Aperiodic Activity Research Articles

Globally elevated excitation–inhibition ratio in children with autism spectrum disorder and below-average intelligence

BackgroundAltered neuronal excitation–inhibition (E–I) balance is strongly implicated in ASD. However, it is not known whether the direction and degree of changes in the E–I ratio in individuals with ASD correlates with intellectual disability often associated with this developmental disorder. The spectral slope of the aperiodic 1/f activity reflects the E–I balance at the scale of large neuronal populations and may uncover its putative alternations in individuals with ASD with and without intellectual disability.MethodsHerein, we used magnetoencephalography (MEG) to test whether the 1/f slope would differentiate ASD children with average and below–average (< 85) IQ. MEG was recorded at rest with eyes open/closed in 49 boys with ASD aged 6–15 years with IQ ranging from 54 to 128, and in 49 age-matched typically developing (TD) boys. The cortical source activity was estimated using the beamformer approach and individual brain models. We then extracted the 1/f slope by fitting a linear function to the log–log-scale power spectra in the high-frequency range.ResultsThe global 1/f slope averaged over all cortical sources demonstrated high rank-order stability between the two conditions. Consistent with previous research, it was steeper in the eyes-closed than in the eyes-open condition and flattened with age. Regardless of condition, children with ASD and below-average IQ had flatter slopes than either TD or ASD children with average or above-average IQ. These group differences could not be explained by differences in signal-to-noise ratio or periodic (alpha and beta) activity.LimitationsFurther research is needed to find out whether the observed changes in E–I ratios are characteristic of children with below-average IQ of other diagnostic groups.ConclusionsThe atypically flattened spectral slope of aperiodic activity in children with ASD and below-average IQ suggests a shift of the global E–I balance toward hyper-excitation. The spectral slope can provide an accessible noninvasive biomarker of the E–I ratio for making objective judgments about treatment effectiveness in people with ASD and comorbid intellectual disability.

Predicting Math Ability Using Working Memory, Number Sense, and Neurophysiology in Children and Adults.

Previous work has shown relations between domain-general processes, domain-specific processes, and mathematical ability. However, the underlying neurophysiological effects of mathematical ability are less clear. Recent evidence highlighted the potential role of beta oscillations in mathematical ability. Here we investigate whether domain-general (working memory) and domain-specific (number sense) processes mediate the relation between resting-state beta oscillations and mathematical ability, and how this may differ as a function of development (children vs. adults). We compared a traditional analysis method normally used in EEG studies with a more recently developed parameterization method that separates periodic from aperiodic activity. Regardless of methods chosen, we found no support for mediation of working memory and number sense, neither for children nor for adults. However, we found subtle differences between the methods. Additionally, we showed that the traditional EEG analysis method conflates periodic activity with aperiodic activity; in addition, the latter is strongly related to mathematical ability and this relation differs between children and adults. At the cognitive level, our findings do not support previous suggestions of a mediation of working memory and number sense. At the neurophysiological level our findings suggest that aperiodic, rather than periodic, activity is linked to mathematical ability as a function of development.

Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk.

Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36weeks gestation (34.60±2.34weeks). EEG was collected during sleep between 39 and 41weeks postmenstrual age adjusted (40.00±0.42weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34±2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.

Periodic/Aperiodic parameterization of transient oscillations (PAPTO)–Implications for healthy ageing

Two techniques for analyzing human extracranial neurophysiological signals, namely the periodic/aperiodic parameterization of neural power spectra and the transient events framework of oscillatory activity, have recently emerged in the scientific literature. In this work, we integrate these two analysis perspectives to analyze extracranial neurophysiological signals as a series of transient rhythmic events disambiguated from the background aperiodic activity. We call this novel technique the periodic/aperiodic parametrization of transient oscillations (PAPTO). We demonstrate PAPTO by investigating resting-state sensorimotor magnetoencephalography recordings from the Cambridge Center for Ageing and Neuroscience cross-sectional study on healthy ageing (n = 600, ages 18–88). We show that PAPTO is more sensitive to neocortical transient beta rhythms compared to more conventional transient event detection algorithms and captures more variance in the resting-state occurrence rate of beta events across participants. The improved sensitivity of PAPTO reveals that the beta occurrence rate almost doubles over the adult lifespan which we discuss in terms of thalamocortical beta generation in the somatosensory cortex and the age-related decline of sensory perception.

