Design and validation of a diagnostic suspicion checklist to differentiate epileptic from psychogenic nonepileptic seizures (PNES-DSC).

OBJECTIVE: Psychogenic non-epileptic seizures (PNES) are complex clinical manifestations and misdiagnosis as status epilepticus remains high, entailing deleterious consequences for patients. Video-electroencephalography (vEEG) remains the gold-standard method for diagnosing PNES. However, time and economic constraints limit access to vEEG, and clinicians lack fast and reliable screening tools to assist in the differential diagnosis with epileptic seizures (ES). This study aimed to design and validate the PNES-DSC, a clinically based PNES diagnostic suspicion checklist with adequate sensitivity (Se) and specificity (Sp) to discriminate PNES from ES. METHODS: A cross-sectional study with 125 patients (n = 104 drug-resistant epilepsy; n = 21 PNES) admitted for a vEEG protocolised study of seizures. A preliminary PNES-DSC (16-item) was designed and used by expert raters blinded to the definitive diagnosis to evaluate the seizure video recordings for each patient. Cohen's kappa coefficient, leave-one-out cross-validation (LOOCV) and balance accuracy (BAC) comprised the main validation analysis. RESULTS: The final PNES-DSC is a 6-item checklist that requires only two to be present to confirm the suspicion of PNES. The LOOCV showed 71.4% BAC (Se = 45.2%; Sp = 97.6%) when the expert rater watched one seizure video recording and 83.4% BAC (Se = 69.6%; Sp = 97.2%) when the expert rater watched two seizure video recordings. CONCLUSION: The PNES-DSC is a straightforward checklist with adequate psychometric properties. With an integrative approach and appropriate patient history, the PNES-DSC can assist clinicians in expediting the final diagnosis of PNES when vEEG is limited. The PNES-DSC can also be used in the absence of patients, allowing clinicians to assess seizure recordings from smartphones.

A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets.

Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow-wave characteristics across multiple, openly available electrocorticography (ECoG) and calcium imaging datasets.

Recording physiological and pathological cortical activity and exogenous electric fields using graphene microtransistor arrays in vitro.

Graphene-based solution-gated field-effect transistors (gSGFETs) allow the quantification of the brain's full-band signal. Extracellular alternating current (AC) signals include local field potentials (LFP, population activity within a reach of hundreds of micrometers), multiunit activity (MUA), and ultimately single units. Direct current (DC) potentials are slow brain signals with a frequency under 0.1 Hz, and commonly filtered out by conventional AC amplifiers. This component conveys information about what has been referred to as "infraslow" activity. We used gSGFET arrays to record full-band patterns from both physiological and pathological activity generated by the cerebral cortex. To this end, we used an in vitro preparation of cerebral cortex that generates spontaneous rhythmic activity, such as that occurring in slow wave sleep. This examination extended to experimentally induced pathological activities, including epileptiform discharges and cortical spreading depression. Validation of recordings obtained via gSGFETs, including both AC and DC components, was accomplished by cross-referencing with well-established technologies, thereby quantifying these components across different activity patterns. We then explored an additional gSGFET potential application, which is the measure of externally induced electric fields such as those used in therapeutic neuromodulation in humans. Finally, we tested the gSGFETs in human cortical slices obtained intrasurgically. In conclusion, this study offers a comprehensive characterization of gSGFETs for brain recordings, with a focus on potential clinical applications of this emerging technology.

Thalamic Foxp2 regulates output connectivity and sensory-motor impairments in a model of Huntington's Disease.

