Seventy years since the invention of the averaging technique in Neurophysiology: Tribute to George Duncan Dawson / 70 anos da invenção da técnica de promediação na Neurofisiologia: Tributo a George Duncan Dawson

ABSTRACT In 1951, the physiologist George Duncan Dawson presented his work with the averaging of the signal in the evoked potentials (EPs), opening a new stage in the development of clinical neurophysiology. The authors present aspects of Professor Dawson's biography and a review of his work on the EPs and, mainly, the article reveals the new technique in detail that would allow the growth of the clinical application of the visual, auditory, and somatosensory EPs.

RESUMO Em 1951 o fisiologista George Duncan Dawson apresentou seu trabalho com a promediação de sinal nos potenciais evocados, abrindo uma nova etapa no desenvolvimento da neurofisiologia clínica. Os autores apresentam aspectos da biografia do professor Dawson e uma revisão de seus trabalhos sobre os potenciais evocados, principalmente do artigo que mostrava a nova técnica, que viria a permitir o crescimento da aplicação clínica dos potenciais evocados visual, auditivo e somatossensitivo.

Seventy years since the invention of the averaging technique in Neurophysiology: Tribute to George Duncan Dawson.

OBJECTIVE: In 1951, the physiologist George Duncan Dawson presented his work with the averaging of the signal in the evoked potentials (EPs), opening a new stage in the development of clinical neurophysiology. The authors present aspects of Professor Dawson's biography and a review of his work on the EPs and, mainly, the article reveals the new technique in detail that would allow the growth of the clinical application of the visual, auditory, and somatosensory EPs.

Importance of access to epilepsy monitoring units during the COVID-19 pandemic: Consensus statement of the International League against epilepsy and the International Federation of Clinical Neurophysiology.

Restructuring of healthcare services during the COVID-19 pandemic has led to lockdown of Epilepsy Monitoring Units (EMUs) in many hospitals. The ad-hoc taskforce of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) highlights the detrimental effect of postponing video-EEG monitoring of patients with epilepsy and other paroxysmal events. The taskforce calls for action to continue functioning of Epilepsy Monitoring Units during emergency situations, such as the COVID-19 pandemic. Long-term video-EEG monitoring is an essential diagnostic service. Access to video-EEG monitoring of the patients in the EMUs must be given high priority. Patients should be screened for COVID-19, before admission, according to the local regulations. Local policies for COVID-19 infection control should be adhered to during the video-EEG monitoring. In cases of differential diagnosis where reduction of antiseizure medication is not required, consider home video-EEG monitoring as an alternative in selected patients.

Best Practices in Facial Nerve Monitoring.

OBJECTIVES/HYPOTHESIS: Facial nerve monitoring (FNM) has evolved into a widely used adjunct for many surgical procedures along the course of the facial nerve. Even though majority opinion holds that FNM reduces the incidence of iatrogenic nerve injury, there are few if any studies yielding high-level evidence and no practice guidelines on which clinicians can rely. Instead, a review of the literature and medicolegal cases reveals significant variations in methodology, training, and clinical indications. STUDY DESIGN: Literature review and expert opinion. METHODS: Given the lack of standard references to serve as a resource for FNM, we assembled a multidisciplinary group of experts representing more than a century of combined monitoring experience to synthesize the literature and provide a rational basis to improve the quality of patient care during FNM. RESULTS: Over the years, two models of monitoring have become well-established: 1) monitoring by the surgeon using a stand-alone device that provides auditory feedback of facial electromyography directly to the surgeon, and 2) a team, typically consisting of surgeon, technologist, and interpreting neurophysiologist. Regardless of the setting and the number of people involved, the reliability of monitoring depends on the integration of proper technical performance, accurate interpretation of responses, and their timely application to the surgical procedure. We describe critical steps in the technical set-up and provide a basis for context-appropriate interpretation and troubleshooting of recorded signals. CONCLUSIONS: We trust this initial attempt to describe best practices will serve as a basis for improving the quality of patient care while reducing inappropriate variations. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:S1-S42, 2021.

A new assessment to monitor student performance in introductory neurophysiology: Electrochemical Gradients Assessment Device.

