Gamma-band neural coupling during conceptual alignment.

Conceptual alignment is a prerequisite for mutual understanding. However, little is known about the neurophysiological brain-to-brain underpinning during conceptual alignment for mutual understanding. Here, we recorded multi-channel electroencephalogram (EEG) simultaneously from two participants in Experiment 1 and adopted the dual-tACS techniques in Experiment 2 to investigate the underlying brain-to-brain EEG coupling during conceptual alignment and the possible enhancement effect. Our results showed that 1) higher phase-locking value (PLV), a sensitive measure for quantifying neural coupling strength between EEG signals, at the gamma frequency band (28-40 Hz), was observed in the left temporoparietal site (left TP) area between successful versus unsuccessful conceptual alignment. The left TP gamma coupling strength correlated with the accuracy of conceptual alignment and differentiated whether subjects belonged to the SUCCESS or FAILURE groups in our study. 2) In-phase gamma-band transcranial alternating current stimulation (tACS) over the left TP area increased the accuracy of subjects in the SUCCESS group but not the FAILURE group. 3) The effect of perspective-taking on the accuracy was mediated by the gamma coupling strength within the left TP area. Our results support the role of gamma-band coupling between brains for interpersonal conceptual alignment. We provide dynamic interpersonal neurophysiological insights into the formation of successful communication.

Stroke of bad luck?

We hypothesized that distinct acute right hemisphere lesions disrupt separate components of valuation and emotional response to winning and losing money and of emotional empathy in observing a partner win or lose money. We measured skin conductance response (SCR) and ratings of emotions when acute right hemisphere stroke patients or healthy controls won or lost money in roulette, or when they watched a partner win or lose. Our results showed that percentage of damage after stroke to right anterior insula and frontal operculum negatively correlated with both SCR to winning and losing and difference between rating wins versus losses.

Bilateral focused ultrasound medial thalamotomies for trigeminal neuropathic pain: a randomized controlled study.

OBJECTIVE: Medial thalamotomy has been shown to benefit patients with neuropathic pain, but widespread adoption of this procedure has been limited by reporting of clinical outcomes in studies without a control group. This study aimed to minimize confounders associated with medial thalamotomy for treating chronic pain by using modern MRI-guided stereotactic lesioning and a rigorous clinical design. METHODS: This prospective, double-blinded, randomized controlled trial in 10 patients with trigeminal neuropathic pain used sham procedures as controls. Participants underwent assessments by a pain psychologist and pain management clinician, including use of the following measures: the Numeric Pain Rating Scale (NPRS); patient-reported outcome measures; and patient's impression of improvement at baseline, 1 day, 1 week, 1 month, and 3 months postprocedure. Patients in the treated group underwent bilateral focused ultrasound (FUS) medial thalamotomy targeting the central lateral nucleus. Patients in the control group underwent sham procedures with energy output disabled. The primary efficacy outcome measure was between-group differences in pain intensity (using the NPRS) at baseline and at 3 months postprocedure. Adverse events were measured for safety and included MRI analysis. Exploratory measures of connectivity and metabolism were analyzed using diffusion tensor imaging, functional MRI, and PET, respectively. RESULTS: There were no serious complications from the FUS procedures. MRI confirmed bilateral medial thalamic ablations. There was no significant improvement in pain intensity from baseline to 3 months, either for patients undergoing FUS medial thalamotomy or for sham controls; and the between-group change in NPRS score as the primary efficacy outcome measure was not significantly different. Patient-reported outcome assessments demonstrated improvement (i.e., a decrease) only in pain interference with enjoyment of life at 3 months. There was a perception of benefit at 1 week, but only for patients treated with FUS and not for the sham cohort. Advanced neuroimaging showed that these medial thalamic lesions altered structural connectivity with the postcentral gyrus and demonstrated a trend toward hypometabolism in the insula and amygdala. CONCLUSIONS: This randomized controlled trial of bilateral FUS medial thalamotomy did not reduce the intensity of trigeminal neuropathic pain, although it should be noted that the ability to estimate the magnitude of treatment effects is limited by the small cohort.

Painful Cutaneous Laser Stimulation for Temporal Summation of Pain Assessment.

Variability in pain sensitivity arises not only from the differences in peripheral sensory receptors but also from the differences in central nervous system (CNS) pain inhibition and facilitation mechanisms. Temporal summation of pain (TSP) is an experimental protocol commonly used in human studies of pain facilitation but is susceptible to confounding when elicited with the skin-contact thermode, which adds the responses of touch-related Aß low-threshold mechanoreceptors to nociceptive receptors. In the present study, we evaluate an alternative method involving the use of a contactless cutaneous laser for TSP assessment. We show that repetitive laser stimulations with a one second inter-stimulus interval evoked reliable TSP responses in a significant proportion of healthy subjects (N = 36). Female subjects (N = 18) reported greater TSP responses than male subjects confirming earlier studies of sex differences in central nociceptive excitability. Furthermore, repetitive laser stimulations during TSP induction elicited increased time-frequency electroencephalography (EEG) responses. The present study demonstrates that repetitive laser stimulation may be an alternative to skin-contact methods for TSP assessment in patients and healthy controls. PERSPECTIVE: Temporal summation of pain (TSP) is an experimental protocol commonly used in human studies of pain facilitation. We show that contactless cutaneous laser stimulation is a reliable alternative to the skin contact approaches during TSP assessment.