Longitudinal age- and sex-related change in background aperiodic activity during early adolescence

Aperiodic activity contains important and meaningful physiological information that has been shown to dynamically change with age. However, no longitudinal studies have examined its development during early-to-mid adolescence. The current study closes this gap by investigating age- and sex-related longitudinal change in aperiodic activity across early-to-mid adolescence (N = 186; 54.3% female). Participants completed a resting state task and a Flanker task while EEG was record at age 13 years and again at age 15 years. Across different tasks and two time points, we observed significant age-related reductions in aperiodic offset and exponent. In addition, we observed significant sex-related differences in the aperiodic offset and exponent over time. We did not find any significant correlation between aperiodic activity and behavioral measures, nor did we find any significant condition-dependent change in aperiodic activity during the Flanker task. However, we did observe significant correlations between aperiodic activity across tasks and over time, suggesting that aperiodic activity may demonstrate stable trait-like characteristics. Collectively, these results may suggest a developmental parallelism between decreases in aperiodic components alongside adolescent brain development during this period; changes to cortical and subcortical brain structure and organization during early adolescence may have been responsible for the observed sex-related effects.

Cortical correlation structure of aperiodic neuronal population activity

Electrophysiological population signals contain oscillatory and non-oscillatory aperiodic (1/frequency-like) components. So far research has largely focused on oscillatory activity, and only recently, interest in aperiodic population activity has gained momentum. Accordingly, while the cortical correlation structure of oscillatory population activity has been characterized, little is known about the correlation of aperiodic neuronal activity. To address this, we investigated aperiodic neuronal population activity in the human brain using resting-state magnetoencephalography (MEG). We combined source-analysis, signal orthogonalization and irregular-resampling auto-spectral analysis (IRASA) to systematically characterize the cortical distribution and correlation of aperiodic neuronal activity. We found that aperiodic population activity is robustly correlated across the cortex and that this correlation is spatially well structured. Furthermore, we found that the cortical correlation structure of aperiodic activity is similar but distinct from the correlation structure of oscillatory neuronal activity. Anterior cortical regions showed the strongest differences between oscillatory and aperiodic correlation patterns. Our results suggest that correlations of aperiodic population activity serve as robust markers of cortical network interactions. Furthermore, our results show that aperiodic and oscillatory signal components provide non-redundant information about large-scale neuronal correlations. This may reflect at least partly distinct neuronal mechanisms underlying and reflected by oscillatory and aperiodic neuronal population activity.

P058 Neural aperiodic activity as a novel objective measure of daytime somnolence

Abstract Background Current assessment of excessive daytime somnolence (EDS) requires subjective measurements like the Epworth Sleepiness Scale (ESS), and/or resource heavy sleep laboratory investigations. Electroencephalographic (EEG) measures index intrinsic properties of the central nervous system. One such component is aperiodic neural activity which is thought to reflect excitation/inhibition ratios of neural populations and is altered in various states of consciousness. From this perspective, resting-state aperiodic activity may be a potential biomarker for hypersomnolence. We aim to analyse retrospective EEG data from patients who underwent a Multiple Sleep Latency Test (MSLT) and determine if aperiodic activity is predictive of subjective and objective measures of EDS. Methods Participants having undergone laboratory polysomnogram (PSG) and next day MSLT will be grouped into those with and without sleepiness (mean sleep latency (MSL) of &amp;lt; 8min and &amp;gt; 10min respectively). Forty patients in each group (n=80) will be assessed. The primary objective is to compare the aperiodic slope between these groups, and secondary objectives comparing aperiodic activity with ESS and time of day. Data will be analysed using linear mixed-effect models. Simple linear regressions will be performed between the aperiodic slope and MSL and ESS, with R2 values used to estimate of effect size. Progress: Formal ethics approval has been submitted and is pending. Intended Outcome and Impact In this exploratory study we hypothesise that EDS is associated with a lower aperiodic exponent/flatter slope, and hope to provoke further investigation of this metric as a novel biomarker for sleepiness.