BACKGROUND: Huntington's Disease (HD) is a disorder that affects body movements. Altered glutamatergic innervation of the striatum is a major hallmark of the disease. Approximately 30% of those glutamatergic inputs come from thalamic nuclei. Foxp2 is a transcription factor involved in cell differentiation and reported low in patients with HD. However, the role of the Foxp2 in the thalamus in HD remains unexplored. METHODS: We used two different mouse models of HD, the R6/1 and the HdhQ111 mice, to demonstrate a consistent thalamic Foxp2 reduction in the context of HD. We used in vivo electrophysiological recordings, microdialysis in behaving mice and rabies virus-based monosynaptic tracing to study thalamo-striatal and thalamo-cortical synaptic connectivity in R6/1 mice. Micro-structural synaptic plasticity was also evaluated in the striatum and cortex of R6/1 mice. We over-expressed Foxp2 in the thalamus of R6/1 mice or reduced Foxp2 in the thalamus of wild type mice to evaluate its role in sensory and motor skills deficiencies, as well as thalamo-striatal and thalamo-cortical connectivity in such mouse models. RESULTS: Here, we demonstrate in a HD mouse model a clear and early thalamo-striatal aberrant connectivity associated with a reduction of thalamic Foxp2 levels. Recovering thalamic Foxp2 levels in the mouse rescued motor coordination and sensory skills concomitant with an amelioration of neuropathological features and with a repair of the structural and functional connectivity through a restoration of neurotransmitter release. In addition, reduction of thalamic Foxp2 levels in wild type mice induced HD-like phenotypes. CONCLUSIONS: In conclusion, we show that a novel identified thalamic Foxp2 dysregulation alters basal ganglia circuits implicated in the pathophysiology of HD.

Virtual embodiment for improving range of motion in patients with movement-related shoulder pain: an experimental study.

BACKGROUND: Recent evidence supports the use of immersive virtual reality (VR) as a means of delivering bodily illusions that may have therapeutic potential for the treatment of musculoskeletal conditions. We wanted to investigate whether a single session of an embodiment-based immersive VR training program influences pain-free range of motion in patients with shoulder pain. METHODS: We designed a rehabilitation program based on developing ownership over a virtual body and then "exercising" the upper limb in immersive VR, while the real arm remains static. We then carried out a single-arm pre-post experiment in which 21 patients with movement-related musculoskeletal shoulder pain were exposed to the 15-min VR program and measured their active pain-free range of motion immediately before and afterwards. RESULTS: We found that shoulder abduction and hand-behind-back movements, but not shoulder flexion, were significantly and clinically improved post-intervention and that the level of improvement correlated with the level of embodiment. Following this one session, at 1-week follow-up the improvements were not maintained. CONCLUSIONS: Virtual embodiment may be a useful therapeutic tool to help improve range of motion in patients with movement-related shoulder pain in the short term, which in turn could expedite rehabilitation and recovery in these conditions.

M-current modulation of cortical slow oscillations: Network dynamics and computational modeling.

The slow oscillation is a synchronized network activity expressed by the cortical network in slow wave sleep and under anesthesia. Waking up requires a transition from this synchronized brain state to a desynchronized one. Cholinergic innervation is critical for the transition from slow-wave-sleep to wakefulness, and muscarinic action is largely exerted through the muscarinic-sensitive potassium current (M-current) block. We investigated the dynamical impact of blocking the M-current on slow oscillations, both in cortical slices and in a cortical network computational model. Blocking M-current resulted in an elongation of Up states (by four times) and in a significant firing rate increase, reflecting an increased network excitability, albeit no epileptiform discharges occurred. These effects were replicated in a biophysical cortical model, where a parametric reduction of the M-current resulted in a progressive elongation of Up states and firing rate. All neurons, and not only those modeled with M-current, increased their firing rates due to network recurrency. Further increases in excitability induced even longer Up states, approaching the microarousals described in the transition towards wakefulness. Our results bridge an ionic current with network modulation, providing a mechanistic insight into network dynamics of awakening.

Virtual embodiment in fibromyalgia.

