN (LFP-STN) in 11 patients with Parkinson's disease implanted with deep brain stimulation electrodes in the on-medication state during rest. We assessed the cross-structural phase-amplitude coupling (PAC) between the STN and cortical activity within a wide frequency range of 1 to 100 Hz. The PAC was dominant between the δ/θ STN phase and ß/γ cortical amplitude in most investigated scalp regions and between the δ cortical phase and θ/α STN amplitude in the frontal and temporal regions. The cross-frequency linkage between the slow oscillations of the LFP-STN activity and the amplitude of the scalp-recorded cortical activity at rest was demonstrated, and similar involvement of the left and right STNs in the coupling was observed. Our results suggest that the STN plays a role in both bottom-up and top-down processes within the subcortico-cortical circuitries of the human brain during the resting state. A relative left-right symmetry in the STN-cortex functional linkage was suggested. Practical treatment studies would be necessary to assess whether unilateral stimulation of the STN might be sufficient for treatment of Parkinson's disease.

Memory retrieval in temporal lobe epilepsy is related to functional segregation of the mesiotemporal structures.

OBJECTIVE: We analyzed the impact of temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) on functional connectivity (FC) between mesiotemporal structures. Functional connectivity modifications related to word retrieval were investigated. METHODS: High-density EEG of 21 patients with TLE with HS (12 left TLE and 9 right TLE) and 10 healthy controls (HCs) were recorded during a verbal subsequent memory paradigm. Electroencephalography data were reconstructed into the source space and FC was calculated from the source activity of regions of interest. RESULTS: A significant decrease in FC between the right- and left-sided mesiotemporal structures in TLE was observed. The decrease was significant only with words that were correctly recognized. The decrease in interhemispheric FC between mesiotemporal structures was found in the 8- to 20-Hz frequency range in both left and right TLE. SIGNIFICANCE: The decreased FC between the mesiotemporal structures in TLE is a condition for successful performance of a memory retrieval task. The successful memory retrieval in TLE is related to functional segregation of lesional from nonlesional mesiotemporal structures. This decrease was absent in non-successful responses.

Inferior parietal lobule involved in representation of "what" in a delayed-action Libet task.

Intentional motor action is typically characterized by the decision about the timing, and the selection of the action variant, known as the "what" component. We compared free action selection with instructed action, where the movement type was externally cued, in order to investigate the action selection and action representation in a Libet's task. Temporal and spatial locus of these processes was examined using the combination of high-density electroencephalography, topographic analysis of variance, and source reconstruction. Instructed action, engaging representation of the response movement, was associated with distinct negativity at the parietal and centro-parietal channels starting around 750 ms before the movement, which has a source particularly in the bilateral inferior parietal lobule. This suggests that in delayed-action tasks, the process of action representation in the inferior parietal lobule may play an important part in the larger parieto-frontal activity responsible for movement selection.

Suboptimal response to STN-DBS in Parkinson's disease can be identified via reaction times in a motor cognitive paradigm.

Although deep brain stimulation of the subthalamic nucleus (STN-DBS) in Parkinson's disease (PD) is generally a successful therapy, adverse events and insufficient clinical effect can complicate the treatment in some patients. We studied clinical parameters and cortical oscillations related to STN-DBS to identify patients with suboptimal responses. High-density EEG was recorded during a visual oddball three-stimuli paradigm in DBS "off" and "on" conditions in 32 PD patients with STN-DBS. Pre-processed data were reconstructed into the source space and the time-frequency analysis was evaluated. We identified a subgroup of six patients with longer reaction times (RT) during the DBS "on" state than in the DBS "off" state after target stimuli. These subjects had lower motor responsiveness to DBS and decreased memory test results compared to the other subjects. Moreover, the alpha and beta power decrease (event-related desynchronizations, ERD), known as an activation correlate linked to motor and cognitive processing, was also reduced in the DBS "on" condition in these patients. A subgroup of PD patients with a suboptimal response to STN-DBS was identified. Evaluation of RT could potentially serve as a biomarker for responsiveness to STN-DBS.

Cognitive task-related functional connectivity alterations in temporal lobe epilepsy.

OBJECTIVE: We investigated cognitive task-related functional connectivity (FC) in patients with temporal lobe epilepsy (TLE). Using a visual three-stimulus paradigm (VTSP), we studied cognitive large-scale networks and the impact of TLE on connectivity outside the temporal lobe. METHODS: High-density electroencephalography (EEG) was recorded during the paradigm from nineteen patients with epilepsy with hippocampal sclerosis (HS) and ten healthy controls (HCs). Scalp data were reconstructed into the source space, and FC was computed. Correlating with the neuropsychological data, possible compensatory mechanisms were investigated. RESULTS: Significant changes were found in the FC of regions outside the epileptogenic network, particularly in the attentional network. These changes were more widespread in left TLE (LTLE). There were no significant differences in task performance (accuracy, time response) in comparison with HCs, implying that there must be some mechanism reducing the impact of connectivity changes on brain functions. When correlated with neuropsychological data, we found stronger compensatory mechanisms in right TLE (RTLE). SIGNIFICANCE: Our findings confirm the hypothesis that LTLE is the more pervasive form of the disease. Even though the network alterations in TLE are severe, some mechanisms reduce the impact of epilepsy on cognitive functions; these mechanisms are more potent in RTLE. We also suggest that there are maladaptive mechanisms in LTLE.