The basis for understanding neurophysiology is understanding ion movement across cell membranes. Students in introductory courses recognize ion concentration gradients as a driving force for ion movement but struggle to simultaneously account for electrical charge gradients. We developed a 17-multiple-choice item assessment of students' understanding of electrochemical gradients and resistance in neurophysiology, the Electrochemical Gradients Assessment Device (EGAD). We investigated the internal evidence validity of the assessment by analyzing item characteristic curves of score probability and student ability for each question, and a Wright map of student scores and ability. We used linear mixed-effect regression to test student performance and ability. Our assessment discriminated students with average ability (weighted likelihood estimate: -2 to 1.5 Θ); however, it was not as effective at discriminating students at the highest ability (weighted likelihood estimate: >2 Θ). We determined the assessment could capture changes in both assessment scores (model r2 = 0.51, P < 0.001, n = 444) and ability estimates (model r2 = 0.47, P < 0.001, n = 444) after a simulation-based laboratory and course instruction for 222 students. Differential item function analysis determined that each item on the assessment performed equitably for all students, regardless of gender, race/ethnicity, or economic status. Overall, we found that men scored higher (r2 = 0.51, P = 0.014, n = 444) and had higher ability scores (P = 0.003) on the EGAD assessment. Caucasian students of both genders were positively correlated with score (r2 = 0.51, P < 0.001, n = 444) and ability (r2 = 0.47, P < 0.001, n = 444). Based on the evidence gathered through our analyses, the scores obtained from the EGAD can distinguish between levels of content knowledge on neurophysiology principles for students in introductory physiology courses.

Real-time particle filtering and smoothing algorithms for detecting abrupt changes in neural ensemble spike activity.

Sequential change-point detection from time series data is a common problem in many neuroscience applications, such as seizure detection, anomaly detection, and pain detection. In our previous work (Chen Z, Zhang Q, Tong AP, Manders TR, Wang J. J Neural Eng 14: 036023, 2017), we developed a latent state-space model, known as the Poisson linear dynamical system, for detecting abrupt changes in neuronal ensemble spike activity. In online brain-machine interface (BMI) applications, a recursive filtering algorithm is used to track the changes in the latent variable. However, previous methods have been restricted to Gaussian dynamical noise and have used Gaussian approximation for the Poisson likelihood. To improve the detection speed, we introduce non-Gaussian dynamical noise for modeling a stochastic jump process in the latent state space. To efficiently estimate the state posterior that accommodates non-Gaussian noise and non-Gaussian likelihood, we propose particle filtering and smoothing algorithms for the change-point detection problem. To speed up the computation, we implement the proposed particle filtering algorithms using advanced graphics processing unit computing technology. We validate our algorithms, using both computer simulations and experimental data for acute pain detection. Finally, we discuss several important practical issues in the context of real-time closed-loop BMI applications. NEW & NOTEWORTHY Sequential change-point detection is an important problem in closed-loop neuroscience experiments. This study proposes novel sequential Monte Carlo methods to quickly detect the onset and offset of a stochastic jump process that drives the population spike activity. This new approach is robust with respect to spike sorting noise and varying levels of signal-to-noise ratio. The GPU implementation of the computational algorithm allows for parallel processing in real time.

Preliminary methods for wearable neuro-vascular assessment with non-invasive, active sensing.

In this study, a non-invasive and active sensing scheme that is ultimately aimed to be integrated in a wearable system for neuro-vascular health assessment is presented with preliminary results. With this system, vascular tone is modulated by local heating and cooling of the palm, and the resulting changes in local hemodynamics are monitored via impedance plethysmography (IPG) and photoplethysmography (PPG) sensors interfaced with custom analog electronics. Proof-of-concept measurements were conducted on three subjects using hot packs/ice bags to modulate the palmar skin temperature. From ensemble averaged and smoothed versions of pulsatile IPG and PPG signals, the effects of local changes in skin temperature on a series of parameters associated with neuro-vascular mechanisms (heart rate, blood volume, blood flow rate, blood volume pulse inflection point area ratio, and local pulse transit time) have been observed. The promising experimental results suggest that, with different active temperature modulation schemes (consisting of heating/cooling cycles covering different temperature ranges at different rates), it would be possible to enhance the depth and specificity of the information associated with neuro-vascular health by using biosensors that can fit inside a wearable device (such as a sleeve). This study sets the foundation for future studies on designing and testing such a wearable neuro-vascular health assessment system employing active sensing.

