Slow oscillation-spindle coupling predicts sequence-based language learning

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: Feb. 14, 2020

Abstract Sentence comprehension involves the rapid decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language relies, in part, on long-term memory. However, electrophysiological mechanisms underpinning initial encoding generalisation higher-order linguistic knowledge remain elusive, particularly from sleep-based consolidation perspective. One candidate mechanism that may support is temporal coordination slow oscillations (SO) sleep spindles during non-rapid eye movement (NREM). To examine this hypothesis, we analysed electroencephalographic (EEG) data recorded 35 participants (M age = 25.4, SD 7.10; 16 males) an artificial learning task, contrasting performance between individuals who were given 8hr nocturnal period or equivalent wake. We found relative wake was associated superior for rules followed sequence-based word order. Post-sleep order processing further less task-related theta desynchronisation, signature successful memory consolidation, as well control working Frontal NREM SO-spindle coupling also positively behavioural sensitivity rules, power. such, activity retrieval previously learned information correlates coupling, thus linking neural sleeping waking brain. Taken together, study presents converging behavioral neurophysiological evidence role signatures context learning. SIGNIFICANCE STATEMENT The endogenous supports states. Here demonstrate oscillation-spindle predicts modulates oscillatory dynamics implicated sentence processing. show increases power predict enhanced violations after strong subsequent influence behaviour. Our findings reveal interaction wake- sleep-related early stages beyond single level.

Language: Английский

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Aperiodic neural activity is a biomarker for depression severity

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 8, 2023

A reliable physiological biomarker for Major Depressive Disorder (MDD) is necessary to improve treatment success rates by shoring up variability in outcome measures. In this study, we establish a passive that tracks with changes mood on the order of minutes hours. We record from intracranial electrodes implanted deep brain - surgical setting providing exquisite temporal and spatial sensitivity detect relationship difficult-to-measure area, ventromedial prefrontal cortex (VMPFC). The aperiodic slope power spectral density captures balance activity across all frequency bands construed as putative proxy excitatory/inhibitory brain. This study demonstrates how shifts correlate depression severity clinical trial stimulation treatment-resistant (TRD). correlation between scores significant N=5 subjects, indicating flatter (less negative) slopes correspond reduced severity, especially cortex. offers new way track patient response MDD treatment, facilitating individualized therapies both non-invasive monitoring scenarios.

Language: Английский

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Task-related, intrinsic oscillatory and aperiodic neural activity predict performance in naturalistic team-based training scenarios

Scientific Reports, Journal Year: 2022, Volume and Issue: 12(1)

Published: Sept. 28, 2022

Abstract Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as operational training environments. In this exploratory study, we recruited forty paired twenty dyads and recorded dual-EEG at rest during realistic scenarios increasing complexity using virtual simulation systems. We estimated markers intrinsic brain activity (i.e., individual alpha frequency aperiodic activity), well task-related theta oscillations. Using nonlinear modelling a logistic regression machine learning model, found that resting-state EEG predicts performance can also reliably differentiate between members within dyad. Task-related easy tasks predicted later on complex to greater extent than prior behaviour. These findings complement laboratory-based research both oscillatory higher-order cognition provide evidence play critical role task team

Language: Английский

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The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: May 15, 2023

Abstract Background: Distinguishing Alzheimer's disease (AD) from frontotemporal dementia (FTD) poses a clinical challenge, and to address this, inexpensive accessible techniques, such as electroencephalography (EEG), are increasingly being employed. However, current studies on electrophysiology have not adequately separated aperiodic activity spectral analysis instead evaluated the combination of periodic oscillatory components components. As understanding has evolved, its potential physiological significance in these disorders become an area growing interest. The objective our study is determine differences between two dementia-related diseases evaluate their effect distinguishing them. Methods: A total 88 participants, including 36 patients with AD, 23 FTD, 29 healthy controls (CN), were enrolled for cognitive assessment scalp EEG acquisition. spectrum was decomposed using method parameterizing neuronal power spectra, comparing group different components, support vector machine used parameters differential diagnosis. Results: AD FTD groups showed varying degrees rhythm slowing compared CN group. Theta higher at channel level. inclusion led better performance Conclusions: Our indicates that shows distinguish disorders. These results underscore diseases.

Language: Английский

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Neurophysiological mechanisms of cognition in the developing brain: Insights from intracranial EEG studies

Developmental Cognitive Neuroscience, Journal Year: 2023, Volume and Issue: 64, P. 101312 - 101312

Published: Oct. 10, 2023

The quest to understand how the development of brain supports complex cognitive functions is fueled by advances in neuroscience methods. Intracranial EEG (iEEG) recorded directly from developing human provides unprecedented spatial and temporal resolution for mapping neurophysiological mechanisms supporting development. In this paper, we focus on episodic memory, ability remember detailed information about past experiences, which improves childhood into adulthood. We review memory effects based broadband spectral power emphasize importance isolating narrowband oscillations activity determine neural coordination within between regions. then evidence developmental variability present emerging linking memory. conclude proposing that increases precision may be an essential factor underlying More broadly, demonstrate recording holds immense potential advance our understanding

Language: Английский

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