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Bradley Voytek

Bio: Bradley Voytek is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Electroencephalography & Prefrontal cortex. The author has an hindex of 30, co-authored 93 publications receiving 4065 citations. Previous affiliations of Bradley Voytek include University of California, Los Angeles & University of California, Berkeley.


Papers
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Journal ArticleDOI
TL;DR: An algorithm to parameterize electrophysiological neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks is introduced, addressing limitations of common approaches.
Abstract: Electrophysiological signals exhibit both periodic and aperiodic properties. Periodic oscillations have been linked to numerous physiological, cognitive, behavioral and disease states. Emerging evidence demonstrates that the aperiodic component has putative physiological interpretations and that it dynamically changes with age, task demands and cognitive states. Electrophysiological neural activity is typically analyzed using canonically defined frequency bands, without consideration of the aperiodic (1/f-like) component. We show that standard analytic approaches can conflate periodic parameters (center frequency, power, bandwidth) with aperiodic ones (offset, exponent), compromising physiological interpretations. To overcome these limitations, we introduce an algorithm to parameterize neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks. This algorithm requires no a priori specification of frequency bands. We validate this algorithm on simulated data, and demonstrate how it can be used in applications ranging from analyzing age-related changes in working memory to large-scale data exploration and analysis.

628 citations

Journal ArticleDOI
TL;DR: It is found, in two separate human studies, that 1/f electrophysiological noise increases with aging, and it is observed that this age-related 1/ f noise statistically mediates age- related working memory decline.
Abstract: Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by an increase in spontaneous, noisy baseline neural activity. Here we analyze data from two different groups of human subjects: intracranial electrocorticography from 15 participants over a 38 year age range (15-53 years) and scalp EEG data from healthy younger (20-30 years) and older (60-70 years) adults to test the neural noise hypothesis from a 1/f noise perspective. Many natural phenomena, including electrophysiology, are characterized by 1/f noise. The defining characteristic of 1/f is that the power of the signal frequency content decreases rapidly as a function of the frequency (f) itself. The slope of this decay, the noise exponent (χ), is often <-1 for electrophysiological data and has been shown to approach white noise (defined as χ = 0) with increasing task difficulty. We observed, in both electrophysiological datasets, that aging is associated with a flatter (more noisy) 1/f power spectral density, even at rest, and that visual cortical 1/f noise statistically mediates age-related impairments in visual working memory. These results provide electrophysiological support for the neural noise hypothesis of aging. Significance statement: Understanding the neurobiological origins of age-related cognitive decline is of critical scientific, medical, and public health importance, especially considering the rapid aging of the world's population. We find, in two separate human studies, that 1/f electrophysiological noise increases with aging. In addition, we observe that this age-related 1/f noise statistically mediates age-related working memory decline. These results significantly add to this understanding and contextualize a long-standing problem in cognition by encapsulating age-related cognitive decline within a neurocomputational model of 1/f noise-induced deficits in neural communication.

424 citations

Journal ArticleDOI
TL;DR: It is shown that high gamma amplitude couples to theta and alpha troughs and it is demonstrated that, during visual tasks, alpha/high gamma coupling preferentially increases in visual cortical regions.
Abstract: The phase of ongoing theta (4-8 Hz) and alpha (8-12 Hz) electrophysiological oscillations is coupled to high gamma (80-150 Hz) amplitude, which suggests that low frequency oscillations modulate local cortical activity. While this phase-amplitude coupling (PAC) has been demonstrated in a variety of tasks and cortical regions, it has not been shown whether task demands differentially affect the regional distribution of the preferred low-frequency coupling to high gamma. To address this issue we investigated multiple-rhythm theta/alpha phase to high gamma amplitude PAC in two subjects with implanted subdural electrocorticographic grids. We show that high gamma amplitude couples to the theta and alpha troughs and demonstrate that, during visual tasks, alpha/high gamma coupling preferentially increases in visual cortical regions. These results suggest that low-frequency phase to high-frequency amplitude PAC is modulated by behavioral task and may reflect a mechanism for selection between communicating neuronal networks.

398 citations

Journal ArticleDOI
TL;DR: A computational model is developed to show that E:I changes can be estimated from the power law exponent (slope) of the electrophysiological power spectrum, and provides evidence thatE:I ratio may be inferred from electrophysics recordings at many spatial scales, ranging from the local field potential to surface electrocorticography.

397 citations

Journal ArticleDOI
TL;DR: Human cortical organoids that dynamically change cellular populations during maturation and exhibited consistent increases in electrical activity over the span of several months show that the development of structured network activity in a human neocortex model may follow stable genetic programming.

388 citations


Cited by
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01 Jan 2010
TL;DR: In this paper, the authors describe a scenario where a group of people are attempting to find a solution to the problem of "finding the needle in a haystack" in the environment.
Abstract: 中枢神経系疾患の治療は正常細胞(ニューロン)の機能維持を目的とするが,脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い.一方,脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める.いずれの場合にも,細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である.現在のところ最も研究の進んでいる細胞死の型はアポトーシスである.そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する.

2,716 citations

Journal ArticleDOI
TL;DR: It is proposed that information is gated by inhibiting task-irrelevant regions, thus routing information to task-relevant regions and the empirical support for this framework is discussed.
Abstract: In order to understand the working brain as a network, it is essential to identify the mechanisms by which information is gated between regions. We here propose that information is gated by inhibiting task-irrelevant regions, thus routing information to task-relevant regions. The functional inhibition is reflected in oscillatory activity in the alpha band (8-13 Hz). From a physiological perspective the alpha activity provides pulsed inhibition reducing the processing capabilities of a given area. Active processing in the engaged areas is reflected by neuronal synchronization in the gamma band (30-100 Hz) accompanied by an alpha band decrease. According to this framework the brain should be studied as a network by investigating cross-frequency interactions between gamma and alpha activity. Specifically the framework predicts that optimal task performance will correlate with alpha activity in task-irrelevant areas. In this review we will discuss the empirical support for this framework. Given that alpha activity is by far the strongest signal recorded by EEG and MEG, we propose that a major part of the electrophysiological activity detected from the working brain reflects gating by inhibition.

2,448 citations

Journal ArticleDOI
TL;DR: The cellular and synaptic mechanisms underlying gamma oscillations are reviewed and empirical questions and controversial conceptual issues are outlined, finding that gamma-band rhythmogenesis is inextricably tied to perisomatic inhibition.
Abstract: Gamma rhythms are commonly observed in many brain regions during both waking and sleep states, yet their functions and mechanisms remain a matter of debate. Here we review the cellular and synaptic mechanisms underlying gamma oscillations and outline empirical questions and controversial conceptual issues. Our main points are as follows: First, gamma-band rhythmogenesis is inextricably tied to perisomatic inhibition. Second, gamma oscillations are short-lived and typically emerge from the coordinated interaction of excitation and inhibition, which can be detected as local field potentials. Third, gamma rhythm typically concurs with irregular firing of single neurons, and the network frequency of gamma oscillations varies extensively depending on the underlying mechanism. To document gamma oscillations, efforts should be made to distinguish them from mere increases of gamma-band power and/or increased spiking activity. Fourth, the magnitude of gamma oscillation is modulated by slower rhythms. Such cross-frequency coupling may serve to couple active patches of cortical circuits. Because of their ubiquitous nature and strong correlation with the "operational modes" of local circuits, gamma oscillations continue to provide important clues about neuronal population dynamics in health and disease.

2,168 citations