Age-Related Changes in 1/f Neural Electrophysiological Noise

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 (), is often1 for electrophysiological data and has been shown to approach white noise (defined as  0) with increasing task difficulty.Weobserved, 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.

AUTHORS

• Bradley Voytek

• Mark A. Kramer

• John Case

• Kyle Q. Lepage

• Zachary Tempesta

• Robert T. Knight

• Adam Gazzaley

Date: 2015

DOI: 10.1523/JNEUROSCI.2332-14.2015

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Electrophysiological evidence for different inhibitory mechanisms when stopping or changing a planned response

Authors:

• Mark A. Kramer

• Robert T. Knight

• Thomas F. Münte

Date: 2009

PubMed: 20849230

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Abstract:

People are able to adapt their behavior to changing environmental contingencies by rapidly inhibiting or modifying their actions. Response inhibition is often studied in the stop-signal paradigm that requires the suppression of an already prepared motor response. Less is known about situations calling for a change of motor plans such that the prepared response has to be withheld but another has to be executed instead. In the present study, we investigated whether electrophysiological data can provide evidence for distinct inhibitory mechanisms when stopping or changing a response. Participants were instructed to perform in a choice RT task with two classes of embedded critical trials: Stop signals called for the inhibition of any response, whereas change signals required participants to inhibit the prepared response and execute another one instead. Under both conditions, we observed differences in go-stimulus processing, suggesting a faster response preparation in failed compared with successful inhibitions. In contrast to stop-signal trials, changing a response did not elicit the inhibition-related frontal N2 and did not modulate the parietal mu power decrease. The results suggest that compared with changing a response, additional frontal and parietal regions are engaged when having to inhibit a response.

Synchronization measures of bursting data: Application to the electrocoricogram of an auditory event-related experiment

Authors:

• Mark A. Kramer

• Erik Edwards

• Maryam Soltani

• Mitchel S. Berger

• Robert T. Knight

• Andrew J. Szeri

Date: 2004

PubMed: 15324095

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Abstract:

Synchronization measures have become an important tool for exploring the relationships between time series. We review three recently proposed nonlinear synchronization measures and expand their definitions in a straightforward way to apply to an ensemble of measurements. We also develop a synchronization measure in which nearest neighbors are determined across the ensemble. We compare these four nonlinear synchronization measures and show that our measure succeeds in physically motivated examples where the other methods fail. We apply the synchronization measure to human electrocorticogram data collected during an auditory event-related potential experiment. The results suggest a crude model of cortical connectivity.