Imagery-induced negative affect, social touch and frontal EEG power band activity.

Social touch seems to modulate emotions, but its brain correlates are poorly understood. Here, we investigated if frontal power band activity in the electroencephalogram (EEG) during aversive mental imagery is modulated by social touch from one's romantic partner and a stranger. We observed the highest theta and beta power when imaging alone, next so when being touched by a stranger, with lowest theta and beta activity during holding hands with the loved one. Delta power was higher when being alone than with a stranger or a partner, with no difference between the two. Gamma power was highest during the stranger condition and lower both when being alone and with the partner, while alpha power did not change as a function of social touch. Theta power displayed a positive correlation with electrodermal activity supporting its relation to emotional arousal. Attachment style modulated the effect of touch on the EEG as only secure but not insecure partner bonding was associated with theta power reductions. Because theta power was sensitive to the experimental perturbations, mapped onto peripheral physiological arousal and reflected partner attachment style we suggest that frontal theta power might serve as an EEG derived bio-marker for social touch in emotionally significant dyads.

Robustness of Representative Signals Relative to Data Loss Using Atlas-Based Parcellations.

Parcellation-based approaches are an important part of functional magnetic resonance imaging data analysis. They are a necessary processing step for sorting data in structurally or functionally homogenous regions. Real functional magnetic resonance imaging datasets usually do not cover the atlas template completely; they are often spatially constrained due to the physical limitations of MR sequence settings, the inter-individual variability in brain shape, etc. When using a parcellation template, many regions are not completely covered by actual data. This paper addresses the issue of the area coverage required in real data in order to reliably estimate the representative signal and the influence of this kind of data loss on network analysis metrics. We demonstrate this issue on four datasets using four different widely used parcellation templates. We used two erosion approaches to simulate data loss on the whole-brain level and the ROI-specific level. Our results show that changes in ROI coverage have a systematic influence on network measures. Based on the results of our analysis, we recommend controlling the ROI coverage and retaining at least 60% of the area in order to ensure at least 80% of explained variance of the original signal.

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks.

Multiway array decomposition methods have been shown to be promising statistical tools for identifying neural activity in the EEG spectrum. They blindly decompose the EEG spectrum into spatial-temporal-spectral patterns by taking into account inherent relationships among signals acquired at different frequencies and sensors. Our study evaluates the stability of spatial-temporal-spectral patterns derived by one particular method, parallel factor analysis (PARAFAC). We focused on patterns' stability over time and in population and divided the complete data set containing data from 50 healthy subjects into several subsets. Our results suggest that the patterns are highly stable in time, as well as among different subgroups of subjects. Further, we show with simultaneously acquired fMRI data that power fluctuations of some patterns have stable correspondence to hemodynamic fluctuations in large-scale brain networks. We did not find such correspondence for power fluctuations in standard frequency bands, the common way of dealing with EEG data. Altogether, our results suggest that PARAFAC is a suitable method for research in the field of large-scale brain networks and their manifestation in EEG signal.

Facial emotion processing in patients with borderline personality disorder as compared with healthy controls: an fMRI and ECG study.

BACKGROUND: Maladaptive behaviors and interpersonal difficulties in patients with borderline personality disorder (BPD) seem connected to biased facial emotion processing. This bias is often accompanied by heightened amygdala activity in patients with BPD as compared to healthy controls. However, functional magnetic resonance imaging (fMRI) studies exploring differences between patients and healthy controls in facial emotion processing have produced divergent results. The current study explored fMRI and heart rate variability (HRV) correlates of negative facial emotion processing in patients with BPD and healthy controls. METHODS: The study included 30 patients with BPD (29 females; age: M = 24.22, SD = 5.22) and 30 healthy controls (29 females; M = 24.66, SD = 5.28). All participants underwent the "faces" task, an emotional face perception task, in an fMRI session simultaneously with ECG. In this task, participants are presented with emotional expressions of disgust, sadness, and fear (as a negative condition) and with the same pictures in a scrambled version (as a neutral condition). RESULTS: We found no differences in brain activity between patients with BPD and healthy controls when processing negative facial expressions as compared to neutral condition. We observed activation in large-scale brain areas in both groups when presented with negative facial expressions as compared to neutral condition. Patients with BPD displayed lower HRV than healthy controls in both conditions. However, there were no significant associations between HRV and amygdala activity and BPD symptoms. CONCLUSION: The results of this study indicate no abnormal brain activity during emotional facial processing in patients with BPD. This result contrasts with previous studies and more studies are needed to clarify the relationship between facial emotion processing and brain activity in patients with BPD. Possible reasons for the absence of brain activity differences are discussed in the study. Consistent with previous findings, patients showed lower HRV than healthy controls. However, HRV was not associated with amygdala activity and BPD symptoms.

