Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study

ABSTRACT

Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon.

AUTHORS

• Julia W. Y. Kam

• Sara Szczepanski

• Ryan T. Canolty

• Adeen Flinker

• Kurtis I. Auguste

• Nathan E. Crone

• Heidi E. Kirsch

• Rachel A. Kuperman

• Jack J. Lin

• Josef Parvizi

• Robert T. Knight

Date: 2016

DOI: 10.1093/cercor/bhw343

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Multivariate Phase–Amplitude Cross-Frequency Coupling in Neurophysiological Signals

Authors:

• Ryan T. Canolty

• Charles F. Cadieu

• Kilian Koepsell

• Robert T. Knight

• Jose M. Carmena

Date: 2012

PubMed: 22020662

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Abstract:

Phase-amplitude cross-frequency coupling (CFC)-where the phase of a low-frequency signal modulates the amplitude or power of a high-frequency signal-is a topic of increasing interest in neuroscience. However, existing methods of assessing CFC are inherently bivariate and cannot estimate CFC between more than two signals at a time. Given the increase in multielectrode recordings, this is a strong limitation. Furthermore, the phase coupling between multiple low-frequency signals is likely to produce a high rate of false positives when CFC is evaluated using bivariate methods. Here, we present a novel method for estimating the statistical dependence between one high-frequency signal and N low-frequency signals, termed multivariate phase-coupling estimation (PCE). Compared to bivariate methods, the PCE produces sparser estimates of CFC and can distinguish between direct and indirect coupling between neurophysiological signals-critical for accurately estimating coupling within multiscale brain networks.

A dynamical pattern recognition model of gamma activity in auditory cortex

Authors:

• Melissa Zavaglia

• Ryan T. Canolty

• Thomas M. Schofield

• Alexander P. Leff

• Mauro Ursino

• Robert T. Knight

• Will D. Penny

Date: 2012

DOI: 10.1016/j.neunet.2011.12.007

PubMed: 22327049

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Abstract:

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75-150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain.

Cortical Spatio-temporal Dynamics Underlying Phonological Target Detection in Humans

Authors:

• Edward F. Chang

• Erik Edwards

• Srikantan S. Nagarajan

• Noa Fogelson

• Sarang S. Dalal

• Ryan T. Canolty

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2011

DOI: 10.1162/jocn.2010.21466

PubMed: 20465359

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Abstract:

Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70-200 Hz) activity across the lateral hemisphere in less than 1 sec. The sequence demonstrated concurrent regional sensory processing of speech syllables in the posterior superior temporal gyrus (STG) and speech motor cortex, and then transitioned to sequential task-dependent processing from prefrontal cortex (PFC), to the final motor response in the hand sensorimotor cortex. STG activation was modestly enhanced for target over nontarget sounds, supporting a selective gain mechanism in early sensory processing, whereas PFC was entirely selective to targets, supporting its role in guiding response behavior. These results reveal that target detection is not a single cognitive event, but rather a process of progressive target selectivity that involves large-scale rapid parallel and serial processing in sensory, cognitive, and motor structures to support goal-directed human behavior.

The functional role of cross-frequency coupling

Authors:

• Ryan T. Canolty

• Robert T. Knight

Date: 2010

DOI: 10.1016/j.tics.2010.09.00

PubMed: 20932795

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Abstract:

Recent studies suggest that cross-frequency coupling (CFC) might play a functional role in neuronal computation, communication and learning. In particular, the strength of phase-amplitude CFC differs across brain areas in a task-relevant manner, changes quickly in response to sensory, motor and cognitive events, and correlates with performance in learning tasks. Importantly, whereas high-frequency brain activity reflects local domains of cortical processing, low-frequency brain rhythms are dynamically entrained across distributed brain regions by both external sensory input and internal cognitive events. CFC might thus serve as a mechanism to transfer information from large-scale brain networks operating at behavioral timescales to the fast, local cortical processing required for effective computation and synaptic modification, thus integrating functional systems across multiple spatiotemporal scales

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.