Quantitative assessment of multiple sclerosis using inertial sensors and the TUG test.

Multiple sclerosis (MS) is a progressive neurological disorder affecting between 2 and 2.5 million people globally. Tests of mobility form part of clinical assessments of MS. Quantitative assessment of mobility using inertial sensors has the potential to provide objective, longitudinal monitoring of disease progression in patients with MS. The mobility of 21 patients (aged 25-59 years, 8 M, 13 F), diagnosed with relapsing-remitting MS was assessed using the Timed up and Go (TUG) test, while patients wore shank-mounted inertial sensors. This exploratory, cross-sectional study aimed to examine the reliability of quantitative measures derived from inertial sensors during the TUG test, in patients with MS. Furthermore, we aimed to determine if disease status (as measured by the Multiple Sclerosis Impact Scale (MSIS-29) and the Expanded Disability Status Score (EDSS)) can be predicted by assessment using a TUG test and inertial sensors. Reliability analysis showed that 32 of 52 inertial sensors parameters obtained during the TUG showed excellent intrasession reliability, while 11 of 52 showed moderate reliability. Using the inertial sensors parameters, regression models of the EDSS and MSIS-29 scales were derived using the elastic net procedure. Using cross validation, an elastic net regularized regression model of MSIS yielded a mean square error (MSE) of 334.6 with 25 degrees of freedom (DoF). Similarly, an elastic net regularized regression model of EDSS yielded a cross-validated MSE of 1.5 with 6 DoF. Results suggest that inertial sensor parameters derived from MS patients while completing the TUG test are reliable and may have utility in assessing disease state as measured using EDSS and MSIS.

[Evaluation and quantification of spasticity: a review of the clinical, biomechanical and neurophysiological methods]. / Valoracion y cuantificacion de la espasticidad: revision de los metodos clinicos, biomecanicos y neurofisiologicos.

INTRODUCTION: Spasticity is a sensory-motor disorder that affects about 85% of the patients with multiple sclerosis and between 65-78% of those with spinal cord injury, among other neurological conditions. Although hypertonia is generally easy to recognise clinically, quantifying it is quite a complex matter. The large number of clinical scales that exist and their subjectivity, the discrepancy between the spasticity perceived by the patient and the clinical measurement, as well as the lack of a general correlation between the neurophysiological measures and hypertonia, all make it especially difficult, in methodological terms, to perform a valid, reliable measurement of the degree of spasticity presented by the patient. AIMS: To review the main methods of evaluating spasticity published in the scientific literature and to carry out a description and critical analysis of their advantages, shortcomings and metric properties in patients with a neurological pathology. DEVELOPMENT: The different methods described for evaluating spasticity are reviewed and classified in three broad groups, namely, clinical scales specifically designed for such a purpose, biomechanical tests and neurophysiological methods. CONCLUSIONS: There is little agreement on the definition of spasticity and the need for the evaluators' training and experience when it comes to evaluating it. We recommend using a combination of the different evaluation instruments, such as the scales, biomechanical methods and neurophysiological measures reported in this study, to carry out a general diagnosis of the degree of spasticity present in the patient.

Isomap approach to EEG-based assessment of neurophysiological changes during anesthesia.

Increasing concentrations of anesthetics in the blood induce a continuum of neurophysiological changes, which reflect on the electroencephalogram (EEG). EEG-based depth of anesthesia assessment requires that the signal samples are correctly associated with the neurophysiological changes occurring at different anesthetic levels. A novel method is presented to estimate the phase of the continuum using the feature data extracted from EEG. The feature data calculated from EEG sequences corresponding to continuously deepening anesthesia are considered to form a one-dimensional nonlinear manifold in the multidimensional feature space. Utilizing a recently proposed algorithm, Isomap, the dimensionality of the feature data is reduced to achieve a one-dimensional embedding representing this manifold and thereby the continuum of neurophysiological changes during induction of anesthesia. The Isomap-based estimation is validated with data recorded from nine patients during induction of propofol anesthesia. The proposed method provides a novel approach to assess neurophysiological changes during anesthesia and offers potential for the development of more advanced systems for the depth of anesthesia monitoring.