Anterior insula stimulation increases pain threshold in humans: a pilot study.

OBJECTIVE: Chronic pain results in an enormous societal and financial burden. Opioids are the mainstay of treatment, but opioid abuse has led to an epidemic in the United States. Nonpharmacological treatment strategies like deep brain stimulation could be applied to refractory chronic pain if safe and effective brain targets are identified. The anterior insula is a putative mediator of pain-related affective-motivational and cognitive-evaluative cerebral processing. However, the effect of anterior insula stimulation on pain perception is still unknown. Here, the authors provide behavioral and neurophysiological evidence for stimulating the anterior insula as a means of potential therapeutic intervention for patients with chronic pain. METHODS: Six patients with epilepsy in whom intracerebral electrodes had been implanted for seizure localization were recruited to the study. The direct anterior insula stimulations were performed in the inpatient epilepsy monitoring unit while subjects were fully awake, comfortable, and without sedating medications. The effects of anterior insula stimulation were assessed with quantitative sensory testing for heat pain threshold, nociceptive-specific cutaneous laser-evoked potentials, and intracranial electroencephalogram (EEG) recordings. Control stimulation of noninsular brain regions was performed to test stimulation specificity. Sham stimulations, in which no current was delivered, were also performed to control for potential placebo effects. The safety of these stimulations was evaluated by bedside physicians, real-time intracranial EEG monitoring, and electrocardiogram recordings. RESULTS: Following anterior insula stimulations, the heat pain threshold of each patient significantly increased from baseline (p < 0.001) and correlated with stimulation intensity (regression analysis: ß = 0.5712, standard error 0.070, p < 0.001). Significant changes in ongoing intracranial EEG frequency band powers (p < 0.001), reduction in laser pain intensity, and attenuated laser-evoked potentials were also observed following stimulations. Furthermore, the observed behavioral and neurophysiological effects persisted beyond the stimulations. Subjects were not aware of the stimulations, and there were no cardiovascular or untoward effects. CONCLUSIONS: Additional, nonpharmacological therapies are imperative for the future management of chronic pain conditions and to mitigate the ongoing opioid crisis. This study suggests that direct stimulation of the anterior insula can safely alter cerebral pain processing in humans. Further investigation of the anterior insula as a potential target for therapeutic neuromodulation is underway.

Real-time differentiation of nonconvulsive status epilepticus from other encephalopathies using quantitative EEG analysis: a pilot study.

PURPOSE: Distinguishing nonconvulsive status epilepticus (NCSE) from some nonepileptic encephalopathies is a challenging problem. In many situations, NCSE and nonepileptic encephalopathies are indistinguishable by clinical symptoms and can produce very similar electroencephalography (EEG) patterns. Misdiagnosis or delay to diagnosis of NCSE may increase the rate of morbidity and mortality. METHODS: We developed a fast-differentiating algorithm using quantitative EEG analysis to distinguish NCSE patients from patients with toxic/metabolic encephalopathy (TME). EEG recordings were collected from 11 patients, including 6 with NCSE and 5 with TME. Three nonlinear dynamic measures were used in the proposed algorithm: the maximum short-term Lyapunov exponent (STLmax), phase of attractor (phase/angular frequency), and approximate entropy (ApEn). A further refined metric derived from STLmax and phase of attractor (the mean distance to EEG epoch samples from their centroid in the feature space) was also utilized as a criterion. Paired t tests were carried out to further clarify the separation between the EEG patterns of NCSE and TME. RESULTS: Computational results showed that the performance of the proposed algorithm was sufficient to distinguish NCSE from TME. The results were consistent in all subjects in our study. CONCLUSIONS: The study presents evidence that the maximum short-term Lyapunov exponents (STLmax) and phase of attractors (phase/angular frequency) can be useful in assisting clinical diagnosis of NCSE. Findings presented in this article provide a promising indication that the proposed algorithm may correctly distinguish NCSE from TME. Although the exact mechanism of this association remains unknown, the authors suggest that epileptic activity is highly associated with and can be modeled by dynamic systems.

Attention to painful cutaneous laser stimuli evokes directed functional interactions between human sensory and modulatory pain-related cortical areas.