Increased scale-free and aperiodic neural activity during sensorimotor integration-a novel facet in Tourette syndrome.

Tourette syndrome is a common neurodevelopmental disorder defined by multiple motor and phonic tics. Tics in Tourette syndrome resemble spontaneously occurring movements in healthy controls and are therefore sometimes difficult to distinguish from these. Tics may in fact be mis-interpreted as a meaningful action, i.e. a signal with social content, whereas they lack such information and could be conceived a surplus of action or ‘motor noise’. These and other considerations have led to a ‘neural noise account’ of Tourette syndrome suggesting that the processing of neural noise and adaptation of the signal-to-noise ratio during information processing is relevant for the understanding of Tourette syndrome. So far, there is no direct evidence for this. Here, we tested the ‘neural noise account’ examining 1/f noise, also called scale-free neural activity as well as aperiodic activity, in n = 74 children, adolescents and adults with Tourette syndrome and n = 74 healthy controls during task performance using EEG data recorded during a sensorimotor integration task. In keeping with results of a previous study in adults with Tourette syndrome, behavioural data confirmed that sensorimotor integration was also stronger in this larger Tourette syndrome cohort underscoring the relevance of perceptual-action processes in this disorder. More importantly, we show that 1/f noise and aperiodic activity during sensorimotor processing is increased in patients with Tourette syndrome supporting the ‘neural noise account’. This implies that asynchronous/aperiodic neural activity during sensorimotor integration is stronger in patients with Tourette syndrome compared to healthy controls, which is probably related to abnormalities of GABAergic and dopaminergic transmission in these patients. Differences in 1/f noise and aperiodic activity between patients with Tourette syndrome and healthy controls were driven by high-frequency oscillations and not lower-frequency activity currently discussed to be important in the pathophysiology of tics. This and the fact that Bayesian statistics showed that there is evidence for the absence of a correlation between neural noise and clinical measures of tics, suggest that increased 1/f noise and aperiodic activity are not directly related to tics but rather represents a novel facet of Tourette syndrome.

Aperiodic sleep networks promote memory consolidation.

Hierarchical synchronization of sleep oscillations establishes communication pathways to support memory reactivation, transfer, and consolidation. From an information-theoretical perspective, oscillations constitute highly structured network states that provide limited information-coding capacity. Recent findings indicate that sleep oscillations occur in transient bursts that are interleaved with aperiodic network states, which were previously considered to be random noise. We argue that aperiodic activity exhibits unique and variable spatiotemporal patterns, providing an ideal information-rich neurophysiological substrate for imprinting new mnemonic patterns onto existing circuits. We discuss novel avenues in conceptualizing and quantifying aperiodic network states during sleep to further understand their relevance and interplay with sleep oscillations in support of memory consolidation.

Methodological considerations for studying neural oscillations.

Neural oscillations are ubiquitous across recording methodologies and species, broadly associated with cognitive tasks, and amenable to computational modelling that investigates neural circuit generating mechanisms and neural population dynamics. Because of this, neural oscillations offer an exciting potential opportunity for linking theory, physiology and mechanisms of cognition. However, despite their prevalence, there are many concerns-new and old-about how our analysis assumptions are violated by known properties of field potential data. For investigations of neural oscillations to be properly interpreted, and ultimately developed into mechanistic theories, it is necessary to carefully consider the underlying assumptions of the methods we employ. Here, we discuss seven methodological considerations for analysing neural oscillations. The considerations are to (1) verify the presence of oscillations, as they may be absent; (2) validate oscillation band definitions, to address variable peak frequencies; (3) account for concurrent non-oscillatory aperiodic activity, which might otherwise confound measures; measure and account for (4) temporal variability and (5) waveform shape of neural oscillations, which are often bursty and/or nonsinusoidal, potentially leading to spurious results; (6) separate spatially overlapping rhythms, which may interfere with each other; and (7) consider the required signal-to-noise ratio for obtaining reliable estimates. For each topic, we provide relevant examples, demonstrate potential errors of interpretation, and offer suggestions to address these issues. We primarily focus on univariate measures, such as power and phase estimates, though we discuss how these issues can propagate to multivariate measures. These considerations and recommendations offer a helpful guide for measuring and interpreting neural oscillations.