A 5-year prospective assessment of advanced Parkinson disease patients treated with subcutaneous apomorphine infusion or deep brain stimulation.

Prospective comparative long-term data on the effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) and continuous subcutaneous infusion of apomorphine (CSAI) in patients with advanced Parkinson disease (PD) are lacking. We report 5-year follow-up of 25 PD patients treated with either STN-DBS (n = 13) or CSAI (n = 12) who fulfilled CAPSIT-PD criteria. Cohorts were matched for disease duration and severity of motor complications. Baseline clinical and neuropsychological status did not differ among cohorts. Patients were assessed with the UPDRS, MMSE, HAMD-17 and Neuropsychiatric Inventory (NPI).Twelve subjects reached the 5-year follow-up with STN-DBS (one was lost at follow-up) versus two in the CSAI cohort. Drop-outs with CSAI were due to subcutaneous nodules (n = 2), insufficient control of motor fluctuations and dyskinesia (n = 4), death for unrelated reasons (n = 3) and one was lost at follow-up. Average apomorphine dose at last visit was 83.4 ± 19.2 mg/day and average treatment duration was 30 months. At 1-year as well as at last follow-up (intention-to-treat analysis), both therapies decreased daily off-time but only STN-DBS reduced dyskinesia duration and severity. Decrement of medications was greater with STN-DBS. There was a significant worsening of NPI after STN-DBS, primarily because four subjects developed apathy.

A bio-friendly and economical technique for chronic implantation of multiple microelectrode arrays.

Many neurophysiological experiments on rodents and non-human primates involve the implantation of more than one multi-electrode array to record from many regions of the brain. So called 'floating' microelectrode arrays are implanted in cortical regions of interest and are coupled via a flexible cable to their connectors which are fixed to the skull by a cement cap or a titanium pedestal, such as the Cereport system, which has been approved for human use. The use of bone cement has several disadvantages including the creation of infection prone areas at the interface with the skull and surrounding skin. Alternatively, the more biocompatible Cereport has a limited carrying capacity and is far more expensive. In this paper, we describe a new implantation technique, which combines the biocompatibility of titanium, a high carrying capacity with a minimal skull footprint, and a decreased chance of infection, all in a relatively inexpensive package. This technique utilizes an in-house fabricated 'Nesting Platform' (NP), mounted on a titanium headpost to hold multiple connectors above the skin, making the headpost the only transcutaneous object. The use of delrin, a durable, lightweight and easily machinable material, allows easy customization of the NP for a wide variety of floating electrodes and their connectors. The ultimate result is a longer survival time with superior neural recordings that can potentially last longer than with traditional implantation techniques.

Low-cost, high-fidelity, adaptive cancellation of periodic 60 Hz noise.

A common method to eliminate unwanted power line interference in neurobiology laboratories where sensitive electronic signals are measured is with a notch filter. However a fixed-frequency notch filter cannot remove all power line noise contamination since inherent frequency and phase variations exist in the contaminating signal. One way to overcome the limitations of a fixed-frequency notch filter is with adaptive noise cancellation. Adaptive noise cancellation is an active approach that uses feedback to create a signal that when summed with the contaminated signal destructively interferes with the noise component leaving only the desired signal. We have implemented an optimized least mean square adaptive noise cancellation algorithm on a low-cost 16 MHz, 8-bit microcontroller to adaptively cancel periodic 60 Hz noise. In our implementation, we achieve between 20 and 25 dB of cancellation of the fundamental 60 Hz noise component.

Mental states as macrostates emerging from brain electrical dynamics.

Psychophysiological correlations form the basis for different medical and scientific disciplines, but the nature of this relation has not yet been fully understood. One conceptual option is to understand the mental as "emerging" from neural processes in the specific sense that psychology and physiology provide two different descriptions of the same system. Stating these descriptions in terms of coarser- and finer-grained system states (macro- and microstates), the two descriptions may be equally adequate if the coarse-graining preserves the possibility to obtain a dynamical rule for the system. To test the empirical viability of our approach, we describe an algorithm to obtain a specific form of such a coarse-graining from data, and illustrate its operation using a simulated dynamical system. We then apply the method to an electroencephalographic recording, where we are able to identify macrostates from the physiological data that correspond to mental states of the subject.