Chronic pain alters the experience of owning a body and leads to disturbances in bodily perception. We tested whether women with fibromyalgia (FM) are receptive to bodily illusions of owning a visible and progressively invisible body in immersive virtual reality (VR), and what modulates this experience. Twenty patients participated in two experimental sessions; each session included two conditions in a counterbalanced order. We found that patients with FM could indeed experience virtual embodiment. Sentiment analysis revealed significantly more positive reactions to the progressively invisible body, yet twice as many patients declared they preferred the illusion of a visible virtual body. A linear mixed model revealed that the strength of embodiment was positively associated with body perception disturbances and negatively associated with FM symptoms intensity. No effect of pain during the VR experience nor interoception awareness on embodiment was found. The results indicated that patients with FM are receptive to virtual bodily illusions and that the impact of the embodiment depends on affective reactions, the level of cognitive body distortions, and the intensity of symptoms. Importantly, there is a large variation among patients which should be considered in future VR-based interventions.

Domestic Violence From a Child Perspective: Impact of an Immersive Virtual Reality Experience on Men With a History of Intimate Partner Violent Behavior.

Domestic violence has long-term negative consequences on children. In this study, men with a history of partner aggression and a control group of non-offenders were embodied in a child's body from a first-person perspective in virtual reality (VR). From this perspective, participants witnessed a scene of domestic violence where a male avatar assaulted a female avatar. We evaluated the impact of the experience on emotion recognition skills and heart rate deceleration responses. We found that the experience mainly impacted the recognition of angry facial expressions. The results also indicate that males with a history of partner aggression had larger physiological responses during an explicit violent event (when the virtual abuser threw a telephone) compared with controls, while their physiological reactions were less pronounced when the virtual abuser invaded the victim's personal space. We show that embodiment from a child's perspective during a conflict situation in VR impacts emotion recognition, physiological reactions, and attitudes towards violence. We provide initial evidence of the potential of VR in the rehabilitation and neuropsychological assessment of males with a history of domestic violence, especially in relation to children.

Altered bodily perceptions in chronic neuropathic pain conditions and implications for treatment using immersive virtual reality.

Chronic neuropathic pain is highly disabling and difficult to treat and manage. Patients with such conditions often report altered bodily perceptions that are thought to be associated with maladaptive structural and functional alterations in the somatosensory cortex. Manipulating these altered perceptions using body illusions in virtual reality is being investigated and may have positive clinical implications for the treatment of these conditions. Here, we have conducted a narrative review of the evidence for the types of bodily distortions associated with a variety of peripheral and central neuropathic pain conditions. In addition, we summarize the experimental and clinical studies that have explored embodiment and body transformation illusions in immersive virtual reality for neuropathic pain relief, which are thought to target these maladaptive changes, as well as suggesting directions for future research.

Deterministic and Stochastic Components of Cortical Down States: Dynamics and Modulation.

Slow oscillations are an emergent activity of the cerebral cortex network consisting of alternating periods of activity (Up states) and silence (Down states). Up states are periods of persistent cortical activity that share properties with that of underlying wakefulness. However, the occurrence of Down states is almost invariably associated with unconsciousness, both in animal models and clinical studies. Down states have been attributed relevant functions, such as being a resetting mechanism or breaking causal interactions between cortical areas. But what do Down states consist of? Here, we explored in detail the network dynamics (e.g., synchronization and phase) during these silent periods in vivo (male mice), in vitro (ferrets, either sex), and in silico, investigating various experimental conditions that modulate them: anesthesia levels, excitability (electric fields), and excitation/inhibition balance. We identified metastability as two complementary phases composing such quiescence states: a highly synchronized "deterministic" period followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamical properties of the resulting rhythm, as well as the responsiveness to incoming inputs or refractoriness. We propose detailed Up and Down state cycle dynamics that bridge cortical properties emerging at the mesoscale with their underlying mechanisms at the microscale, providing a key to understanding unconscious states.SIGNIFICANCE STATEMENT The cerebral cortex expresses slow oscillations consisting of Up (active) and Down (silent) states. Such activity emerges not only in slow wave sleep, but also under anesthesia and in brain lesions. Down states functionally disconnect the network, and are associated with unconsciousness. Based on a large collection of data, novel data analysis approaches and computational modeling, we thoroughly investigate the nature of Down states. We identify two phases: a highly synchronized "deterministic" period, followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamic properties of the resulting rhythm and responsiveness to incoming inputs. This finding reconciles different theories of slow rhythm generation and provides clues about how the brain switches from conscious to unconscious brain states.

