Spontaneous thought and microstate activity modulation by social imitation.

The human mind wanders spontaneously and frequently, revisiting the past and imagining the future of self and of others. External and internal factors can influence wandering spontaneous thoughts, whose content predicts subsequent emotional states. We propose that social imitation, an action that increases well-being and closeness by poorly understood mechanisms, impacts behavioural states in part by modulating post-imitation mind-wandering. In 43 young subjects, we find that imitating the arm movements of an actor alters the dynamics and the content of subsequent resting-state spontaneous thoughts. Imitation-sensitive features of spontaneous thoughts correlate with behavioural states and personality traits. EEG microstate analysis reveals that global patterns of correlated neuronal activity predict imitation-induced changes in spontaneous thoughts. Exploratory analyses indicate a possible modulatory effect of social imitation via the endogenous release of oxytocin. Thus, social imitation can induce selective modulations of ongoing activity in specific neural networks to change spontaneous thought patterns as a function of personality traits, and to ultimately orchestrate behavioural states.

Imaging the effective networks associated with cortical function through intracranial high-frequency stimulation.

Direct electrical stimulation (DES) is considered to be the gold standard for mapping cortical function. A careful mapping of the eloquent cortex is key to successful resective or ablative surgeries, with a minimal postoperative deficit, for treatment of drug-resistant epilepsy. There is accumulating evidence suggesting that not only local, but also remote activations play an equally important role in evoking clinical effects. By introducing a new intracranial stimulation paradigm and signal analysis methodology allowing to disambiguate EEG responses from stimulation artifacts we highlight the spatial extent of the networks associated with clinical effects. Our study includes 26 patients that underwent stereoelectroencephalographic investigations for drug-resistant epilepsy, having 337 depth electrodes with 4,351 contacts sampling most brain structures. The routine high-frequency electrical stimulation protocol for eloquent cortex mapping was altered in a subtle way, by alternating the polarity of the biphasic pulses in a train, causing the splitting the spectral lines of the artifactual components, exposing the underlying tissue response. By performing a frequency-domain analysis of the EEG responses during DES we were able to capture remote activations and highlight the effect's network. By using standard intersubject averaging and a fine granularity HCP-MMP parcellation, we were able to create local and distant connectivity maps for 614 stimulations evoking specific clinical effects. The clinical value of such maps is not only for a better understanding of the extent of the effects' networks guiding the invasive exploration, but also for understanding the spatial patterns of seizure propagation given the timeline of the seizure semiology.

Accuracy and Safety of Customized Stereotactic Fixtures for Stereoelectroencephalography in Pediatric Patients.

Stereoelectroencephalography (SEEG) in children with intractable epilepsy presents particular challenges. Their thin and partially ossified cranium, specifically in the temporal area, is prone to fracture while attaching stereotactic systems to the head or stabilizing the head in robot's field of action. Postponing SEEG in this special population of patients can have serious consequences, reducing their chances of becoming seizure-free and impacting their social and cognitive development. This study demonstrates the safety and accuracy offered by a frameless personalized 3D printed stereotactic implantation system for SEEG investigations in children under 4 years of age. SEEG was carried out in a 3-year-old patient with drug-resistant focal epilepsy, based on a right temporal-perisylvian epileptogenic zone hypothesis. Fifteen intracerebral electrodes were placed using a StarFix patient-customized stereotactic fixture. The median lateral entry point localization error of the electrodes was 0.90 mm, median lateral target point localization error was 1.86 mm, median target depth error was 0.83 mm, and median target point localization error was 1.96 mm. There were no perioperative complications. SEEG data led to a tailored right temporal-insular-opercular resection, with resulting seizure freedom (Engel IA). In conclusion, patient-customized stereotactic fixtures are a safe and accurate option for SEEG exploration in young children.

Cingulate cortex function and multi-modal connectivity mapped using intracranial stimulation.