Coupling between beta band and high frequency oscillations as a clinically useful biomarker for DBS.

Beta hypersynchrony was recently introduced into clinical practice in Parkinson's disease (PD) to identify the best stimulation contacts and for adaptive deep brain stimulation (aDBS) sensing. However, many other oscillopathies accompany the disease, and beta power sensing may not be optimal for all patients. The aim of this work was to study the potential clinical usefulness of beta power phase-amplitude coupling (PAC) with high frequency oscillations (HFOs). Subthalamic nucleus (STN) local field potentials (LFPs) from externalized DBS electrodes were recorded and analyzed in PD patients (n = 19). Beta power and HFOs were evaluated in a resting-state condition; PAC was then studied and compared with the electrode contact positions, structural connectivity, and medication state. Beta-HFO PAC (mainly in the 200-500 Hz range) was observed in all subjects. PAC was detectable more specifically in the motor part of the STN compared to beta power and HFOs. Moreover, the presence of PAC better corresponds to the stimulation setup based on the clinical effect. PAC is also sensitive to the laterality of symptoms and dopaminergic therapy, where the greater PAC cluster reflects the more affected side and medication "off" state. Coupling between beta power and HFOs is known to be a correlate of the PD "off" state. Beta-HFO PAC seems to be more sensitive than beta power itself and could be more helpful in the selection of the best clinical stimulation contact and probably also as a potential future input signal for aDBS.

The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates.

Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.

Neural correlates of social exclusion and overinclusion in patients with borderline personality disorder: an fMRI study.

BACKGROUND: Interpersonal difficulties of patients with borderline personality disorder (BPD) are closely related to rejection sensitivity. The aim of the present study was to gain further insight into the experience and cerebral processing of social interactions in patients with BPD by using fMRI during experimentally induced experiences of social exclusion, inclusion, and overinclusion. METHODS: The study involved 30 participants diagnosed with BPD (29 female and 1 male; age: M = 24.22, SD = 5.22) and 30 healthy controls (29 female and 1 male; age: M = 24.66, SD = 5.28) with no current or lifetime psychiatric diagnoses. In the fMRI session, all participants were asked to complete a Cyberball task that consisted of an alternating sequence of inclusion, exclusion, and overinclusion conditions. RESULTS: Compared to healthy controls, participants with BPD reported higher levels of inner tension and more unpleasant emotions across all experimental conditions. At the neural level, the participants with BPD showed lower recruitment of the left hippocampus in response to social exclusion (relative to the inclusion condition) than the healthy controls did. Lower recruitment of the left hippocampus in this contrast was associated with childhood maltreatment in patients with BPD. However, this difference was no longer significant when we added the covariate of hippocampal volume to the analysis. During social overinclusion (relative to the inclusion condition), we observed no significant differences in a group comparison of neural activation. CONCLUSIONS: The results of our study suggest that patients with BPD experience more discomfort than do healthy controls during social interactions. Compared to healthy participants, patients with BPD reported more inner tension and unpleasant emotions, irrespective of the extent to which others included them in social interactions. At a neural level, the participants with BPD showed a lower recruitment of the left hippocampus in response to social exclusion than the healthy controls did. The reduced activation of this neural structure could be related to a history of childhood maltreatment and smaller hippocampal volume in patients with BPD.

Inter-individual differences in baseline dynamic functional connectivity are linked to cognitive aftereffects of tDCS.

Transcranial direct current stimulation (tDCS) has the potential to modulate cognitive training in healthy aging; however, results from various studies have been inconsistent. We hypothesized that inter-individual differences in baseline brain state may contribute to the varied results. We aimed to explore whether baseline resting-state dynamic functional connectivity (rs-dFC) and/or conventional resting-state static functional connectivity (rs-sFC) may be related to the magnitude of cognitive aftereffects of tDCS. To achieve this aim, we used data from our double-blind randomized sham-controlled cross-over tDCS trial in 25 healthy seniors in which bifrontal tDCS combined with cognitive training had induced significant behavioral aftereffects. We performed a backward regression analysis including rs-sFC/rs-dFC measures to explain the variability in the magnitude of tDCS-induced improvements in visual object-matching task (VOMT) accuracy. Rs-dFC analysis revealed four rs-dFC states. The occurrence rate of a rs-dFC state 4, characterized by a high correlation between the left fronto-parietal control network and the language network, was significantly associated with tDCS-induced VOMT accuracy changes. The rs-sFC measure was not significantly associated with the cognitive outcome. We show that flexibility of the brain state representing readiness for top-down control of object identification implicated in the studied task is linked to the tDCS-enhanced task accuracy.