On the Practical Use of Immersive Virtual Reality for Rehabilitation of Intimate Partner Violence Perpetrators in Prison.

Virtual reality (VR) allows the user to be immersed in environments in which they can experience situations and social interactions from different perspectives by means of virtual embodiment. In the context of rehabilitation of violent behaviors, a participant could experience a virtual violent confrontation from different perspectives, including that of the victim and bystanders. This approach and other virtual scenes can be used as a useful tool for the rehabilitation of intimate partner violence (IPV) perpetrators, through improvement of their empathic skills or for training in non-violent responses. In this perspective, we revise and discuss the use of this tool in a prison environment for the rehabilitation of IPV perpetrators with a particular focus on practical aspects based on our experience.

Impact of virtual embodiment and exercises on functional ability and range of motion in orthopedic rehabilitation.

Recent evidence supports the use of immersive virtual reality (immersive VR) as a means of applying visual feedback techniques in neurorehabilitation. In this study, we investigated the benefits of an embodiment-based immersive VR training program for orthopedic upper limb rehabilitation, with the aim of improving the motor functional ability of the arm and accelerating the rehabilitation process in patients with a conservatively managed distal radius fracture. We designed a rehabilitation program based on developing ownership over a virtual arm and then exercising it in immersive VR. We carried out a between 3-group controlled trial with 54 patients (mean age = 61.80 ± 14.18): 20 patients were assigned to the experimental training group (immersive VR), 20 to the conventional digit mobilization (CDM) training control group, and 14 to a non-immersive (non-immersive VR) training control group. We found that functional recovery of the arm in the immersive VR group was correlated with the ownership and agency scores over the virtual arm. We also found larger range of joint movements and lower disability of the fractured arm compared with patients in the Non-immersive VR and CDM groups. Feeling embodied in a virtual body can be used as a rehabilitation tool to speed up and improve motor functional recovery of a fractured arm after the immobilization period.

Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia.

In the arousal process, the brain restores its integrative activity from the synchronized state of slow wave activity (SWA). The mechanisms underpinning this state transition remain, however, to be elucidated. Here we simultaneously probed neuronal assemblies throughout the whole cortex with micro-electrocorticographic recordings in mice. We investigated the progressive shaping of propagating SWA at different levels of isoflurane. We found a form of memory of the wavefront shapes at deep anesthesia, tightly alternating posterior-anterior-posterior patterns. At low isoflurane, metastable patterns propagated in more directions, reflecting an increased complexity. The wandering across these mesostates progressively increased its randomness, as predicted by simulations of a network of spiking neurons, and confirmed in our experimental data. The complexity increase is explained by the elevated excitability of local assemblies with no modifications of the network connectivity. These results shed new light on the functional reorganization of the cortical network as anesthesia fades out.

Is Consciousness First in Virtual Reality?

The prevailing scientific paradigm is that matter is primary and everything, including consciousness can be derived from the laws governing matter. Although the scientific explanation of consciousness on these lines has not been realized, in this view it is only a matter of time before consciousness will be explained through neurobiological activity in the brain, and nothing else. There is an alternative view that holds that it is fundamentally impossible to explain how subjectivity can arise solely out of material processes-"the hard problem of consciousness"-and instead consciousness should be regarded in itself as a primary force in nature. This view attempts to derive, for example, the laws of physics from models of consciousness, instead of the other way around. While as scientists we can understand and have an intuition for the first paradigm, it is very difficult to understand what "consciousness is primary" might mean since it has no intuitive scientific grounding. Here we show that worlds experienced through virtual reality (VR) are such that consciousness is a first order phenomenon. We discuss the Interface Theory of Perception which claims that in physical reality perceptions are not veridical and that we do not see the "truth" but that perception is based on evolutionary payoffs. We show that this theory may provide an accurate description of perception and consciousness within VR, and we put forward an experimental study that could throw light on this. We conclude that VR does offer an experimental frame that provides intuition with respect to the idea that "consciousness is first" and what this might mean regarding the perceived world. However, we do not draw any conclusions about the veracity of this notion with respect to physical reality or question the emergence of consciousness from brain function.

