Our attentional focus is constantly shifting: in one moment our attention may be intently concent... more Our attentional focus is constantly shifting: in one moment our attention may be intently concentrated on a specific spot, while in another moment we might spread our attention more broadly. While much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is know about how we shift the aperture of attention from more narrowly-to more broadly-focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate—with varying degrees of certainty—approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that with decreasing certainty regarding the precise location of the impending target, participant response times increased while target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8-12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and response time nearly one second later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution, and how that influences behavior.
Oscillations are a prevalent feature of brain recordings. They are believed to play key roles in ... more Oscillations are a prevalent feature of brain recordings. They are believed to play key roles in neural communication and computation. Current analysis methods for studying neural oscillations often implicitly assume the oscillations are sinusoidal. While these approaches have proven fruitful, here we show that there are numerous instances in which neural oscillations are nonsinusoidal. We highlight approaches to characterize nonsinusoidal features and account for them in traditional spectral analysis. Rather than being a nuisance, we discuss how these nonsinusoidal features may provide critical, heretofore overlooked physiological information related to neural communication, computation, and cognition. Trends • Properties of neural oscillations are commonly correlated to disease or behavior states. These measures are mostly derived using traditional spectral analysis techniques that assume a sinusoidal basis. • Electrical recordings from many brain regions, at multiple spatial scales, exhibit neural oscillations that are nonsinusoidal. • New methods have been developed to quantify the nonsinusoidal features of oscillations and account for these features when using traditional spectral analysis. • Features of oscillatory waveform shape have been related to physiological processes and behaviors. • Manipulating features of stimulation waveforms changes the effects of rhythmic electrical stimulation.
Overview Modern science is creating data at an unprecedented rate, yet most of these data are bei... more Overview Modern science is creating data at an unprecedented rate, yet most of these data are being discarded. Raw scientific data, when they are published at all, are provided in a very limited form. Large, multidimensional datasets—rich with hidden information—are reduced to summary statistics filtered through limitations imposed by contemporary methods and technologies, and through the biased lens of the originating research group. The massive loss of raw data currently underway, and the lack of a system for discovering them, hinders scientific progress. In this Perspective, I argue that our contemporary limited view of the long-term scientific and medical benefits that could be made possible by data sharing masks the benefits for doing so. This, in turn, makes the costs of data sharing seem higher than they are.
Aging is associated with performance decrements across multiple cognitive domains. The neural noi... more 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.
Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control i... more Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4–8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80–150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.
Perception, cognition, and social interaction depend upon coordinated neural activity. This coord... more Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this paper we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity, and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders— including Parkinson’s disease, autism, depression, schizophrenia, and anxiety—are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural grey or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states, or their treatment, is a product of how these physical processes affect dynamic network communication.
Whereas neuroimaging studies of healthy subjects have demonstrated an association between the ant... more Whereas neuroimaging studies of healthy subjects have demonstrated an association between the anterior cingulate cortex (ACC) and cognitive control functions, including response monitoring and error detection, lesion studies are sparse and have produced mixed results. Due to largely normal behavioral test results in two patients with medial prefrontal lesions, a hypothesis has been advanced claiming that the ACC is not involved in cognitive operations. In the current study, two comparably rare patients with unilateral lesions to dorsal medial prefrontal cortex (MPFC) encompassing the ACC were assessed with neuropsychological tests as well as Event-Related Potentials in two experimental paradigms known to engage prefrontal cortex (PFC). These included an auditory Novelty Oddball task and a visual Stop-signal task. Both patients performed normally on the Stroop test but showed reduced performance on tests of learning and memory. Moreover, altered attentional control was reflected in a diminished Novelty P3, whereas the posterior P3b to target stimuli was present in both patients. The error-related negativity, which has been hypothesized to be generated in the ACC, was present in both patients, but alterations of inhibitory behavior were observed. Although interpretative caution is generally called for in single case studies, and the fact that the lesions extended outside the ACC, the findings nevertheless suggest a role for MPFC in cognitive control that is not restricted to error monitoring.► A case study with two unilateral lesions including anterior cingulate cortex (ACC) is presented. ► Neuropsychologically, both patients had memory impairment while Stroop performance was normal. ► Both patients had a diminished Novelty P3 Event Related Potential (ERP) in a Novelty Oddball task. ► Both patients had an Error-Related Negativity (ERN) ERP-component in a Stop-Signal task. ► The study suggests ACC involvement in cognition that is not restricted to error monitoring.
Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contain... more Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contains more than 21 million peer-reviewed articles with 40–50,000 more published every month. Understanding the human brain, cognition, and disease will require integrating facts from dozens of scientific fields spread amongst millions of studies locked away in static documents, making any such integration daunting, at best. The future of scientific progress will be aided by bridging the gap between the millions of published research articles and modern databases such as the Allen brain atlas (ABA). To that end, we have analyzed the text of over 3.5 million scientific abstracts to find associations between neuroscientific concepts. From the literature alone, we show that we can blindly and algorithmically extract a “cognome”: relationships between brain structure, function, and disease. We demonstrate the potential of data-mining and cross-platform data-integration with the ABA by introducing two methods for semi-automated hypothesis generation. By analyzing statistical “holes” and discrepancies in the literature we can find understudied or overlooked research paths. That is, we have added a layer of semi-automation to a part of the scientific process itself. This is an important step toward fundamentally incorporating data-mining algorithms into the scientific method in a manner that is generalizable to any scientific or medical field.► Understanding the human brain, cognition, and disease will require integrating millions of facts from dozens of fields. ► The peer-reviewed neuroscientific literature contains millions of articles, making any such integration daunting. ► Text-mining the peer-review literature allows us to automatically and statistically identify relationships between neuroscientific concepts. ► We introduce an algorithm that identifies possible new hypotheses. ► We have added a layer of semi-automation to a part of the scientific process itself by finding statistical anomalies in the peer-reviewed literature. ► We combined our data with the massive gene expression database made public with the Allen Brian Atlas to uncover biases in neuroscientific research.
Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local ... more Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local and long-distance neuronal communication. Current techniques for calculating PAC provide a numerical index that represents an average value across an arbitrarily long time period. This requires researchers to rely on block design experiments and temporal concatenation at the cost of the sub-second temporal resolution afforded by electrophysiological recordings. Here we present a method for calculating event-related phase/amplitude coupling (ERPAC) designed to capture the temporal evolution of task-related changes in PAC across events or between distant brain regions that is applicable to human or animal electromagnetic recording.► Event-related phase/amplitude coupling (ERPAC) enables time-resolved coupling. ► ERPAC is easy to instantiate for human and animal electrophysiology. ► ERPAC provides novel insight into the timing of brain dynamics. ► ERPAC can be used to assess the timing of coupling across brain regions.
Our attentional focus is constantly shifting: in one moment our attention may be intently concent... more Our attentional focus is constantly shifting: in one moment our attention may be intently concentrated on a specific spot, while in another moment we might spread our attention more broadly. While much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is know about how we shift the aperture of attention from more narrowly-to more broadly-focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate—with varying degrees of certainty—approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that with decreasing certainty regarding the precise location of the impending target, participant response times increased while target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8-12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and response time nearly one second later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution, and how that influences behavior.
Oscillations are a prevalent feature of brain recordings. They are believed to play key roles in ... more Oscillations are a prevalent feature of brain recordings. They are believed to play key roles in neural communication and computation. Current analysis methods for studying neural oscillations often implicitly assume the oscillations are sinusoidal. While these approaches have proven fruitful, here we show that there are numerous instances in which neural oscillations are nonsinusoidal. We highlight approaches to characterize nonsinusoidal features and account for them in traditional spectral analysis. Rather than being a nuisance, we discuss how these nonsinusoidal features may provide critical, heretofore overlooked physiological information related to neural communication, computation, and cognition. Trends • Properties of neural oscillations are commonly correlated to disease or behavior states. These measures are mostly derived using traditional spectral analysis techniques that assume a sinusoidal basis. • Electrical recordings from many brain regions, at multiple spatial scales, exhibit neural oscillations that are nonsinusoidal. • New methods have been developed to quantify the nonsinusoidal features of oscillations and account for these features when using traditional spectral analysis. • Features of oscillatory waveform shape have been related to physiological processes and behaviors. • Manipulating features of stimulation waveforms changes the effects of rhythmic electrical stimulation.
Overview Modern science is creating data at an unprecedented rate, yet most of these data are bei... more Overview Modern science is creating data at an unprecedented rate, yet most of these data are being discarded. Raw scientific data, when they are published at all, are provided in a very limited form. Large, multidimensional datasets—rich with hidden information—are reduced to summary statistics filtered through limitations imposed by contemporary methods and technologies, and through the biased lens of the originating research group. The massive loss of raw data currently underway, and the lack of a system for discovering them, hinders scientific progress. In this Perspective, I argue that our contemporary limited view of the long-term scientific and medical benefits that could be made possible by data sharing masks the benefits for doing so. This, in turn, makes the costs of data sharing seem higher than they are.