Disturbances in Aperiodic Neural Activity During Resting State in Patients With Schizophrenia

Abnormal oscillatory power measured in canonical frequency bands during resting EEG has been observed in schizophrenia, however, recent evidence suggests that aperiodic neural activity may be important to understanding functional brain abnormalities in the disorder. We characterized the frequency composition of aperiodic (i.e., non-oscillatory) EEG activity in patients with schizophrenia (SCZ) and healthy controls (CON) during rest, and determined whether shifts in aperiodic activity reflect aspects of psychiatric symptoms or cognition.

Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity.

Band ratio measures, computed as the ratio of power between two frequency bands, are a common analysis measure in neuroelectrophysiological recordings. Band ratio measures are typically interpreted as reflecting quantitative measures of periodic, or oscillatory, activity. This assumes that the measure reflects relative powers of distinct periodic components that are well captured by predefined frequency ranges. However, electrophysiological signals contain periodic components and a 1/f-like aperiodic component, the latter of which contributes power across all frequencies. Here, we investigate whether band ratio measures truly reflect oscillatory power differences, and/or to what extent ratios may instead reflect other periodic changes, such as in center frequency or bandwidth, and/or aperiodic activity. In simulation, we investigate how band ratio measures relate to changes in multiple spectral features, and show how multiple periodic and aperiodic features influence band ratio measures. We validate these findings in human electroencephalography (EEG) data, comparing band ratio measures to parameterizations of power spectral features and find that multiple disparate features influence ratio measures. For example, the commonly applied θ/β ratio is most reflective of differences in aperiodic activity, and not oscillatory θ or β power. Collectively, we show that periodic and aperiodic features can create the same observed changes in band ratio measures, and that this is inconsistent with their typical interpretations as measures of periodic power. We conclude that band ratio measures are a non-specific measure, conflating multiple possible underlying spectral changes, and recommend explicit parameterization of neural power spectra as a more specific approach.

Exact response time analysis of fixed priority systems based on sporadic servers

Abstract Real-time servers have been widely explored in the scheduling literature to predictably execute aperiodic activities, as well as to allow hierarchical scheduling settings. As they facilitate timing isolation between different software components, there is a renewed interest for the adoption of fixed priority real-time servers in the automotive domain, as a way to implement more efficient reservation mechanisms than TDMA-based methods. In this paper, we focus on the Sporadic Server, which is the only fixed priority server supported by the POSIX standard. Despite its popularity, we realized that only sufficient schedulability conditions exist for real-time systems scheduled with a Sporadic Server. Thus, we develop a formal characterization of an exact response time analysis for fixed priority systems based on Sporadic Servers in a multi-level scheduling setting under preemptive scheduling. We then provide an experimental characterization of the schedulabilty improvement that can be obtained with respect to existing sufficient schedulability tests, proving the effectiveness of the proposed exact analysis.

Mindfulness Meditators Show Enhanced Accuracy and Different Neural Activity During Working Memory