Linking Brain Structure, Activity, and Cognitive Function through Computation.

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

Virtual reality for the rehabilitation and prevention of intimate partner violence - From brain to behavior: A narrative review.

Rehabilitation and prevention strategies to reduce intimate partner violence (IPV) have limited effectiveness in terms of improving key risk factors and reducing occurrence. Accumulated experimental evidence demonstrates that virtual embodiment, which results in the illusion of owning a virtual body, has a large impact on people's emotional, cognitive, and behavioral responses. This narrative review discusses work that has investigated how embodied perspective - taking in virtual reality has been used as a tool to reduce bias, to enhance recognition of the emotional state of another, and to reduce violent behaviors, in particular in the realm of IPV. Some of the potential neurological mechanisms behind these affective and behavioral changes are also discussed. The process of rehabilitation and prevention is complex and not always effective, but the integration of neuroscience-inspired and validated state-of-the-art technology into the rehabilitation process can make a positive contribution.

Energy-Based Hierarchical Clustering of Cortical Slow Waves in Multi-Electrode Recordings.

The recent development of novel multi-electrode recording technologies has revealed the existence of traveling patterns of cortical activity in many species and under different states of awareness. Among these, slow activation waves occurring under sleep and anesthesia have been widely investigated as they provide unique insights into network features such as excitability, connectivity, structure, and dynamics of the cerebral cortex. Such characterization is usually based on clustering methods which are constrained by a priori assumptions as to the number of clusters to be used or rely on wave-by-wave pattern reconstruction. Here, we introduce a new computational tool based on modal analysis of fluid flows which is robustly applied to multivariate electrophysiological data from cortical networks, namely the Energy-based Hierarchical Waves Clustering method (EHWC). EHWC is composed of three main steps: (1) detecting the occurrence of global waves; (2) reducing the data dimensionality via singular value decomposition; (3) clustering hierarchically the singled-out waves. The analysis does not require the single-channel contribution to the waves, which is a typical bottleneck in this kind of analysis due to the unavoidable intrinsic variability of locally recorded activity. For testing and validation, here we used in vivo extracellular recordings from mice cortex under three different levels of anesthesia. As a result, we found slow waves with an increasing number of propagation modes as the anesthesia level decreases, giving an estimate of the increasing complexity of network dynamics. This and other wave's features replicate and extend the findings from previous literature, paving the way to extend the same approach to non-invasive electrophysiological recordings like EEG and fMRI used clinically for the characterization of brain dynamics and clinical stratification in brain lesions.

Correction: Representation of foreseeable choice outcomes in orbitofrontal cortex triplet-wise interactions.

[This corrects the article DOI: 10.1371/journal.pcbi.1007862.].

Attractor competition enriches cortical dynamics during awakening from anesthesia.

Slow oscillations (≲ 1 Hz), a hallmark of slow-wave sleep and deep anesthesia across species, arise from spatiotemporal patterns of activity whose complexity increases as wakefulness is approached and cognitive functions emerge. The arousal process constitutes an open window to the unknown mechanisms underlying the emergence of such dynamical richness in awake cortical networks. Here, we investigate the changes in network dynamics as anesthesia fades out in the rat visual cortex. Starting from deep anesthesia, slow oscillations gradually increase their frequency, eventually expressing maximum regularity. This stage is followed by the abrupt onset of an infra-slow (~0.2 Hz) alternation between sleep-like oscillations and activated states. A population rate model reproduces this transition driven by an increased excitability that brings it to periodically cross a critical point. Based on our model, dynamical richness emerges as a competition between two metastable attractor states, a conclusion strongly supported by the data.