Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 54, P. 101076 - 101076

Published: Jan. 22, 2022

The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for emergence maturation range social cognitive processes. Here, we utilised both eyes open closed resting-state electroencephalography (EEG) to examine maturational in oscillatory (i.e., periodic) non-oscillatory (aperiodic, '1/f-like') activity large cohort participants ranging from 4-to-12 years age (N = 139, average age=9.41 years, SD=1.95). EEG signal was parameterised into aperiodic periodic components, linear regression models were used evaluate if chronological could predict exponent offset, as well peak frequency power within alpha beta ranges. Exponent offset found decrease with age, while aperiodic-adjusted increased age; however, there no association between band. Age also unrelated spectral either or bands, despite ranges being correlated signal. Overall, these results highlight capacity features elucidate age-related functional developing brain.

Language: Английский

---

Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations

Neuroinformatics, Journal Year: 2022, Volume and Issue: 20(4), P. 991 - 1012

Published: April 7, 2022

Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f law [Formula: see text] and periodic components appearing as spectral peaks. While the investigation parts, commonly referred to neural oscillations, has received considerable attention, study only recently gained more interest. The is quantified by center frequencies, powers, bandwidths, while parameterized y-intercept exponent text]. For either part, however, it essential separate components. In this article, we scrutinize frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) IRASA (Irregular Resampling Auto-Spectral Analysis), that are from component. We evaluate these methods using diverse obtained with electroencephalography (EEG), magnetoencephalography (MEG), local field potential (LFP) recordings relating three independent research datasets. Each method each dataset poses distinct challenges for extraction both parts. specific features hindering separation highlighted simulations emphasizing features. Through comparison simulation parameters defined a priori, parameterization error quantified. Based on real simulated spectra, advantages discuss common challenges, note which impede separation, assess computational costs, propose recommendations how use them.

Language: Английский

---

Advances in human intracranial electroencephalography research, guidelines and good practices

NeuroImage, Journal Year: 2022, Volume and Issue: 260, P. 119438 - 119438

Published: July 2, 2022

Since the second half of twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into human brain. At interface between fundamental research clinic, iEEG provides high temporal resolution spatial specificity but comes with constraints, such as individual's tailored sparsity electrode sampling. Over years, researchers in neuroscience developed their practices to make most approach. Here we offer a critical review didactic framework for newcomers, well addressing issues encountered by proficient researchers. The scope is threefold: (i) common research, (ii) suggest potential guidelines working data answer frequently asked questions based on widespread practices, (iii) current neurophysiological knowledge methodologies, pave way good practice standards research. organization this paper follows steps processing. first section contextualizes collection. focuses localization electrodes. third highlights main pre-processing steps. fourth presents signal analysis methods. fifth discusses statistical approaches. sixth draws some unique perspectives Finally, ensure consistent nomenclature throughout manuscript align other guidelines, e.g., Brain Imaging Data Structure (BIDS) OHBM Committee Best Practices Analysis Sharing (COBIDAS), provide glossary disambiguate terms related

Language: Английский

---

Time-frequency analysis methods and their application in developmental EEG data

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 54, P. 101067 - 101067

Published: Jan. 14, 2022

EEG provides a rich measure of brain activity that can be characterized as neuronal oscillations. However, most developmental work to date has focused on analyzing data Event-Related Potentials (ERPs) or power based the Fourier transform. While these measures have been productive, they do not leverage all information contained within signal. Namely, ERP analyses ignore non-phase-locked signals and Fourier-based temporal information. Time-frequency better characterize oscillations in data. By separating phase across different frequencies, time-frequency provide closer interpretation neurophysiological mechanisms, facilitate translation neurophysiology disciplines, capture processes observed by (e.g., connectivity). Despite their unique contributions, literature review this journal reveals are yet embraced cognitive neuroscience field. This manuscript presents conceptual introduction for researchers. To use analyses, we include tutorial accessible scripts, Cohen (2014), calculate (signal strength), inter-trial synchrony consistency), two types phase-based connectivity (inter-channel weighted lag index).

Language: Английский

---

Spectral parameterization for studying neurodevelopment: How and why

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 54, P. 101073 - 101073

Published: Jan. 15, 2022

A growing body of literature suggests that the explicit parameterization neural power spectra is important for appropriate physiological interpretation periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why an imperative step developmental cognitive neuroscientists interested in cognition behavior across lifespan, as well how can be readily accomplished with automated spectral ("specparam") algorithm (Donoghue et al., 2020a). We provide annotated code parameterization, via specparam, Jupyter Notebook R Studio. then apply to EEG data childhood (N = 60; Mage 9.97, SD 0.95) illustrate its utility neuroscientists. Ultimately, may help us refine our understanding dynamic communication contributes normative aberrant lifespan. Data analysis manuscript are available on GitHub a supplement open-access specparam toolbox.