ObjectivesMindfulness meditation has been shown to improve working memory (WM). However, brain activity underpinning these improvements is underexplored. In meditation-naïve individuals, increased fronto-midline theta and parieto-occipital alpha oscillations, and steeper 1/f aperiodic activity during WM correlate with better WM performance. Resting theta and alpha oscillations have been found to differ in meditators, but WM-related oscillations and 1/f aperiodic activity have not been examined. Additionally, WM-related event-related-potentials (ERPs) are modulated by attention, which is enhanced by mindfulness meditation, so these neural measures are candidate explanations for WM improvement in mindfulness meditators.MethodsWe recorded electroencephalography (EEG) from 29 meditation-naïve controls and 29 experienced mindfulness meditators during a Sternberg WM task and compared theta, alpha and 1/f aperiodic activity during the WM delay, and ERPs time-locked to the WM probe.ResultsCompared to controls, meditators demonstrated greater WM accuracy (p = 0.008, Cohen’s d = 0.688), earlier left-temporal ERP responses and a more frontal distribution of activity (FDR-p = 0.0186, η2 = 0.0903), as well as a reduction in overall neural response strength (FDR-p = 0.0098, η2 = 0.1251). A higher proportion of meditators showed theta oscillations during the WM delay, but no other differences in theta, alpha or 1/f aperiodic activity were present.ConclusionsResults suggest that increased WM performance in mindfulness meditators might not result from higher amplitudes of typical WM activity, but instead from an alternative pattern of brain region engagement during WM decision making, allowing more accurate responses with less neural activation (perhaps reflecting increased neural efficiency).

Reflection of the State of Hunger in Impulse Activity of Nose Wing Muscles and Upper Esophageal Sphincter during Search behavior in Rabbits.

Reflection of the state of hunger in impulse activity of nose wing muscles and upper esophageal sphincter muscles was studied in chronic experiments on rabbits subjected to 24-h food deprivation in the absence of locomotion and during search behavior. In the absence of apparent behavioral activity, including sniffing, alai nasi muscles of hungry rabbits constantly generated bursts of action potentials synchronous with breathing, while upper esophageal sphincter muscles exhibited regular aperiodic low-amplitude impulse activity of tonic type. Latent form of food motivation was reflected in the structure of temporal organization of impulse activity of alai nasi muscles in the form of bimodal distribution of interpulse intervals and in temporal structure of impulse activity of upper esophageal sphincter muscles in the form of monomodal distribution. The latent form of food motivation was manifested in the structure of temporal organization of periods of the action potentials burst-like rhythm, generated by alai nasi muscles, in the form of monomodal distribution, characterized by a high degree of dispersion of respiratory cycle periods. In the absence of physical activity hungry animals sporadically exhibited sniffing activity, manifested in the change from the burst-like impulse activity of alai nasi muscles to the single-burst activity type with bimodal distribution of interpulse intervals and monomodal distribution of the burst-like action potentials rhythm periods, the maximum of which was shifted towards lower values, which was the cause of increased respiratory rate. At the same time, the monomodal temporal structure of impulse activity of the upper esophageal sphincter muscles was not changed. With increasing food motivation in the process of search behavior temporal structure of periods of the burst-like action potentials rhythm, generated by alai nasi muscles, became similar to that observed during sniffing, not accompanied by animal's locomotion, which is typical for the increased respiratory rhythm frequency. Increased hunger motivation was reflected in the temporal structure of impulse activity of upper esophageal sphincter muscles in the form of a shift to lower values of the maximum of monomodal distribution of interpulse intervals on the histogram, resulting in higher impulse activity frequency. The simultaneous increase in the frequency of action potentials bursts generation by alai nasi muscles and regular impulse activity of upper esophageal sphincter muscles is a reliable criterion for enhanced food motivation during search behavior in rabbits.

The binary millisecond pulsar PSR J1023+0038 during its accretion state – I. Optical variability

We present time-resolved optical photometry of the binary millisecond `redback' pulsar PSR J1023+0038 (=AY Sex) during its low-mass X-ray binary phase. The light curves taken between 2014 January and April show an underlying sinusoidal modulation due to the irradiated secondary star and accretion disc. We also observe superimposed rapid flaring on time-scales as short as ~20 s with amplitudes of ~0.1-0.5 mag and additional large flare events on time-scales of ~5-60 min with amplitudes ~0.5-1.0 mag. The power density spectrum of the optical flare light curves is dominated by a red-noise component, typical of aperiodic activity in X-ray binaries. Simultaneous X-ray and UV observations by the Swift satellite reveal strong correlations that are consistent with X-ray reprocessing of the UV light, most likely in the outer regions of the accretion disc. On some nights we also observe sharp-edged, rectangular, flat-bottomed dips randomly distributed in orbital phase, with a median duration of ~250 s and a median ingress/egress time of ~20 s. These rectangular dips are similar to the mode-switching behaviour between disc `active' and `passive' luminosity states, observed in the X-ray light curves of other redback millisecond pulsars. This is the first time that the optical analogue of the X-ray mode-switching has been observed. The properties of the passive and active state light curves can be explained in terms of clumpy accretion from a trapped inner accretion disc near the corotation radius, resulting in rectangular, flat-bottomed optical and X-ray light curves.