The cingulate cortex is part of the limbic system. Its function and connectivity are organized in a rostro-caudal and ventral-dorsal manner which was addressed by various other studies using rather coarse cortical parcellations. In this study, we aim at describing its function and connectivity using invasive recordings from patients explored for focal drug-resistant epilepsy. We included patients that underwent stereo-electroencephalographic recordings using intracranial electrodes in the University Emergency Hospital Bucharest between 2012 and 2019. We reviewed all high frequency stimulations (50 â€‹Hz) performed for functional mapping of the cingulate cortex. We used two methods to characterize brain connectivity. Effective connectivity was inferred based on the analysis of cortico-cortical potentials (CCEPs) evoked by single pulse electrical stimulation (SPES) (15 â€‹s inter-pulse interval). Functional connectivity was estimated using the non-linear regression method applied to 60 â€‹s spontaneous electrical brain signal intervals. The effective (stimulation-evoked) and functional (non-evoked) connectivity analyses highlight brain networks in a different way. While non-evoked connectivity evidences areas having related activity, often in close proximity to each other, evoked connectivity highlights spatially extended networks. To highlight in a comprehensive way the cingulate cortex's network, we have performed a bi-modal connectivity analysis that combines the resting-state broadband h2 non-linear correlation with cortico-cortical evoked potentials. We co-registered the patient's anatomy with the fsaverage FreeSurfer template to perform the automatic labeling based on HCP-MMP parcellation. At a group level, connectivity was estimated by averaging responses over stimulated/recorded or recorded sites in each pair of parcels. Finally, for multiple regions that evoked a clinical response during high frequency stimulation, we combined the connectivity of individual pairs using maximum intensity projection. Connectivity was assessed by applying SPES on 2094 contact pairs and recording CCEPs on 3580 contacts out of 8582 contacts of 660 electrodes implanted in 47 patients. Clinical responses elicited by high frequency stimulations in 107 sites (pairs of contacts) located in the cingulate cortex were divided in 10 groups: affective, motor behavior, motor elementary, versive, speech, vestibular, autonomic, somatosensory, visual and changes in body perception. Anterior cingulate cortex was shown to be connected to the mesial temporal, orbitofrontal and prefrontal cortex. In the middle cingulate cortex, we located affective, motor behavior in the anterior region, and elementary motor and somatosensory in the posterior part. This region is connected to the prefrontal, premotor and primary motor network. Finally, the posterior cingulate was shown to be connected with the visual areas, mesial and lateral parietal and temporal cortex.

Studying memory processes at different levels with simultaneous depth and surface EEG recordings.

Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.

A comparison of uni- and multi-variate methods for identifying brain networks activated by cognitive tasks using intracranial EEG.

Cognitive tasks are commonly used to identify brain networks involved in the underlying cognitive process. However, inferring the brain networks from intracranial EEG data presents several challenges related to the sparse spatial sampling of the brain and the high variability of the EEG trace due to concurrent brain processes. In this manuscript, we use a well-known facial emotion recognition task to compare three different ways of analyzing the contrasts between task conditions: permutation cluster tests, machine learning (ML) classifiers, and a searchlight implementation of multivariate pattern analysis (MVPA) for intracranial sparse data recorded from 13 patients undergoing presurgical evaluation for drug-resistant epilepsy. Using all three methods, we aim at highlighting the brain structures with significant contrast between conditions. In the absence of ground truth, we use the scientific literature to validate our results. The comparison of the three methods' results shows moderate agreement, measured by the Jaccard coefficient, between the permutation cluster tests and the machine learning [0.33 and 0.52 for the left (LH) and right (RH) hemispheres], and 0.44 and 0.37 for the LH and RH between the permutation cluster tests and MVPA. The agreement between ML and MVPA is higher: 0.65 for the LH and 0.62 for the RH. To put these results in context, we performed a brief review of the literature and we discuss how each brain structure's involvement in the facial emotion recognition task.

