Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity

eNeuro, Год журнала: 2020, Номер 7(6), С. ENEURO.0192 - 20.2020

Опубликована: Сен. 25, 2020

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

Язык: Английский

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Behavioral and cognitive correlates of the aperiodic (1/f-like) exponent of the EEG power spectrum in adolescents with and without ADHD

Developmental Cognitive Neuroscience, Год журнала: 2021, Номер 48, С. 100931 - 100931

Опубликована: Янв. 29, 2021

Efficient information processing facilitates cognition and may be disrupted in a number of neurodevelopmental conditions. And yet, the role inefficient its neural underpinnings remains poorly understood. In current study, we examined cognitive behavioral correlates aperiodic exponent electroencephalogram (EEG) power spectrum, putative marker disrupted, communication, sample adolescents with without ADHD (n = 184 nADHD 87; Mage 13.95 years, SD 1.36). Exponents were calculated via FOOOF (Donoghue et al., 2020a) from EEG data recorded during an 8-minute baseline episode. Reaction time speed variability, as well drift diffusion parameters (including rate parameter, parameter directly related to processing) calculated. Adolescents had smaller exponents (a "flattened" spectrum) relative their typically-developing peers. After controlling for ADHD, reaction variability but not expected direction. Our findings lend support correlate processing, provide insight into cortical excitation/inhibition imbalance pathophysiology ADHD.

Язык: Английский

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Advances in human intracranial electroencephalography research, guidelines and good practices

NeuroImage, Год журнала: 2022, Номер 260, С. 119438 - 119438

Опубликована: Июль 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

Язык: Английский

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An increase of inhibition drives the developmental decorrelation of neural activity

eLife, Год журнала: 2022, Номер 11

Опубликована: Авг. 17, 2022

Throughout development, the brain transits from early highly synchronous activity patterns to a mature state with sparse and decorrelated neural activity, yet mechanisms underlying this process are poorly understood. The developmental transition has important functional consequences, as latter is thought allow for more efficient storage, retrieval, processing of information. Here, we show that, in mouse medial prefrontal cortex (mPFC), during first two postnatal weeks decorrelates following specific spatial patterns. This accompanied by concomitant tilting excitation-inhibition (E-I) ratio toward inhibition. Using optogenetic manipulations network modeling, that phenomena mechanistically linked, relative increase inhibition drives decorrelation activity. Accordingly, mice mimicking etiology neurodevelopmental disorders, subtle alterations E-I associated impairments correlational structure spike trains. Finally, capitalizing on EEG data newborn babies, an analogous takes place also human brain. Thus, changes control (de)correlation and, these means, its imbalance might contribute pathogenesis disorders.

Язык: Английский

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Consciousness is supported by near-critical slow cortical electrodynamics

Proceedings of the National Academy of Sciences, Год журнала: 2022, Номер 119(7)

Опубликована: Фев. 10, 2022

Significance What changes in the brain when we lose consciousness? One possibility is that loss of consciousness corresponds to a transition brain’s electric activity away from edge-of-chaos criticality, or knife’s edge between stability and chaos. Recent mathematical developments have produced tools for testing this hypothesis, which apply cortical recordings diverse states. We show cortex indeed poised near boundary chaos during conscious states transitions unconsciousness disrupts information processing.

Язык: Английский

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