Deviations from Critical Dynamics in Interictal Epileptiform Activity.

The framework of criticality provides a unifying perspective on neuronal dynamics from in vitro cortical cultures to functioning human brains. Recent findings suggest that a healthy cortex displays critical dynamics, giving rise to scale-free spatiotemporal cascades of activity, termed neuronal avalanches. Pharmacological manipulations of the excitation-inhibition balance (EIB) in cortical cultures were previously shown to result in deviations from criticality and from the power law scaling of avalanche size distribution. To examine the sensitivity of neuronal avalanche metrics to altered EIB in humans, we focused on epilepsy, a neurological disorder characterized by hyperexcitable networks. Using magnetoencephalography, we quantitatively assessed deviations from criticality in the brain dynamics of patients with epilepsy during interictal (between-seizures) activity. Compared with healthy control subjects, epilepsy patients tended to exhibit a higher neural gain and larger avalanches, particularly during interictal epileptiform activity. Moreover, deviations from scale-free behavior were exclusively connected to brief intervals at epileptiform discharges, strengthening the association between deviations from criticality and the instantaneous changes in EIB. The avalanches collected during interictal epileptiform activity had not only a stereotypical size range but also involved particular spatial patterns of activations, as expected for periods of epileptic network dominance. Overall, the neuronal avalanche metrics provide a quantitative novel description of interictal brain activity of patients with epilepsy. SIGNIFICANCE STATEMENT: Healthy brain dynamics requires a delicate balance between excitatory and inhibitory processes. Several brain disorders, such as epilepsy, are associated with altered excitation-inhibition balance, but assessing this balance using noninvasive tools is still challenging. In this study, we apply the framework of critical brain dynamics to data from epilepsy patients, which were recorded between seizures. We show that metrics of criticality provide a sensitive tool for noninvasive assessment of changes in the balance. Specifically, brain activity of epilepsy patients deviates from healthy critical brain dynamics, particularly during abnormal epileptiform activity. The study offers a novel quantitative perspective on epilepsy and its relation to healthy brain dynamics.

Near-Critical Dynamics in Stimulus-Evoked Activity of the Human Brain and Its Relation to Spontaneous Resting-State Activity.

In recent years, numerous studies have found that the brain at resting state displays many features characteristic of a critical state. Here we examine whether stimulus-evoked activity can also be regarded as critical. Additionally, we investigate the relation between resting-state activity and stimulus-evoked activity from the perspective of criticality. We found that cortical activity measured by magnetoencephalography (MEG) is near critical and organizes as neuronal avalanches at both resting-state and stimulus-evoked activities. Moreover, a significantly high intrasubject similarity between avalanche size and duration distributions at both cognitive states was found, suggesting that the distributions capture specific features of the individual brain dynamics. When comparing different subjects, a higher intersubject consistency was found for stimulus-evoked activity than for resting state. This was expressed by the distance between avalanche size and duration distributions of different participants and was supported by the spatial spreading of the avalanches involved. During the course of stimulus-evoked activity, time locked to the stimulus onset, we demonstrate fluctuations in the gain of the neuronal system and thus short timescale deviations from the critical state. Nonetheless, the overall near-critical state in stimulus-evoked activity is retained over longer timescales, in close proximity and with a high correlation to spontaneous (not time-locked) resting-state activity. Spatially, the observed fluctuations in gain manifest through anticorrelative activations of brain sites involved, suggesting a switch between task-negative (default mode) and task-positive networks and assigning the changes in excitation-inhibition balance to nodes within these networks. Overall, this study offers a novel outlook on evoked activity through the framework of criticality. SIGNIFICANCE STATEMENT: The organization of stimulus-evoked activity and ongoing cortical activity is a topic of high importance. The article addresses several general questions. What is the spatiotemporal organization of stimulus-evoked cortical activity in healthy human subjects? Are there deviations from excitation-inhibition balance during stimulus-evoked activity? What is the relationship between stimulus-evoked activity and ongoing resting-state activity? Using magnetoencephalography (MEG), we demonstrate that stimulus-evoked activity in humans follows a critical branching process that produces neuronal avalanches. Additionally, we investigate the spatiotemporal relationship between resting-state activity and stimulus-evoked activity from the perspective of critical dynamics. These analyses reveal new aspects of this complex relationship and offer novel insights into the interplay between excitation and inhibition that were not observed previously using conventional approaches.

Folding of multidomain proteins: biophysical consequences of tethering even in apparently independent folding.

Most eukaryotic and a substantial fraction of prokaryotic proteins are composed of more than one domain. The tethering of these evolutionary, structural, and functional units raises, among others, questions regarding the folding process of conjugated domains. Studying the folding of multidomain proteins in silico enables one to identify and isolate the tethering-induced biophysical determinants that govern crosstalks generated between neighboring domains. For this purpose, we carried out coarse-grained and atomistic molecular dynamics simulations of two two-domain constructs from the immunoglobulin-like ß-sandwich fold. Each of these was experimentally shown to behave as the "sum of its parts," that is, the thermodynamic and kinetic folding behavior of the constituent domains of these constructs seems to occur independently, with the folding of each domain uncoupled from the folding of its partner in the two-domain construct. We show that the properties of the individual domains can be significantly affected by conjugation to another domain. The tethering may be accompanied by stabilizing as well as destabilizing factors whose magnitude depends on the size of the interface, the length, and the flexibility of the linker, and the relative stability of the domains. Accordingly, the folding of a multidomain protein should not be viewed as the sum of the folding patterns of each of its parts, but rather, it involves abrogating several effects that lead to this outcome. An imbalance between these effects may result in either stabilization or destabilization owing to the tethering.