Motor and emotional facial features in parietal lobe seizures: an ictal functional connectivity study using SEEG

Objectives: Parietal lobe epilepsy is one of the rarest types and patients with this form of epilepsy report multiple subjective symptoms during ictal manifestation. Specific facial coupling of emotion and motor symptoms may take various forms, such as pouting and disgust or smiling. We aimed to highlight brain structures and the network involved during ictal grimacing in parietal lobe seizures. Methods: In this study, we report two patients with drug-resistant epilepsy, with seizure onset located in the inferior parietal lobule and a semiology characterized by ictal grimacing. Patients were explored with intracranial electrodes using the stereo-electroencephalographic method. Time-frequency and functional connectivity (a non-linear regression method based on the h² correlation coefficient) signal analyses were performed time-locked to ictal grimace. For both patients, using spectral analysis, we were able to confirm that the bipolar channels, localized at the level of the inferior parietal lobule, were involved in the seizure onset zone, exhibiting a high frequency discharge. Results: The first patient presented with ictal pouting and disgust and the second with smiling/laughter. Connectivity analysis highlighted two different networks responsible for seizure semiology, consisting of grimacing with different emotional expression. The inferior parietal lobule, connected mainly to the anterior insula, dorsal-lateral prefrontal cortex and frontal operculum were responsible for the typical grimace associated with disgust. Furthermore, the inferior parietal lobule, basal temporal structures, superior temporal gyrus, orbitofrontal cortex and temporal pole were involved in smiling and laughter. Significance: It is of great significance for epileptologists to know that the same seizure onset zone in the inferior parietal lobule can generate contrasting facial expressions, smiling/laughter and pouting/disgust, by engaging different epileptogenic networks; the temporo-basal-orbitofrontal and insulo-opercular networks, respectively.

Network of autoscopic hallucinations elicited by intracerebral stimulations of periventricular nodular heterotopia: An SEEG study.

Periventricular nodular heterotopias (PVNH) are areas of neurons abnormally located in the white matter that might be involved in physiological cortical functions. Autoscopic hallucinations are changes in self-consciousness determined by a mismatch in integration of multiple sensory inputs. Our goal is to highlight the brain network involved in generation of autoscopic hallucination elicited by electrical stimulation of a PVNH in a drug resistant epilepsy patient. Our patient was explored using stereo-electroencephalography with electrodes covering the right posterior temporal PVNH and the adjacent cortex. Direct electrical high frequency stimulation of the PVNH elicited autoscopic hallucinations mainly involving the face and upper trunk. We then used multiple modalities to determine brain connectivity: single pulse electrical stimulation of the PVNH and stimulation-evoked potentials were used to highlight resting state effective connectivity. High-frequency stimulation using alternating polarity pulses enabled us to identify the network involved, time-locked to the clinical effect and to map symptom-related effective connectivity. Functional connectivity using a non-linear regression method was used to determine dependencies between different cortical regions following the stimulation. Finally, structural connectivity was highlighted using deterministic fiber tracking. Multi-modal connectivity analysis identified a network involving the PVNH, occipital and temporal neocortex, fusiform gyrus and parietal cortex.

Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG.

The success of stereoelectroencephalographic (SEEG) investigations depends crucially on the hypotheses on the putative location of the seizure onset zone. This information is derived from non-invasive data either based on visual analysis or advanced source localization algorithms. While source localization applied to interictal spikes recorded on scalp is the classical method, it does not provide unequivocal information regarding the seizure onset zone. Raw ictal activity contains a mixture of signals originating from several regions of the brain as well as EMG artifacts, hampering direct input to the source localization algorithms. We therefore introduce a methodology that disentangles the various sources contributing to the scalp ictal activity using independent component analysis and uses equivalent current dipole localization as putative locus of ictal sources. We validated the results of our analysis pipeline by performing long-term simultaneous scalp - intracerebral (SEEG) recordings in 14 patients and analyzing the wavelet coherence between the independent component encoding the ictal discharge and the SEEG signals in 8 patients passing the inclusion criteria. Our results show that invasively recorded ictal onset patterns, including low-voltage fast activity, can be captured by the independent component analysis of scalp EEG. The visibility of the ictal activity strongly depends on the depth of the sources. The equivalent current dipole localization can point to the seizure onset zone (SOZ) with an accuracy that can be as high as 10 mm for superficially located sources, that gradually decreases for deeper seizure generators, averaging at 47 mm in the 8 analyzed patients. Independent component analysis is therefore shown to have a promising SOZ localizing value, indicating whether the seizure onset zone is neocortical, and its approximate location, or located in mesial structures. That may contribute to a better crafting of the hypotheses used as basis of the stereo-EEG implantations.

