Parameterizing neural power spectra into periodic and aperiodic components

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.

Authors:

• Thomas Donoghue

• Matar Haller

• Erik J Peterson

• Paroma Varma

• Priyadarshini Sebastian

• Richard Gao

• Torben Noto

• Antonio H Lara

• Joni D Wallis

• Robert T Knight

• Avgusta Shestyuk

• Bradley Voytek

Date: 2020

DOI: https://doi.org/10.1038/s41593-020-00744-x

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Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement

Abstract:

Television (TV) programming attracts ever-growing audiences and dominates the cultural zeitgeist. Viewership and social media engagement have become standard indices of programming success. However, accurately predicting individual episode success or future show performance using traditional metrics remains a challenge. Here we examine whether TV viewership and Twitter activity can be predicted using electroencephalography (EEG) measures, which are less affected by reporting biases and which are commonly associated with different cognitive processes. 331 participants watched an hour-long episode from one of nine prime-time shows (~36 participants per episode). Three frequency-based measures were extracted: fronto-central alpha/beta asymmetry (indexing approach motivation), fronto-central alpha/theta power (indexing attention), and fronto-central theta/gamma power (indexing memory processing). All three EEG measures and the composite EEG score significantly correlated across episode segments with the two behavioral measures of TV viewership and Twitter volume. EEG measures explained more variance than either of the behavioral metrics and mediated the relationship between the two. Attentional focus was integral for both audience retention and Twitter activity, while emotional motivation was specifically linked with social engagement and program segments with high TV viewership. These findings highlight the viability of using EEG measures to predict success of TV programming and identify cognitive processes that contribute to audience engagement with television shows.

Authors:

• Avgusta Y. Shestyuk

• Karthik Kasinathan

• Viswajith Karapoondinott

• Robert T. Knight

• Ram Gurumoorthy

Date: 2019

DOI: https://doi.org/10.1371/journal.pone.0214507

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Temporal dynamics and response modulation across the human visual system in a spatial attention task: an ECoG study

Abstract:

The selection of behaviorally relevant information from cluttered visual scenes (often referred to as “attention”) is mediated by a cortical large-scale network consisting of areas in occipital, temporal, parietal, and frontal cortex that is organized into a functional hierarchy of feedforward and feedback pathways. In the human brain, little is known about the temporal dynamics of attentional processing from studies at the mesoscopic level of electrocorticography (ECoG), that combines millisecond temporal resolution with precise anatomical localization of recording sites. We analyzed high-frequency broadband responses (HFB) responses from 626 electrodes implanted in 8 epilepsy patients who performed a spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system. HFB responses showed high spatial selectivity and tuning, constituting ECoG response fields (RFs), within and outside the topographic visual system. In accordance with monkey physiology studies, both RF widths and onset latencies increased systematically across the visual processing hierarchy. We used the spatial specificity of HFB responses to quantitatively study spatial attention effects and their temporal dynamics to probe a hierarchical top-down model suggesting that feedback signals back propagate the visual processing hierarchy. Consistent with such a model, the strengths of attentional modulation were found to be greater and modulation latencies to be shorter in posterior parietal cortex, middle temporal cortex and ventral extrastriate cortex compared with early visual cortex. However, inconsistent with such a model, attention effects were weaker and more delayed in anterior parietal and frontal cortex.

Authors:

• Anne B. Martin

• Xiaofang Yang

• Yuri B. Saalmann

• Liang Wang

• Avgusta Shestyuk

• Jack J. Lin

• Josef Parvizi

• Robert T. Knight

• Sabine Kastner

Date: 2019

DOI: 10.1523/JNEUROSCI.1889-18.2018

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Amygdala-hippocampal dynamics during salient information processing

ABSTRACT

Recognizing motivationally salient information is critical to guiding behaviour. The amygdala and hippocampus are thought to support this operation, but the circuit-level mechanism of this interaction is unclear. We used direct recordings in the amygdala and hippocampus from human epilepsy patients to examine oscillatory activity during processing of fearful faces compared with neutral landscapes. We report high gamma (70–180 Hz) activation for fearful faces with earlier stimulus evoked onset in the amygdala compared with the hippocampus. Attending to fearful faces compared with neutral landscape stimuli enhances low-frequency coupling between the amygdala and the hippocampus. The interaction between the amygdala and hippocampus is largely unidirectional, with theta/alpha oscillations in the amygdala modulating hippocampal gamma activity. Granger prediction, phase slope index and phase lag analysis corroborate this directional coupling. These results demonstrate that processing emotionally salient events in humans engages an amygdala-hippocampal network, with the amygdala influencing hippocampal dynamics during fear processing.

AUTHORS

• Robert T. Knight

• Avgusta Shestyuk

• Kristopher L. Anderson

• Jie Zheng

• Stephanie L. Leal

• Gultekin Gulsen

• Lilit Mnatsakanyan

• Sumeet Vadera

• Frank P.K. Hsu

• Michael A. Yassa

• Jack J. Lin

Date: 2017

DOI: 10.1038/ncomms14413

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Redefining the role of Broca’s area in speech

Authors:

• Adeen Flinker

• Anna Korzeniewska

• Avgusta Shestyuk

• Piotr Franaszczuk

• Nina F. Dronkers

• Robert T. Knight

• Nathan E. Crone

Date: 2015

DOI: 10.1073/pnas.1414491112

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Abstract:

For over a century neuroscientists have debated the dynamics by which human cortical language networks allow words to be spoken. Although it is widely accepted that Broca’s area in the left inferior frontal gyrus plays an important role in this process, it was not possible, until recently, to detail the timing of its recruitment relative to other language areas, nor how it interacts with these areas during word production. Using direct cortical surface recordings in neurosurgical patients, we studied the evolution of activity in cortical neuronal populations, as well as the Granger causal interactions between them. We found that, during the cued production of words, a temporal cascade of neural activity proceeds from sensory representations of words in temporal cortex to their corresponding articulatory gestures in motor cortex. Broca’s area mediates this cascade through reciprocal interactions with temporal and frontal motor regions. Contrary to classic notions of the role of Broca’s area in speech, while motor cortex is activated during spoken responses, Broca’s area is surprisingly silent. Moreover, when novel strings of articulatory gestures must be produced in response to non- word stimuli, neural activity is enhanced in Broca’s area, but not in motor cortex. These unique data provide evidence that Broca’s area coordinates the transformation of information across large-scale cortical networks involved in spoken word production. In this role, Broca’s area formulates an appropriate articulatory code to be implemented by motor cortex.

Shifts in gamma phase-amplitude coupling frequency from theta to alpha over posterior cortex during visual tasks

Authors:

• Bradley Voytek

• Ryan T. Canolty

• Avgusta Shestyuk

• Nathan E. Crone

• Josef Parvizi

• Robert T. Knight

Date: 2010

DOI: 10.3389/fnhum.2010.00191

PubMed: 21060716

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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 to high gamma 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 coupling is modulated by behavioral task and may reflect a mechanism for selection between communicating neuronal networks.