Changes in measures of consciousness during anaesthesia of one hemisphere (Wada test)

Exploring effects of anesthesia on complexity, differentiation, and integrated information in rat EEG

To investigate mechanisms underlying loss of consciousness, it is important to extend methods established in humans to rodents as well. Perturbational complexity index (PCI) is a promising metric of "capacity for consciousness" and is based on a perturbational approach that allows inferring a system's capacity for causal integration and differentiation of information. These properties have been proposed as necessary for conscious systems. Measures based on spontaneous electroencephalography recordings, however, may be more practical for certain clinical purposes and may better reflect ongoing dynamics. Here, we compare PCI (using electrical stimulation for perturbing cortical activity) to several spontaneous electroencephalography-based measures of signal diversity and integrated information in rats undergoing propofol, sevoflurane, and ketamine anesthesia. We find that, along with PCI, the spontaneous electroencephalography-based measures, Lempel-Ziv complexity (LZ) and geometric integrated information (ΦG), were best able to distinguish between awake and propofol and sevoflurane anesthesia. However, PCI was anti-correlated with spontaneous measures of integrated information, which generally increased during propofol and sevoflurane anesthesia, contrary to expectations. Together with an observed divergence in network properties estimated from directed functional connectivity (current results) and effective connectivity (earlier results), the perturbation-based results seem to suggest that anesthesia disrupts global cortico-cortical information transfer, whereas spontaneous activity suggests the opposite. We speculate that these seemingly diverging results may be because of suppressed encoding specificity of information or driving subcortical projections from, e.g., the thalamus. We conclude that certain perturbation-based measures (PCI) and spontaneous measures (LZ and ΦG) may be complementary and mutually informative when studying altered states of consciousness.

Super-selective Wada test for pre-surgical leg motor function assessment: A case report

INTRODUCTION

Wada test is well-known to assess lateralization of memory and language functions; however, super-selective Wada (ss-Wada) to evaluate motor leg function is rare. We present a ss-Wada test within the anterior cerebral artery (ACA) to assess the motor function of the leg.

METHODS

Retrospective chart review.

RESULTS

Comprehensive phase-I/II surgical evaluation revealed an ictal focus around the left post-central gyrus with immediate involvement around the left para-central regions. To avoid potential right leg motor dysfunction with the surgery, the patient underwent a ss-Wada procedure. Angiography revealed bilateral ACAs were supplied by the left A1 segment. Super-selective microcatheter injection of amobarbital into the left ACA was performed to avoid cross-filling the contralateral ACA. The ss-Wada test confirmed no right leg motor impairment. Afterward, a craniotomy with direct cortical stimulation confirmed that the left-sided ictal/peri-ictal zone had no clear leg motor function. The patient underwent disconnection of that region and remained seizure-free at 10-month post-op follow-up without any motor or sensory deficits in the right limbs.

CONCLUSION

This case demonstrates the proof of concept for ss-Wada in assessing lower extremity motor function. The ss-Wada procedure accurately predicted no motor deficits in the right leg, consistent with preserved motor function post-surgery.

Support-vector classification of low-dose nitrous oxide administration with multi-channel EEG power spectra

Support-vector machines (SVMs) can potentially improve patient monitoring during nitrous oxide anaesthesia. By elucidating the effects of low-dose nitrous oxide on the power spectra of multi-channel EEG recordings, we quantified the degree to which these effects generalise across participants. In this single-blind, cross-over study, 32-channel EEG was recorded from 12 healthy participants exposed to 0, 20, 30 and 40% end-tidal nitrous oxide. Features of the delta-, theta-, alpha- and beta-band power were used within a 12-fold, participant-wise cross-validation framework to train and test two SVMs: (1) binary SVM classifying EEG during 0 or 40% exposure (chance = 50%); (2) multi-class SVM classifying EEG during 0, 20, 30 or 40% exposure (chance = 25%). Both the binary (accuracy 92%) and the multi-class (accuracy 52%) SVMs classified EEG recordings at rates significantly better than chance (p < 0.001 and p = 0.01, respectively). To determine the relative importance of frequency band features for classification accuracy, we systematically removed features before re-training and re-testing the SVMs. This showed the relative importance of decreased delta power and the frontal region. SVM classification identified that the most important effects of nitrous oxide were found in the delta band in the frontal electrodes that was consistent between participants. Furthermore, support-vector classification of nitrous oxide dosage is a promising method that might be used to improve patient monitoring during nitrous oxide anaesthesia.

