Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

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Abstract

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson’s Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, questioning such role. We hypothesized that this inconsistency is due to the influence of electrophysiological broadband activity —a neurophysiological indicator of synaptic excitation/inhibition ratio— that could confound measurements of beta activity in STN recordings. Here we propose a data-driven, automatic and individualized mathematical model that disentangles beta activity and 1/f broadband activity in the STN power spectrum, and investigate the link between these individual components and motor symptoms in thirteen Parkinsonian patients. We show, using both modeled and actual data, how beta oscillatory activity significantly correlates with motor symptoms (bradykinesia and rigidity) only when broadband activity is not considered in the biomarker estimations, providing solid evidence that oscillatory beta activity does correlate with motor symptoms in untreated PD states as well as the significant impact of broadband activity. These findings emphasize the importance of data-driven models and the identification of better biomarkers for characterizing symptom severity and closed-loop applications.

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Most cited references 5

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Inferring synaptic excitation/inhibition balance from field potentials.

Bradley Voytek, Erik Peterson, Richard Gao (2017)

Neural circuits sit in a dynamic balance between excitation (E) and inhibition (I). Fluctuations in E:I balance have been shown to influence neural computation, working memory, and information flow, while more drastic shifts and aberrant E:I patterns are implicated in numerous neurological and psychiatric disorders. Current methods for measuring E:I dynamics require invasive procedures that are difficult to perform in behaving animals, and nearly impossible in humans. This has limited the ability to examine the full impact that E:I shifts have in cognition and disease. In this study, we develop a computational model to show that E:I changes can be estimated from the power law exponent (slope) of the electrophysiological power spectrum. Predictions from the model are validated in published data from two species (rats and macaques). We find that reducing E:I ratio via the administration of general anesthetic in macaques results in steeper power spectra, tracking conscious state over time. This causal result is supported by inference from known anatomical E:I changes across the depth of rat hippocampus, as well as oscillatory theta-modulated dynamic shifts in E:I. Our results provide evidence that E:I ratio may be inferred from electrophysiological recordings at many spatial scales, ranging from the local field potential to surface electrocorticography. This simple method for estimating E:I ratio-one that can be applied retrospectively to existing data-removes a major hurdle in understanding a currently difficult to measure, yet fundamental, aspect of neural computation.

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Age-Related Changes in 1/f Neural Electrophysiological Noise.

Bradley Voytek, Mark Kramer, John P. Case … (2015)

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.

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Simulated power spectral density (PSD) of background electrocorticogram (ECoG).

James Freeman, J Zhai (2009)

The ECoG background activity of cerebral cortex in states of rest and slow wave sleep resembles broadband noise. The power spectral density (PSD) then may often conform to a power-law distribution: a straight line in coordinates of log power vs. log frequency. The exponent, x, of the distribution, 1/f(x), ranges between 2 and 4. These findings are explained with a model of the neural source of the background activity in mutual excitation among pyramidal cells. The dendritic response of a population of interactive excitatory neurons to an impulse input is a rapid exponential rise and a slow exponential decay, which can be fitted with the sum of two exponential terms. When that function is convolved as the kernel with pulses from a Poisson process and summed, the resulting "brown" or "black noise conforms to the ECoG time series and the PSD in rest and sleep. The PSD slope is dependent on the rate of rise. The variation in the observed slope is attributed to variation in the level of the background activity that is homeostatically regulated by the refractory periods of the excitatory neurons. Departures in behavior from rest and sleep to action are accompanied by local peaks in the PSD, which manifest emergent nonrandom structure in the ECoG, and which prevent reliable estimation of the 1/f(x) exponents in active states. We conclude that the resting ECoG truly is low-dimensional noise, and that the resting state is an optimal starting point for defining and measuring both artifactual and physiological structures emergent in the activated ECoG.

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Author and article information

Contributors

Iñaki Iturrate:

ORCID: http://orcid.org/0000-0001-7781-7826

inaki.iturrate@epfl.ch

Journal

Journal ID (nlm-ta): NPJ Parkinsons Dis

Journal ID (iso-abbrev): NPJ Parkinsons Dis

Title: NPJ Parkinson's Disease

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2373-8057

Publication date (Electronic): 5 November 2018

Publication date PMC-release: 5 November 2018

Publication date Collection: 2018

Volume: 4

Electronic Location Identifier: 32

Affiliations

[1 ]ISNI 0000000121839049, GRID grid.5333.6, Defitech Chair in Brain-Machine Interface (CNBI), Center for Neuroprosthetics (CNP), , Ecole Polytechnique Fédérale de Lausanne (EPFL), ; Lausanne, Switzerland

[2 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Helen Wills Neuroscience Institute, , University of California, ; Berkeley, CA USA

[3 ]ISNI 0000000121742757, GRID grid.194645.b, Li Ka Shing Faculty of Medicine, , University of Hong Kong, ; Hong Kong, P.R. China

[4 ]ISNI 0000 0001 0423 4662, GRID grid.8515.9, Department of Clinical Neurosciences (Neurology and Neurosurgery), , University Hospital of Vaud (CHUV), ; Lausanne, Switzerland

[5 ]ISNI 0000 0000 8631 6364, GRID grid.418149.1, Service de Neurochirurgie, Hôpital de Sion, , Hôpital du Valais, ; Valais, Switzerland

[6 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Department of Psychology, , University of California, ; Berkeley, CA USA

Author information

Stephanie Martin http://orcid.org/0000-0001-8678-5862

Iñaki Iturrate http://orcid.org/0000-0001-7781-7826

Ricardo Chavarriaga http://orcid.org/0000-0002-8879-2860

David Benninger http://orcid.org/0000-0002-1049-9533

Jocelyne Bloch http://orcid.org/0000-0002-6405-1590

José del R. Millán http://orcid.org/0000-0001-5819-1522

Article

Publisher ID: 68

DOI: 10.1038/s41531-018-0068-y

PMC ID: 6218479

PubMed ID: 30417084

SO-VID: dd999ff7-b36d-4573-b1c7-2e12e27d37f9

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Date received : 6 July 2018

Date accepted : 18 October 2018

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Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

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Most cited references 5

Inferring synaptic excitation/inhibition balance from field potentials.

Age-Related Changes in 1/f Neural Electrophysiological Noise.

Simulated power spectral density (PSD) of background electrocorticogram (ECoG).

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