Spatiotemporal imaging of cortical activation during verb generation and picture naming

Authors:

• Erik Edwards

• Srikantan S. Nagarajan

• Sarang S. Dalal

• Ryan T. Canolty

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

DOI: 10.1016/j.neuroimage.2009.12.035.

PubMed: 20026224

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Abstract:

One hundred and fifty years of neurolinguistic research has identified the key structures in the human brain that support language. However, neither the classic neuropsychological approaches introduced by Broca (1861) and Wernicke (1874), nor modern neuroimaging employing PET and fMRI has been able to delineate the temporal flow of language processing in the human brain. We recorded the electrocorticogram (ECoG) from indwelling electrodes over left hemisphere language cortices during two common language tasks, verb generation and picture naming. We observed that the very high frequencies of the ECoG (high-gamma, 70–160 Hz) track language processing with spatial and temporal precision. Serial progression of activations is seen at a larger timescale, showing distinct stages of perception, semantic association/selection, and speech production. Within the areas supporting each of these larger processing stages, parallel (or “incremental”) processing is observed. In addition to the traditional posterior vs. anterior localization for speech perception vs. production, we provide novel evidence for the role of premotor cortex in speech perception and of Wernicke’s and surrounding cortex in speech production. The data are discussed with regards to current leading models of speech perception and production, and a “dual ventral stream” hybrid of leading speech perception models is given.

Cortical spatiotemporal dynamics underlying phonological target detection in humans

Authors:

• Edward F. Chang

• Erik Edwards

• Srikantan S. Nagarajan

• Noa Fogelson

• Sarang S. Dalal

• Ryan T. Canolty

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2010

DOI: 10.1162/jocn.2010.21466

PubMed: 20465359

View PDF

Abstract:

Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70–200 Hz) activity across the lateral hemisphere in less than 1 sec. The sequence demonstrated concurrent regional sensory processing of speech syllables in the posterior superior temporal gyrus (STG) and speech motor cortex, and then transitioned to sequential task-dependent processing from prefrontal cortex (PFC), to the final motor response in the hand sensorimotor cortex. STG activation was modestly enhanced for target over nontarget sounds, supporting a selective gain mechanism in early sensory processing, whereas PFC was entirely selective to targets, supporting its role in guiding response behavior. These results reveal that target detection is not a single cognitive event, but rather a process of progressive target selectivity that involves large-scale rapid parallel and serial processing in sensory, cognitive, and motor structures to support goal-directed human behavior.

Five-dimensional neuroimaging: localization of the time-frequency dynamics of cortical activity

Authors:

• Sarang S. Dalal

• Adrian G. Guggisberg

• Erik Edwards

• Kensuke Sekihara

• Anne M. Findlay

• Ryan T. Canolty

• Mitchel S. Berger

• Robert T. Knight

• Nicholas M. Barbaro

• Heidi E. Kirsch

• Srikantan S. Nagarajan

Date: 2008

DOI: 10.1016/j.neuroimage.2008.01.023

PubMed: 18356081

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Abstract:

The spatiotemporal dynamics of cortical oscillations across human brain regions remain poorly understood because of a lack of adequately validated methods for reconstructing such activity from noninvasive electrophysiological data. In this paper, we present a novel adaptive spatial filtering algorithm optimized for robust source time– frequency reconstruction from magnetoencephalography (MEG) and electroencephalography (EEG) data. The efficacy of the method is demonstrated with simulated sources and is also applied to real MEG data from a self-paced finger movement task. The algorithm reliably reveals modulations both in the beta band (12–30 Hz) and high gamma band (65–90 Hz) in sensorimotor cortex. The performance is validated by both across-subjects statistical comparisons and by intracranial electrocorticography (ECoG) data from two epilepsy patients. Inter- estingly, we also reliably observed high frequency activity (30–300 Hz) in the cerebellum, although with variable locations and frequencies across subjects. The proposed algorithm is highly parallelizable and runs efficiently on modern high-performance computing clusters. This method enables the ultimate promise of MEG and EEG for five- dimensional imaging of space, time, and frequency activity in the brain and renders it applicable for widespread studies of human cortical dynamics during cognition.