Source localization using virtual magnetoencephalography helmets: A simulation study toward a prior-based tailored scheme.

Magnetoencephalography (MEG) source estimation of brain electromagnetic fields is an ill-posed problem. A virtual MEG helmet (VMH), can be constructed by recording in different head positions and then transforming the multiple head-MEG coordinates into one head frame (i.e., as though the MEG helmet was moving while the head remained static). The constructed VMH has sensors placed in various distances and angles, thus improving the spatial sampling of neuromagnetic fields. VMH has been previously shown to increase total information in comparison to a standard MEG helmet. The aim of this study was to examine whether VMH can improve source estimation accuracy. To this end, controlled simulations were carried out, in which the source characteristics are predefined. A series of VMHs were constructed by applying two or three translations and rotations to a standard 248 channel MEG array. In each simulation, the magnetic field generated by 1 to 5 dipoles was forward projected, alongside noise components. The results of this study showed that at low noise levels (e.g., averaged data of similar signals), VMHs can significantly improve the accuracy of source estimations, compared to the standard MEG array. Moreover, when utilizing a priori information, tailoring the constructed VMHs to specific sets of postulated neuronal sources can further improve the accuracy. This is shown to be a robust and stable method, even for proximate locations. Overall, VMH may add significant precision to MEG source estimation, for research and clinical benefits, such as in challenging epilepsy cases, aiding in surgical design.

Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures.

Video-EEG monitoring (VEM) is imperative in seizure classification and presurgical assessment of epilepsy patients. Analysis of VEM is currently performed in most institutions using a freeform report, a time-consuming process resulting in a non-standardized report, limiting the use of this essential diagnostic tool. Herein we present a pilot feasibility study of our experience with "Digital Semiology" (DS), a novel seizure encoding software. It allows semiautomated annotation of the videos of suspected events from a predetermined, hierarchal set of options, with highly detailed semiologic descriptions, somatic localization, and timing. In addition, the software's semiologic extrapolation functions identify characteristics of focal seizures and PNES, sequences compatible with a Jacksonian march, and risk factors for SUDEP. Sixty episodes from a mixed adult and pediatric cohort from one level 4 epilepsy center VEM archives were analyzed using DS and the reports were compared with the standard freeform ones, written by the same epileptologists. The behavioral characteristics appearing in the DS and freeform reports overlapped by 78-80%. Encoding of one episode using DS required an average of 18 min 13 s (standard deviation: 14 min and 16 s). The focality function identified 19 out of 43 focal episodes, with a sensitivity of 45.45% (CI 30.39-61.15%) and specificity of 87.50% (CI 61.65-98.45%). The PNES function identified 6 of 12 PNES episodes, with a sensitivity of 50% (95% CI 21.09-78.91%) and specificity of 97.2 (95% CI 88.93-99.95%). Eleven events of GTCS triggered the SUDEP risk alert. Overall, these results show that video recordings of suspected seizures can be encoded using the DS software in a precise manner, offering the added benefit of semiologic alerts. The present study represents an important step toward the formation of an annotated video archive, to be used for machine learning purposes. This will further the goal of automated VEM analysis, ultimately contributing to wider utilization of VEM and therefore to the reduction of the treatment gap in epilepsy.

Neuronal avalanches and time-frequency representations in stimulus-evoked activity.

Neuronal avalanches are a hallmark feature of critical dynamics in the brain. While the theoretical framework of a critical branching processes is generally accepted for describing avalanches during ongoing brain activity, there is a current debate about the corresponding dynamical description during stimulus-evoked activity. As the brain activity evoked by external stimuli considerably varies in magnitude across time, it is not clear whether the parameters that govern the neuronal avalanche analysis (a threshold or a temporal scale) should be adaptively altered to accommodate these changes. Here, the relationship between neuronal avalanches and time-frequency representations of stimulus-evoked activity is explored. We show that neuronal avalanche metrics, calculated under a fixed threshold and temporal scale, reflect genuine changes in the underlying dynamics. In particular, event-related synchronization and de-synchronization are shown to align with variations in the power-law exponents of avalanche size distributions and the branching parameter (neural gain), as well as in the spatio-temporal spreading of avalanches. Nonetheless, the scale-invariant behavior associated with avalanches is shown to be a robust feature of healthy brain dynamics, preserved across various periods of stimulus-evoked activity and frequency bands. Taken together, the combined results suggest that throughout stimulus-evoked responses the operating point of the dynamics may drift within an extended-critical-like region.

Brain response during the M170 time interval is sensitive to socially relevant information.

Deciphering the social meaning of facial displays is a highly complex neurological process. The M170, an event related field component of MEG recording, like its EEG counterpart N170, was repeatedly shown to be associated with structural encoding of faces. However, the scope of information encoded during the M170 time window is still being debated. We investigated the neuronal origin of facial processing of integrated social rank cues (SRCs) and emotional facial expressions (EFEs) during the M170 time interval. Participants viewed integrated facial displays of emotion (happy, angry, neutral) and SRCs (indicated by upward, downward, or straight head tilts). We found that the activity during the M170 time window is sensitive to both EFEs and SRCs. Specifically, highly prominent activation was observed in response to SRC connoting dominance as compared to submissive or egalitarian head cues. Interestingly, the processing of EFEs and SRCs appeared to rely on different circuitry. Our findings suggest that vertical head tilts are processed not only for their sheer structural variance, but as social information. Exploring the temporal unfolding and brain localization of non-verbal cues processing may assist in understanding the functioning of the social rank biobehavioral system.