Language: Английский

---

From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans

Translational Psychiatry, Journal Year: 2022, Volume and Issue: 12(1)

Published: Nov. 8, 2022

Abstract Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in regulation this activity thought to give rise normal variation human traits, disruptions are potentially underlie spectrum neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs’ Syndrome, intellectual disability). Hypotheses related E/I dysfunction have potential provide cross-diagnostic explanations combine genetic neurological evidence that exists within psychiatric conditions. However, hypothesis has been difficult test because: (1) it lacks specificity—an could pertain any level neural system- neurotransmitters, single neurons/receptors, local networks neurons, or global - most researchers do not define at which they examining function; (2) We lack validated methods for assessing these levels humans. As result, possible reliably robustly disorders large cohort longitudinal patient studies. Currently available, vivo markers humans either carry significant risks deep electrode recordings using Positron Emission Tomography (PET) with radioactive tracers) and/or highly restrictive limited spatial extent Transcranial Magnetic Stimulation (TMS) Resonance Spectroscopy (MRS). More recently, range novel Electroencephalography (EEG) features described, serve as proxy given inference. Thus, perspective review, we survey theories experimental underlying 6 EEG their biological underpinnings specific level. These cheap-to-record scalable may offer clinical utility identifying subgroups diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. argue studies populations premature. To maximize prospective markers, first need understand link mechanisms measurement techniques.

Language: Английский

---

Recommendations and publication guidelines for studies using frequency domain and time‐frequency domain analyses of neural time series

Psychophysiology, Journal Year: 2022, Volume and Issue: 59(5)

Published: April 10, 2022

Abstract Since its beginnings in the early 20th century, psychophysiological study of human brain function has included research into spectral properties electrical and magnetic signals. Now, dramatic advances digital signal processing, biophysics, computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations hardware recording techniques further expanded range tools available to researchers interested measuring, quantifying, modeling, altering series. These are used field, by a growing number who vary their training, background, interests. Implementation reporting standards also greatly published literature, causing challenges authors, readers, reviewers, editors alike. The present report addresses this issue providing recommendations use these methods, with focus on foundational aspects frequency domain time‐frequency analyses. It provides publication guidelines, which aim (1) foster replication scientific rigor, (2) assist new wish enter field oscillations, (3) facilitate communication among editors.

Language: Английский

---

Decomposing age effects in EEG alpha power

Cortex, Journal Year: 2023, Volume and Issue: 161, P. 116 - 144

Published: Feb. 22, 2023

Increasing life expectancy is prompting the need to understand how brain changes during healthy aging. Research utilizing electroencephalography (EEG) has found that power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in data may confound results and thus require re-investigation these findings. Thus, present report analyzed a pilot two additional independent samples (total N = 533) resting-state EEG young elderly individuals. A newly developed algorithm was utilized allows decomposition measured signal into periodic aperiodic components. By using multivariate sequential Bayesian updating age effect each component, evidence across datasets accumulated. It hypothesized previously reported age-related differences will largely diminish when total adjusted for component. First, replicated. Concurrently, decreases intercept slope (i.e. exponent) component were observed. Findings on aperiodic-adjusted indicated this general shift spectrum leads an overestimation true effects conventional analyses power. importance separating neural spectra highlighted. also after accounting confounding factors, analysis provided robust aging associated with decreased While relation cognitive decline demands further investigation, consistent findings high test-retest reliabilities support emerging measures are reliable markers brain. Hence, previous interpretations reevaluated, incorporating signal.

Language: Английский

---

Innovation at the Intersection: Emerging Translational Research in Neurology and Psychiatry

Cells, Journal Year: 2024, Volume and Issue: 13(10), P. 790 - 790

Published: May 7, 2024

Translational research in neurological and psychiatric diseases is a rapidly advancing field that promises to redefine our approach these complex conditions [...]

Language: Английский

---

Posture‐Dependent Modulation of Interoceptive Processing in Young Male Participants: A Heartbeat‐Evoked Potential Study

European Journal of Neuroscience, Journal Year: 2025, Volume and Issue: 61(4)

Published: Feb. 1, 2025

ABSTRACT Interoception, the internal perception of bodily states such as heartbeat and hunger, plays a crucial role in shaping cognitive emotional states. Since postural control affects processing, exploring effects on interoception could help uncover neural mechanisms underlying its cognition emotion. In this study, we aimed to investigate how different postures affect by using heartbeat‐evoked potentials (HEPs), which reflect cortical processing cardiac signals. Two experiments were conducted; Experiment 1 involved 47 healthy male participants comparing sitting standing postures, 2 24 stable unstable conditions. HEPs analyzed cluster‐based permutation analysis identify statistically significant spatiotemporal clusters. 1, clusters identified over central electrodes (Cz, C1, C2, FCz, FC1) within post‐R‐wave interval 304–572 ms, revealing significantly lower HEP amplitudes during compared [ W = 80, p < 0.001, r 0.62]. 2, t (20) 2.9, 0.0099, d Furthermore, found no correlations between changes physiological activity periodic aperiodic brain activity. These findings suggest differences modulate interoceptive with attenuating amplitudes, probably because redistribution attentional resources from somatosensory (proprioceptive) vestibular necessary for maintaining posture. This study provides insights into posture–interoception interaction.

Language: Английский

---