Microneurographic assessment of C-fibre function in aged healthy subjects.

Physiological changes in the nervous system occur with ageing. Both a decline of function and a decrease in the number of C-fibres in the skin have been reported for healthy aged subjects. With the use of microneurographic recordings from single C-fibres in humans we have compared the sensory and axonal properties of these neurones in young and aged healthy subjects. A total of 146 C-fibres were recorded from the common peroneal nerve in young subjects (mean age 24.7 years) and 230 C-fibres were recorded in aged subjects (mean age 56.2 years). In aged subjects, changes were found in the composition of the C-fibre population and in sensory and axonal properties. The relative incidence of afferent to efferent C-fibres was relatively constant independent of the age of subjects. The ratio of mechano-responsive to mechano-insensitive nociceptors was approximately 8 : 2 in the young controls while in aged subjects it was 7 : 3. In aged subjects 13% of the fibres showed atypical discharge characteristics, while this was not observed in young subjects. Spontaneous activity, sensitization and loss of sensory function were found regularly. Changes in functions of the conductile membrane were also observed in fibres from aged subjects. The degree of activity-dependent conduction velocity slowing in response to high frequency stimulation (2 Hz) was more pronounced, while the normalization of conduction velocity subsequent to high frequency stimulation was protracted. We found that both sensitization and desensitization or degeneration of afferent C-fibres occur with age, but are still rare compared to patients with neuropathy. The changes in the axonal properties of C-fibres in aged subjects are compatible with hypoexcitability of the fibres. These findings are important for the understanding and differential diagnoses regarding pathological processes and normal ageing.

Spike sorting with hidden Markov models.

The ability to detect and sort overlapping spike waveforms in extracellular recordings is key to studies of neural coding at high spatial and temporal resolution. Most spike-sorting algorithms are based on initial spike detection (e.g. by a voltage threshold) and subsequent waveform classification. Much effort has been devoted to the clustering step, despite the fact that conservative spike detection is notoriously difficult in low signal-to-noise conditions and often entails many spike misses. Hidden Markov models (HMMs) can serve as generative models for continuous extracellular data records. These models naturally combine the spike detection and classification steps into a single computational procedure. They unify the advantages of independent component analysis (ICA) and overlap-search algorithms because they blindly perform source separation even in cases where several neurons are recorded on a single electrode. We apply HMMs to artificially generated data and to extracellular signals recorded with glass electrodes. We show that in comparison with state-of-art spike-sorting algorithms, HMM-based spike sorting exhibits a comparable number of false positive spike classifications but many fewer spike misses.

Iron states and cognitive abilities in young adults: neuropsychological and neurophysiological assessment.

Many investigators found that iron deficiency anemia (IDA) had a great influence on cognitive functions in infants and children. However, studies of such topic in adults are few and controversial. We prospectively assessed the possible influence of IDA and iron supplementation (for 3 months) on cognitive function and intelligence of 28 young adults with IDA. We used group of hematological, cognitive, neurophysiological tests for assessment including: mini-mental state examination (MMSE), Wechsler memory scale-revised (WMS-R), Wechsler adult intelligence scale-revised (WAIS-R), event-related potentials (ERPs), and electroencephalography (EEG). Compared to controls, patients demonstrated lower scores of different cognitive tests (MMSE, WMS-R, and WAIS-R), which showed significant improvement after treatment. Prolongation of ERPs latencies (N200 and P300) and reduction in their amplitudes (P200 and P300) were identified with significant increase in amplitude occurred after treatment. EEG abnormalities were observed in 55% of patients which showed improvement in 35% after treatment. Positive correlation was identified before and after treatment between hemoglobin levels and MMSE (P=0.01, 0.05), total verbal (P=0.04) and performance (P=0.05, 0.04) IQ scores. Negative correlation was identified between before and after treatment between P300 latency and total IQ of WAIS-R (P=0.03, 0.008) and hemoglobin level (P=0.4, 0.01). Positive correlation was found before and after treatment between P300 amplitude and total IQ (P=0.028, 0.01) and serum iron (P=0.01, 0.001). In conclusion, IDA is a significant factor in cognitive performance in adult population, which can be partially reversed by treatment.