Daniel C. Moore, MD, and the Renaissance of Regional Anesthesia in North America

While much attention is paid to the early days of organized regional anesthesia in North America under the leadership of Gaston Labat in New York, there was a period of decline in energy and activity in those techniques after the demise of his original American Society of Regional Anesthesia in 1940. In the years after World War II, questions were raised about the safety and utility of regional blockade. Dr. Daniel C. Moore emerged as a colorful and enthusiastic advocate of regional techniques, effectively leading a renaissance of regional anesthesia interest through his textbook, teaching, and research in Seattle, Washington. His protégés were instrumental in the rebirth of American Society of Regional Anesthesia and the extensive spread of regional anesthesia today.

Phase connecting multi-epoch radio data for the ultracool dwarf TVLM 513-46546

Context. Radio data obtained for the ultracool dwarf TVLM 513-46546 has indicated a rotation period of ≈1.96 h via regular radio pulses, but how stable is this period. This has major implications regarding the stability of the magnetic field structures responsible for the radio emission from the ultracool dwarf. Aims. The aim of the present work is to investigate the stability of this rotation period using two datasets taken ≈40 days apart, some 12 months after the first report of periodical pulses in the radio data. Methods. Here we use a Bayesian analysis method which is a statistical procedure that endeavours to estimate the parameters of an underlying model probability distribution based on the observed data. Results. Periodical pulses are detected in datasets taken in April and June 2007, with the pulses being confined to a narrow range in the rotation period. This is in contradiction to a previous report of only aperiodic activity in the April 2007 dataset, while in fact both datasets have a periodic signal with a false alarm probability ≪ 10^-12. These two datasets are then used to derive a more accurate period (previously determined to be 1.96 h) of 1.96733 ± 0.00002 h. Conclusions. The similarly in the burst structure in datasets taken several weeks apart point towards the stability of an electric field structure which is somehow generated and sustained within the magnetosphere of the ultracool dwarf. The derived period of 1.96733 h is consistent with the period derived via radio and optical data taken some 12 months prior to the present observations and implies the near phase constancy of the pulsed emission. This suggest the presence of stable large-scale magnetic fields on timescales of more than 1 year. The characteristics of the pulses suggest that they are produced by the electron cyclotron maser (ECM) instability.

Modeling schizophrenic-like neuronal patterns using nonlinear delayed differential equations

We examined the simultaneous effect of altered dopamine and glutamate level on pyramidal cells using a mathematical model. The simulation results suggest that increased dopamine brings about irregular and aperiodic activity, interpreted as schizophrenic state. Hypoglutamatergic conditions have the same effect on the membrane potential of pyramidal cells. Increased glutamate level was able to neutralize the effects of the hyperdopamine state and normal periodic bursting behavior appeared. We suggest that glutamate receptor activation may have therapeutic results in schizophrenic patients. Surely, this hypothesis must be evaluated in the light of experimental studies on animal models or clinical trials.

Empirical model of variations in the OI 630 nm emission. 1. Intensity

The empirical model of variations in the atomic oxygen emission intensity depending on different heliogeophysical conditions such as nighttime, lunar time, lunar phase age, season, year, and solar activity level during the 11-year cycle, as well as on cyclic aperiodic activity variations, level of geomagnetic disturbances, and their manifestations in the form of midlatitude subauroral red arcs, has been developed based on the long-term measurements of this emission intensity.