The human 'pain network' includes cortical areas that are activated during the response to painful stimuli (termed category 1) or during psychological processes that modulate pain, for example, distraction (termed category 2). These categories include parts of the parasylvian (PS), medial frontal (MF), and paracentral cortex (S1&M1). Here we test the hypothesis that causal interactions both within and between category 1 and category 2 modules occur during attention to a painful stimulus. Event-related causality (ERC) was calculated from local field potentials recorded directly from these cortical areas during the response to a painful cutaneous laser stimulus in patients being monitored for epilepsy. The number of electrodes involved in pairs with significant ERC in category 1 was greater for pre-stimulus vs post-stimulus and for attention vs distraction. This is consistent with our prior evidence that the category 1 'pain network' changes rapidly with time intervals and tasks. In contrast, the interaction between categories was often unchanged or stable across intervals and tasks, particularly in MF. The proportion of contacts involved in interactions with PS was greater during distraction vs attention while activation was less, which suggests that distraction involves an inhibitory process in PS. Functional interactions between categories were overwhelmingly in the direction from category 2>1, particularly for contacts in MF which often had a driver role. These results demonstrate that MF is densely interconnected throughout the 'pain network' so that stimulation of MF might be used to disrupt the 'pain network' as a therapy for pain.

Optimisation and data mining techniques for the screening of epileptic patients.

Identifying abnormalities or anomalies by visual inspection on neurophysiologic signals such as ElectroEncephaloGrams (EEGs), is extremely challenging. We propose a novel Multi-Dimensional Time Series (MDTS) classification technique, called Connectivity Support Vector Machines (C-SVMs) that integrates brain connectivity network with SVMs. To alter noise in EEG data, Independent Component Analysis based on the Unbiased Quasi Newton Method was applied. C-SVM achieved 94.8% accuracy classifying subjects compared to 69.4% accuracy with standard SVMs. It suggests that C-SVM can be a rapid, yet accurate, technique for online differentiation between epileptic and normal subjects. It may solve other classification MDTS problems too.

A robust spike and wave algorithm for detecting seizures in a genetic absence seizure model.

Animal Models are used extensively in basic epilepsy research. In many studies, there is a need to accurately score and quantify all epileptic spike and wave discharges (SWDs) as captured by electroencephalographic (EEG) recordings. Manual scoring of long term EEG recordings is a time-consuming and tedious task that requires inordinate amount of time of laboratory personnel and an experienced electroencephalographer. In this paper, we adapt a SWD detection algorithm, originally proposed by the authors for absence (petit mal) seizure detection in humans, to detect SWDs appearing in EEG recordings of Fischer 334 rats. The algorithm is robust with respect to the threshold parameters. Results are compared to manual scoring and the effect of different threshold parameters is discussed.

Antiepileptic drug intervention decouples electroencephalogram (EEG) signals: a case study in Unverricht-Lundborg Disease.

Change in severity of myoclonus as an outcome measure of antiepileptic drug (AED) treatment in patients with Unverricht-Lundborg Disease (ULD) has been estimated by utilizing the Unified Myoclonus Rating Scale (UMRS). In this study, we measure treatment effects through EEG analysis using mutual information approach to quantify interdependence/coupling strength among different electrode sites. Mutual information is known to have the ability to capture linear and non-linear dependencies between EEG time series with superior performance over the traditional linear measures. One subject with ULD participated in this study and 1-hour EEG recordings were acquired before and after treatment of AED. Our results indicate that the mutual information is significantly lower after taking the add-on AED for four weeks at least. This finding could lead to a new insight for developing a new outcome measure for patient with ULD, when UMRS could potentially fail to detect a significant difference.

Quantitative complexity analysis in multi-channel intracranial EEG recordings form epilepsy brains.

Epilepsy is a brain disorder characterized clinically by temporary but recurrent disturbances of brain function that may or may not be associated with destruction or loss of consciousness and abnormal behavior. Human brain is composed of more than 10 to the power 10 neurons, each of which receives electrical impulses known as action potentials from others neurons via synapses and sends electrical impulses via a sing output line to a similar (the axon) number of neurons. When neuronal networks are active, they produced a change in voltage potential, which can be captured by an electroencephalogram (EEG). The EEG recordings represent the time series that match up to neurological activity as a function of time. By analyzing the EEG recordings, we sought to evaluate the degree of underlining dynamical complexity prior to progression of seizure onset. Through the utilization of the dynamical measurements, it is possible to classify the state of the brain according to the underlying dynamical properties of EEG recordings. The results from two patients with temporal lobe epilepsy (TLE), the degree of complexity start converging to lower value prior to the epileptic seizures was observed from epileptic regions as well as non-epileptic regions. The dynamical measurements appear to reflect the changes of EEG's dynamical structure. We suggest that the nonlinear dynamical analysis can provide a useful information for detecting relative changes in brain dynamics, which cannot be detected by conventional linear analysis.