Toward a functional future for the cognitive neuroscience of human aging DOI Creative Commons

Zoya Mooraj,

Alireza Salami, Karen L. Campbell

et al.

Neuron, Journal Year: 2025, Volume and Issue: 113(1), P. 154 - 183

Published: Jan. 1, 2025

Language: Английский

Methodological considerations for studying neural oscillations DOI
Thomas Donoghue, Natalie Schaworonkow, Bradley Voytek

et al.

European Journal of Neuroscience, Journal Year: 2021, Volume and Issue: 55(11-12), P. 3502 - 3527

Published: July 16, 2021

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

Language: Английский

Citations

209

Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent DOI Creative Commons
Leonhard Waschke, Thomas Donoghue, Lorenz Fiedler

et al.

eLife, Journal Year: 2021, Volume and Issue: 10

Published: Oct. 21, 2021

A hallmark of electrophysiological brain activity is its 1/f-like spectrum – power decreases with increasing frequency. The steepness this ‘roll-off’ approximated by the spectral exponent, which in invasively recorded neural populations reflects balance excitatory to inhibitory (E:I balance). Here, we first establish that exponent non-invasive electroencephalography (EEG) recordings highly sensitive general (i.e., anaesthesia-driven) changes E:I balance. Building on EEG as a viable marker E:I, then demonstrate sensitivity focus selective attention an experiment during participants detected targets simultaneous audio-visual noise. In addition these endogenous balance, exponents over auditory and visual sensory cortices also tracked stimulus exponents, respectively. Individuals’ degree stimulus–brain coupling predicted behavioural performance. Our results highlight rich information contained activity, providing window into diverse processes previously thought be inaccessible human recordings.

Language: Английский

Citations

182

Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations DOI Creative Commons
Moritz Gerster, Gunnar Waterstraat, Vladimir Litvak

et al.

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

Citations

144

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood DOI Creative Commons
Aron T. Hill, Gillian M. Clark, Felicity J. Bigelow

et al.

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

Citations

142

The impact of the human thalamus on brain-wide information processing DOI
James M. Shine, Laura D. Lewis, Douglas D. Garrett

et al.

Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(7), P. 416 - 430

Published: May 26, 2023

Language: Английский

Citations

131

Spectral parameterization for studying neurodevelopment: How and why DOI Creative Commons
Brendan Ostlund, Thomas Donoghue, Berenice Anaya

et al.

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

Citations

89

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing DOI Creative Commons
Thomas Pfeffer, Christian Keitel, Daniel S. Kluger

et al.

eLife, Journal Year: 2022, Volume and Issue: 11

Published: Feb. 8, 2022

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence population activity detail has so far only been characterized a few selected brain regions. Traditional accounts conceptualize as homogeneous modulator of neural across the cerebral cortex. Recent insights, however, point to higher specificity effects on different components and Here, we provide comprehensive account relationships between fluctuations neuronal human brain. Exploiting established link pupil size central performed concurrent magnetoencephalographic (MEG) pupillographic recordings large number participants, pooled three laboratories. We found cascade relative peak timing spontaneous dilations: Decreases low-frequency (2–8 Hz) temporal lateral frontal cortex, followed increased high-frequency (>64 mid-frontal regions, monotonic inverted U intermediate frequency-range (8–32 occipito-parietal Pupil-linked also coincided widespread changes structure aperiodic component activity, indicative excitation-inhibition balance underlying microcircuits. Our results novel basis studying modulation cognitive computations circuits.

Language: Английский

Citations

72

The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism DOI Creative Commons
Christoph Wiest, Flavie Torrecillos, Alek Pogosyan

et al.

eLife, Journal Year: 2023, Volume and Issue: 12

Published: Feb. 22, 2023

Periodic features of neural time-series data, such as local field potentials (LFPs), are often quantified using power spectra. While the aperiodic exponent spectra is typically disregarded, it nevertheless modulated in a physiologically relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance neuronal populations. Here, we used cross-species vivo electrophysiological approach test E/I hypothesis context experimental idiopathic Parkinsonism. We demonstrate dopamine-depleted rats that exponents at 30–100 Hz subthalamic nucleus (STN) LFPs defined changes basal ganglia network activity; higher tally with lower levels STN neuron firing tipped towards inhibition. Using STN-LFPs recorded from awake Parkinson’s patients, show accompany dopaminergic medication deep brain stimulation (DBS) STN, consistent untreated manifesting reduced inhibition hyperactivity STN. These results suggest Parkinsonism reflects might be candidate biomarker for adaptive DBS.

Language: Английский

Citations

49

Spectral Slope and Lempel–Ziv Complexity as Robust Markers of Brain States during Sleep and Wakefulness DOI Creative Commons
Christopher Höhn, Michael A Hahn, Janna D. Lendner

et al.

eNeuro, Journal Year: 2024, Volume and Issue: 11(3), P. ENEURO.0259 - 23.2024

Published: March 1, 2024

Nonoscillatory measures of brain activity such as the spectral slope and Lempel–Ziv complexity are affected by many neurological disorders modulated sleep. A multitude frequency ranges, particularly a broadband (encompassing full spectrum) narrowband approach, have been used especially for estimating slope. However, effects choosing different ranges not yet explored in detail. Here, we evaluated impact sleep stage task engagement (resting, attention, memory) on (30–45 Hz) (1–45 range 28 healthy male human subjects (21.54 ± 1.90 years) using within-subject design over 2 weeks with three recording nights days per subject. We strived to determine how states affect two perform comparison. In range, steepened, decreased continuously from wakefulness N3 REM sleep, however, was best discriminated Importantly, also differed between tasks during wakefulness. While engagement, flattened both ranges. Interestingly, only positively correlated performance. Our results show that sensitive indices state variations yields more information could be greater variety research questions than complexity, when is used.

Language: Английский

Citations

23

Aperiodic EEG and 7T MRSI evidence for maturation of E/I balance supporting the development of working memory through adolescence DOI Creative Commons
Shane D. McKeon,

Maria I. Perica,

Ashley C. Parr

et al.

Developmental Cognitive Neuroscience, Journal Year: 2024, Volume and Issue: 66, P. 101373 - 101373

Published: April 1, 2024

Adolescence has been hypothesized to be a critical period for the development of human association cortex and higher-order cognition. A defining feature is shift in excitation: inhibition (E/I) balance neural circuitry, however how changes E/I may enhance cortical circuit function support maturational improvements cognitive capacities not known. Harnessing ultra-high field 7 T MR spectroscopy EEG large, longitudinal cohort youth (N = 164, ages 10–32 years old, 347 neuroimaging sessions), we delineate biologically specific associations between age-related excitatory glutamate inhibitory GABA neurotransmitters EEG-derived measures aperiodic activity reflective prefrontal cortex. Specifically, find that developmental increases reflected glutamate:GABA are linked assessed by suppression activity, which turn facilitates robust working memory. These findings indicate role E/I-engendered signaling mechanisms maturation maintenance. More broadly, this multi-modal imaging study provides evidence undergoes physiological consistent with plasticity during adolescence.

Language: Английский

Citations

23