Encoded multichromophore response for simultaneous label-free detection.

The self-assembly of molecularly precise nanostructures is widely expected to form the basis of future high-speed integrated circuits, but the technologies suitable for such circuits are not well understood. In this work, DNA self-assembly is used to create molecular logic circuits that can selectively identify specific biomolecules in solution by encoding the optical response of near-field coupled arrangements of chromophores. The resulting circuits can detect label-free, femtomole quantities of multiple proteins, DNA oligomers, and small fragments of RNA in solution via ensemble optical measurements. This method, which is capable of creating multiple logic-gate-sensor pairs on a 2 x 80 x 80-nm DNA grid, is a step toward more sophisticated nanoscale logic circuits capable of interfacing computers with biological processes.

Social Feedback During Sensorimotor Synchronization Changes Salivary Oxytocin and Behavioral States.

In humans and animal models, oxytocin increases social closeness, attachment and prosocial behaviors, while decreasing anxiety and stress levels. Efficiently triggering the release of endogenous oxytocin could serve as a powerful therapeutic intervention for disorders of social behavior and for anxiety. We designed a new version of a social sensorimotor synchronization task to investigate the role of social approval in inducing biochemical and psychological changes following behavioral synchrony in a sample of 80 college students. Social approval in the form of real time positive feedback increased well-being only in women, while increasing social closeness in both genders. Social disapproval in the form of real time negative feedback prevented a decrease in stress levels that otherwise women reported following engagement in either social or non-social synchronization. Surprisingly, for certain personality traits, negative social feedback during sensorimotor synchronization was psychologically beneficial irrespective of gender. Salivary oxytocin levels increased only in women after the social but not the non-social synchronization tasks. Oxytocin dynamics were independent of the type of real time feedback that subjects received, indicating the existence of distinct mechanisms for hormonal versus behavioral changes following synchronization. Nevertheless, changes in salivary oxytocin after positive social feedback correlated with changes in well-being and predicted changes in prosocial attitudes. Our findings show evidence of distinct mechanisms for behavioral versus hormonal changes following social sensorimotor synchronization, and indicate that gender and personality traits should be carefully considered when designing behavioral therapies for improving social attitudes and for stress management.

Clinical Accuracy of Customized Stereotactic Fixtures for Stereoelectroencephalography.

BACKGROUND: Stereoelectroencephalograpy (SEEG) is a diagnostic method involving 3-dimensional exploration of brain structures using depth electrodes for locating epileptogenic foci in patients with drug-resistant epilepsy. A variety of frame-based, frameless, and robotic stereotactic systems have been designed for the accurate placement of depth electrodes. OBJECTIVES: Using the FHC microTargeting platform as a model, we introduce a fully customized design that has all the constructive elements positioned by a computer algorithm, according to the planned trajectories, anchoring points, and anatomic constraints. All the constructive elements form a single-body fixture, which allows for the efficient implantation of multiple depth electrodes following trajectories having a wide range of orientations. We aim at evaluating the safety and accuracy of this stereotactic system in a clinical setting. METHODS: A total of 173 depth electrodes were implanted in 21 patients with drug-resistant epilepsy. Matlab and DEETO software packages were used to postoperatively evaluate the targeting accuracy. Automatic detection of electrode locations eliminated any subjectivity in calculating the targeting errors. RESULTS: As a result of using custom geometry of the stereotactic platform, the new design is optimized for each patient and streamlines the surgical procedures. The most important results characterizing the platform's accuracy are the values of 1.22 mm for the median lateral target point localization error and 1.17 mm for the median lateral entry point localization error. CONCLUSIONS: The patient-customized platforms are comparable in terms of safety, accuracy, and simplicity of use to the existing robotic devices for implantation of depth electrodes in patients undergoing SEEG investigations.