Laminar evoked responses in mouse somatosensory cortex suggest a special role for deep layers in cortical complexity

It has been suggested that consciousness is closely related to the complexity of the brain. The perturbational complexity index (PCI) has been used in humans and rodents to distinguish conscious from unconscious states based on the global cortical responses (recorded by electroencephalography, EEG) to local cortical stimulation (CS). However, it is unclear how different cortical layers respond to CS and contribute to the resulting intra- and inter-areal cortical connectivity and PCI. A detailed investigation of the local dynamics is needed to understand the basis for PCI. We hypothesized that the complexity level of global cortical responses (PCI) correlates with layer-specific activity and connectivity. We tested this idea by measuring global cortical dynamics and layer-specific activity in the somatosensory cortex (S1) of mice, combining cortical electrical stimulation in deep motor cortex, global electrocorticography (ECoG) and local laminar recordings from layers 1-6 in S1, during wakefulness and general anaesthesia (sevoflurane). We found that the transition from wake to sevoflurane anaesthesia correlated with a drop in both the global and local PCI (PCIst ) values (complexity). This was accompanied by a local decrease in neural firing rate, spike-field coherence and long-range functional connectivity specific to deep layers (L5, L6). Our results suggest that deep cortical layers are mechanistically important for changes in PCI and thereby for changes in the state of consciousness.

Spatial and temporal frequency band changes during infarct induction, infarct progression, and spreading depolarizations in the gyrencephalic brain

Aim

To describe the spatial and temporal electrocorticographic (ECoG) changes after middle cerebral artery occlusion (MCAo), including those caused by spreading depolarization (SD) in the pig brain.

Methods

The left middle cerebral arteries (MCAs) were clipped in six pigs. The clipping procedure lasted between 8 and 12 min, achieving a permanent occlusion (MCAo). Five-contact ECoG stripes were placed bilaterally over the frontoparietal cortices corresponding to the irrigation territory of the MCA and anterior cerebral artery (ACA). ECoG recordings were performed around 24 h: 1 h before and 23 h after the MCAo, and SDs were quantified. Five-minute ECoG signal segments were sampled before, 5 min, and 4, 8, and 12 h after cerebral artery occlusion and before, during, and after the negative direct current shift of the SDs. The power spectrum of the signals was decomposed into delta, theta, alpha, beta, and gamma bands. Descriptive statistics, Wilcoxon matched-pairs signed-rank tests, and Friedman tests were performed.

Results

Electrodes close to the MCAo showed instant decay in all frequency bands and SD onset during the first 5 h. Electrodes far from the MCAo exhibited immediate loss of fast frequencies and progressive decline of slow frequencies with an increased SD incidence between 6 and 14 h. After 8 h, the ACA electrode reported a secondary reduction of all frequency bands except gamma and high SD incidence within 12-17 h. During the SD, all electrodes showed a decline in all frequency bands. After SD passage, frequency band recovery was impaired only in MCA electrodes.

Conclusion

ECoG can identify infarct progression and secondary brain injury. Severe disturbances in all the frequency bands are generated in the cortices where the SDs are passing by.

Developing a robust model to predict depth of anesthesia from single channel EEG signal

Monitoring depth of anaesthesia (DoA) from electroencephalograph (EEG) signals is an ongoing challenge for anaesthesiologists. In this study, we propose an intelligence model that predicts the DoA from a single channel electroencephalograph (EEG) signal. A segmentation technique based on a sliding window is employed to partition EEG signals. Hierarchical dispersion entropy (HDE) is applied to each EEG segment. A set of features is extracted from each EEG segment. The extracted features are investigated using a community graph detection approach (CGDA), and the most relevant features are selected to trace the DoA. The proposed model, based on HDE coupled with CGDA, is evaluated in term of BIS index using several statistical metrics such Q-Q plot, regression, and correlation coefficients. In addition, the proposed model is evaluated against the BIS index in the case of the poor signal quality. The results demonstrated that the proposed model showed an earlier reaction compared with the BIS index when patient’s state transits from deep anaesthesia to moderate anaesthesia in the case of poor signal quality. The highest Pearson correlation coefficient obtained by the proposed is 0.96.

Searching in the wrong place: Might consciousness reside in the brainstem?

Doubtless, the conscious brain integrates masses of information. But declaring that consciousness simply "emerges" when enough has accumulated, doesn't really explain how first person experience is implemented by neurons. Moreover, empirical observations challenge integrated information theory's (IIT) reliance on thalamo-cortical interactions as the information integrator. More likely, the cortex streams processed information to a still-enigmatic consciousness generator, one perhaps located in the brainstem.

Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

A Century Searching for the Neurons Necessary for Wakefulness

Wakefulness is necessary for consciousness, and impaired wakefulness is a symptom of many diseases. The neural circuits that maintain wakefulness remain incompletely understood, as do the mechanisms of impaired consciousness in many patients. In contrast to the influential concept of a diffuse "reticular activating system," the past century of neuroscience research has identified a focal region of the upper brainstem that, when damaged, causes coma. This region contains diverse neuronal populations with different axonal projections, neurotransmitters, and genetic identities. Activating some of these populations promotes wakefulness, but it remains unclear which specific neurons are necessary for sustaining consciousness. In parallel, pharmacological evidence has indicated a role for special neurotransmitters, including hypocretin/orexin, histamine, norepinephrine, serotonin, dopamine, adenosine and acetylcholine. However, genetically targeted experiments have indicated that none of these neurotransmitters or the neurons producing them are individually necessary for maintaining wakefulness. In this review, we emphasize the need to determine the specific subset of brainstem neurons necessary for maintaining arousal. Accomplishing this will enable more precise mapping of wakefulness circuitry, which will be useful in developing therapies for patients with coma and other disorders of arousal.