Aging is associated with performance decrements across multiple cognitive domains. The neural noi... more 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.
Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control i... more Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4–8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80–150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.
Perception, cognition, and social interaction depend upon coordinated neural activity. This coord... more Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this paper we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity, and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders— including Parkinson’s disease, autism, depression, schizophrenia, and anxiety—are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural grey or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states, or their treatment, is a product of how these physical processes affect dynamic network communication.
Whereas neuroimaging studies of healthy subjects have demonstrated an association between the ant... more Whereas neuroimaging studies of healthy subjects have demonstrated an association between the anterior cingulate cortex (ACC) and cognitive control functions, including response monitoring and error detection, lesion studies are sparse and have produced mixed results. Due to largely normal behavioral test results in two patients with medial prefrontal lesions, a hypothesis has been advanced claiming that the ACC is not involved in cognitive operations. In the current study, two comparably rare patients with unilateral lesions to dorsal medial prefrontal cortex (MPFC) encompassing the ACC were assessed with neuropsychological tests as well as Event-Related Potentials in two experimental paradigms known to engage prefrontal cortex (PFC). These included an auditory Novelty Oddball task and a visual Stop-signal task. Both patients performed normally on the Stroop test but showed reduced performance on tests of learning and memory. Moreover, altered attentional control was reflected in a diminished Novelty P3, whereas the posterior P3b to target stimuli was present in both patients. The error-related negativity, which has been hypothesized to be generated in the ACC, was present in both patients, but alterations of inhibitory behavior were observed. Although interpretative caution is generally called for in single case studies, and the fact that the lesions extended outside the ACC, the findings nevertheless suggest a role for MPFC in cognitive control that is not restricted to error monitoring.► A case study with two unilateral lesions including anterior cingulate cortex (ACC) is presented. ► Neuropsychologically, both patients had memory impairment while Stroop performance was normal. ► Both patients had a diminished Novelty P3 Event Related Potential (ERP) in a Novelty Oddball task. ► Both patients had an Error-Related Negativity (ERN) ERP-component in a Stop-Signal task. ► The study suggests ACC involvement in cognition that is not restricted to error monitoring.
Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contain... more Modern neuroscientific research stands on the shoulders of countless giants. PubMed alone contains more than 21 million peer-reviewed articles with 40–50,000 more published every month. Understanding the human brain, cognition, and disease will require integrating facts from dozens of scientific fields spread amongst millions of studies locked away in static documents, making any such integration daunting, at best. The future of scientific progress will be aided by bridging the gap between the millions of published research articles and modern databases such as the Allen brain atlas (ABA). To that end, we have analyzed the text of over 3.5 million scientific abstracts to find associations between neuroscientific concepts. From the literature alone, we show that we can blindly and algorithmically extract a “cognome”: relationships between brain structure, function, and disease. We demonstrate the potential of data-mining and cross-platform data-integration with the ABA by introducing two methods for semi-automated hypothesis generation. By analyzing statistical “holes” and discrepancies in the literature we can find understudied or overlooked research paths. That is, we have added a layer of semi-automation to a part of the scientific process itself. This is an important step toward fundamentally incorporating data-mining algorithms into the scientific method in a manner that is generalizable to any scientific or medical field.► Understanding the human brain, cognition, and disease will require integrating millions of facts from dozens of fields. ► The peer-reviewed neuroscientific literature contains millions of articles, making any such integration daunting. ► Text-mining the peer-review literature allows us to automatically and statistically identify relationships between neuroscientific concepts. ► We introduce an algorithm that identifies possible new hypotheses. ► We have added a layer of semi-automation to a part of the scientific process itself by finding statistical anomalies in the peer-reviewed literature. ► We combined our data with the massive gene expression database made public with the Allen Brian Atlas to uncover biases in neuroscientific research.
Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local ... more Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local and long-distance neuronal communication. Current techniques for calculating PAC provide a numerical index that represents an average value across an arbitrarily long time period. This requires researchers to rely on block design experiments and temporal concatenation at the cost of the sub-second temporal resolution afforded by electrophysiological recordings. Here we present a method for calculating event-related phase/amplitude coupling (ERPAC) designed to capture the temporal evolution of task-related changes in PAC across events or between distant brain regions that is applicable to human or animal electromagnetic recording.► Event-related phase/amplitude coupling (ERPAC) enables time-resolved coupling. ► ERPAC is easy to instantiate for human and animal electrophysiology. ► ERPAC provides novel insight into the timing of brain dynamics. ► ERPAC can be used to assess the timing of coupling across brain regions.
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Papers by Bradley Voytek