Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis

This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these domains. The event related multiple EEG recordings of the chronic pain patients and non-pain controls with somatosensory stimuli (pain, random pain, touch, random touch) are analyzed. Multiple linear regression (MLR) is applied to describe the effects of aging on the frequency response differences between patients and controls. The results show that the somatosensory cortical responses occurred around 250 ms in both groups. In the frequency domain, the neural response frequency in the pain group (around 4 Hz) was less than that in the control group (around 5.5 Hz) under the somatosensory stimuli. In the channel domain, cortical activation was predominant in the frontal region for the chronic pain group and in the central region for controls. The indices of active ratios were statistical significant between the two groups in the frontal and central regions. These findings demonstrate that the PARAFAC is an interesting method to understanding the pathophysiological characteristics of chronic pain

Anesthetic action on the transmission delay between cortex and thalamus explains the beta-buzz observed under propofol anesthesia

In recent years, more and more surgeries under general anesthesia have been performed with the assistance of electroencephalogram (EEG) monitors. An increase in anesthetic concentration leads to characteristic changes in the power spectra of the EEG. Although tracking the anesthetic-induced changes in EEG rhythms can be employed to estimate the depth of anesthesia, their precise underlying mechanisms are still unknown. A prominent feature in the EEG of some patients is the emergence of a strong power peak in the β–frequency band, which moves to the α–frequency band while increasing the anesthetic concentration. This feature is called the beta-buzz. In the present study, we use a thalamo-cortical neural population feedback model to reproduce observed characteristic features in frontal EEG power obtained experimentally during propofol general anesthesia, such as this beta-buzz. First, we find that the spectral power peak in the α– and δ–frequency ranges depend on the decay rate constant of excitatory and inhibitory synapses, but the anesthetic action on synapses does not explain the beta-buzz. Moreover, considering the action of propofol on the transmission delay between cortex and thalamus, the model reveals that the beta-buzz may result from a prolongation of the transmission delay by increasing propofol concentration. A corresponding relationship between transmission delay and anesthetic blood concentration is derived. Finally, an analytical stability study demonstrates that increasing propofol concentration moves the systems resting state towards its stability threshold

Continuing professional development module : An updated introduction to electroencephalogram-based brain monitoring during intended general anesthesia.

The electroencephalogram (EEG) provides a reliable reflection of the brain's electrical state, so it can reassure us that the anesthetic agents are actually reaching the patient's brain, and are having the desired effect. In most patients, the EEG changes somewhat predictably in response to propofol and volatile agents, so a frontal EEG channel can guide avoidance of insufficient and excessive administration of general anesthesia. Persistent alpha-spindles (around 10 Hz) phase-amplitude coupled with slow delta waves (around 1 Hz) are commonly seen during an "appropriate hypnotic state of general anesthesia". Such patterns can be appreciated from the EEG waveform or from the spectrogram (a colour-coded display of how the power in the various EEG frequencies changes with time). Nevertheless, there are exceptions to this. For example, administration of ketamine and nitrous oxide is generally not associated with the aforementioned alpha-spindle coupled with delta wave pattern. Also, some patients, including older adults and those with neurodegenerative disorders, are less predisposed to generate a strong electroencephalographic "alpha-spindle" pattern during general anesthesia. There might also be some rare instances when the frontal EEG shows a pattern suggestive of general anesthesia, while the patient has some awareness and is able to follow simple commands, albeit this is typically without obvious distress or memory formation. Thus, the frontal EEG alone, as currently analyzed, is an imperfect but clinically useful mirror, and more scientific insights will be needed before we can claim to have a reliable readout of brain "function" during general anesthesia

Comment on Mankowska et al. Critical Flicker Fusion Frequency: A Narrative Review. Medicina 2021, 57, 1096

We have read with great interest the review by Mankowska et al. [...

Determination of Krogh Coefficient for Oxygen Consumption Measurement from Thin Slices of Rodent Cortical Tissue Using a Fick’s Law Model of Diffusion

To investigate the impact of experimental interventions on living biological tissue, ex vivo rodent brain slices are often used as a more controllable alternative to a live animal model. However, for meaningful results, the biological sample must be known to be healthy and viable. One of the gold-standard approaches to identifying tissue viability status is to measure the rate of tissue oxygen consumption under specific controlled conditions. Here, we work with thin (400 μm) slices of mouse cortical brain tissue which are sustained by a steady flow of oxygenated artificial cerebralspinal fluid (aCSF) at room temperature. To quantify tissue oxygen consumption (Q), we measure oxygen partial pressure (pO2) as a function of probe depth. The curvature of the obtained parabolic (or parabola-like) pO2 profiles can be used to extract Q, providing one knows the Krogh coefficient Kt, for the tissue. The oxygen trends are well described by a Fick’s law diffusion–consumption model developed by Ivanova and Simeonov, and expressed in terms of ratio (Q/K), being the rate of oxygen consumption in tissue divided by the Krogh coefficient (oxygen diffusivity × oxygen solubility) for tissue. If the fluid immediately adjacent to the tissue can be assumed to be stationary (i.e., nonflowing), one may invoke conservation of oxygen flux K·(∂P/∂x) across the interface to deduce (Kt/Kf), the ratio of Krogh coefficients for tissue and fluid. Using published interpolation formulas for the effect of salt content and temperature on oxygen diffusivity and solubility for pure water, we estimate Kf, the Krogh coefficient for aCSF, and hence deduce the Kt coefficient for tissue. We distinguish experimental uncertainty from natural biological variability by using pairs of repeated profiles at the same tissue location. We report a dimensionless Krogh ratio (Kt/Kf)=0.562±0.088 (mean ± SD), corresponding to a Krogh coefficient Kt=(1.29±0.21)×10−14 mol/(m·s·Pa) for mouse cortical tissue at room temperature, but acknowledge the experimental limitation of being unable to verify that the fluid boundary layer is truly stationary. We compare our results with those reported in the literature, and comment on the challenges and ambiguities caused by the extensive use of ‘biologically convenient’ non-SI units for tissue Krogh coefficient

Does hyperbaric oxygen cause narcosis or hyperexcitability? A quantitative EEG analysis

Abstract Divers breathe higher partial pressures of oxygen at depth than at the surface. The literature and diving community are divided on whether or not oxygen is narcotic. Conversely, hyperbaric oxygen may induce dose‐dependent cerebral hyperexcitability. This study evaluated whether hyperbaric oxygen causes similar narcotic effects to nitrogen, and investigated oxygen's hyperexcitability effect. Twelve human participants breathed “normobaric” air and 100% oxygen, and “hyperbaric” 100% oxygen at 142 and 284 kPa, while psychometric performance, electroencephalography (EEG), and task load perception were measured. EEG was analyzed with functional connectivity and temporal complexity algorithms. The spatial functional connectivity, estimated using mutual information, was summarized with the global efficiency network measure. Temporal complexity was calculated with a “default‐mode‐network (DMN) complexity” algorithm. Hyperbaric oxygen‐breathing caused no change in EEG global efficiency or in the psychometric test. However, oxygen caused a significant reduction of DMN complexity and a reduction in task load perception. Hyperbaric oxygen did not cause the same changes in EEG global efficiency seen with hyperbaric air, which likely related to a narcotic effect of nitrogen. Hyperbaric oxygen seemed to disturb the time evolution of EEG patterns that could be taken as evidence of early oxygen‐induced cortical hyperexcitability. These findings suggest that hyperbaric oxygen is not narcotic and will help inform divers' decisions on suitable gas mixtures