Spatiotemporal dynamics of word processing in the human brain

Authors:

• Ryan T. Canolty

• Maryam Soltani

• Sarang S. Dalal

• Erik Edwards

• Nina F. Dronkers

• Srikantan S. Nagarajan

• Heidi E. Kirsch

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2007

PubMed: 18982128

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Abstract:

We examined the spatiotemporal dynamics of word processing by recording the electrocorticogram (ECoG) from the lateral frontotemporal cortex of neurosurgical patients chronically implanted with subdural electrode grids. Subjects engaged in a target detection task where proper names served as infrequent targets embedded in a stream of task-irrelevant verbs and nonwords. Verbs described actions related to the hand (e.g, throw) or mouth (e.g., blow), while unintelligible nonwords were sounds which matched the verbs in duration, intensity, temporal modulation, and power spectrum. Complex oscillatory dynamics were observed in the delta, theta, alpha, beta, low, and high gamma (HG) bands in response to presentation of all stimulus types. HG activity (80-200 Hz) in the ECoG tracked the spatiotemporal dynamics of word processing and identified a network of cortical structures involved in early word processing. HG was used to determine the relative onset, peak, and offset times of local cortical activation during word processing. Listening to verbs compared to nonwords sequentially activates first the posterior superior temporal gyrus (post-STG), then the middle superior temporal gyrus (mid-STG), followed by the superior temporal sulcus (STS). We also observed strong phase-locking between pairs of electrodes in the theta band, with weaker phase-locking occurring in the delta, alpha, and beta frequency ranges. These results provide details on the first few hundred milliseconds of the spatiotemporal evolution of cortical activity during word processing and provide evidence consistent with the hypothesis that an oscillatory hierarchy coordinates the flow of information between distinct cortical regions during goal-directed behavior.

Spatial localization of cortical time-frequency dynamics

Authors:

• Sarang S. Dalal

• Adrian G. Guggisberg

• Erik Edwards

• Kensuke Sekihara

• Anne M. Findlay

• Ryan T. Canolty

• Robert T. Knight

• Nicholas M. Barbaro

• Heidi E. Kirsch

• Srikantan S. Nagarajan

Date: 2007

PubMed: 18003115

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Abstract:

The spatiotemporal dynamics of cortical oscillations across human brain regions remain poorly understood because of a lack of adequately validated methods for reconstructing such activity from noninvasive electrophysiological data. We present a novel adaptive spatial filtering algorithm optimized for robust source time-frequency reconstruction from magnetoencephalography (MEG) and electroencephalography (EEG) data. The efficacy of the method is demonstrated with real MEG data from a self-paced finger movement task. The algorithm reliably reveals modulations both in the beta band (12-30 Hz) and a high gamma band (65-90 Hz) in sensorimotor cortex. The performance is validated by both across-subjects statistical comparisons and by intracranial electrocorticography (ECoG) data from two epilepsy patients. We also revealed observed high gamma activity in the cerebellum. The proposed algorithm is highly parallelizable and runs efficiently on modern high performance computing clusters. This method enables non-invasive five-dimensional imaging of space, time, and frequency activity in the brain and renders it applicable for widespread studies of human cortical dynamics.

High Gamma Power is Phase-Locked to Theta Oscillations in Human Neocortex

Authors:

• Ryan T. Canolty

• Erik Edwards

• Sarang S. Dalal

• Maryam Soltani

• Srikantan S. Nagarajan

• Heidi E. Kirsch

• Mitchel S. Berger

• Nicholas M. Barbaro

• Robert T. Knight

Date: 2006

PubMed: 16973878

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Abstract:

We observed robust coupling between the high- and low-frequency bands of ongoing electrical activity in the human brain. In particular, the phase of the low-frequency theta (4 to 8 hertz) rhythm modulates power in the high gamma (80 to 150 hertz) band of the electrocorticogram, with stronger modulation occurring at higher theta amplitudes. Furthermore, different behavioral tasks evoke distinct patterns of theta/high gamma coupling across the cortex. The results indicate that transient coupling between low- and high-frequency brain rhythms coordinates activity in distributed cortical areas, providing a mechanism for effective communication during cognitive processing in humans.