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Bradley Voytek

Publications and source records attributed to Bradley Voytek.

4 recordsLinked to original sources

Preparatory encoding of the fine scale of human spatial attention

Our attentional focus is constantly shifting: in one moment our vision 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, N1 amplitude in response to the cue parametrically increased with spatial certainty while the multivariate pattern of preparatory period visual cortical alpha (8-12 Hz) activity encoded attentional distribution. Both of these electrophysiological parameters were predictive of behavioral performance 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.\n\nAuthors contributionsB.V. and A.G. conceived of the study; B.V. and A.G. designed the experimental task; B.V. and J.S. analyzed the EEG data; B.V., J.S., Z.G., N.G., S.P., T.K., S.R., and R.M. collected and analyzed behavioral data; all co-authors assisted in writing the manuscript.\n\nB.V. is funded by an NIH IRACDA (Institutional Research and Academic Career Development Award), a University of California Presidential Postdoctoral Fellowship, the University of California, San Diego CalIt2 Strategic Research Opportunities Program, and a Sloan Research Fellowship. A.G. is funded by the National Institutes of Health Grant R01-AG30395.\n\nSignificant StatementAnimals--including humans--frequently shift their visual attentional focus more narrowly or broadly depending on expectations. For example, a predator feline may focus their visual attention on a burrow hole, waiting for their prey to emerge. In contrast, a grizzly bear hunting salmon doesn't know precisely where the fish will jump out of the water, so it must spread its attention more broadly. In a series of novel experiments, we show that this broadening of attention comes at a behavioral cost. We find that multivariate changes in preparatory visual cortical oscillatory alpha (8-12 Hz) encode attentional distribution. These results shed light on the potential neural mechanisms by which preparatory information is used to guide attentional focus.

Neuroscience

Alpha Phase Dynamics Predict Age-Related Visual Working Memory Decline

Alpha oscillations are modulated in response to visual temporal and spatial cues, However, the neural response to alerting cues is less explored, as is how this response is affected by healthy aging. Using scalp EEG, we examined how visual cortical alpha activity relates to working memory performance. Younger (20-30 years) and older (60-70 years) participants were presented with a visual alerting cue uninformative of the position or size of a lateralized working memory array. Older adults showed longer response times overall, and reduced accuracy when memory load was high. Older adults had less consistent cue-evoked phase resetting than younger adults, which predicted worse performance. Alpha phase prior to memory array presentation predicted response time, but the relationship between phase and response time was weaker in older adults. These results suggest that changes in alpha phase dynamics, especially prior to presentation of task-relevant stimuli, potentially contribute to age-related cognitive decline.

Neuroscience

Nonsinusoidal oscillations underlie pathological phase-amplitude coupling in the motor cortex in Parkinson’s disease

Parkinsons disease (PD) is associated with abnormal beta oscillations (13-30 Hz) in the basal ganglia and motor cortex (M1). Recent reports show that M1 beta-high gamma (50-200 Hz) phase-amplitude coupling (PAC) is exaggerated in PD and is reduced following acute deep brain stimulation (DBS). Here we analyze invasive M1 electrocorticography recordings in PD patients on and off DBS, and in isolated cervical dystonia patients, and show that M1 beta oscillations are nonsinusoidal, having sharp and asymmetric features. These sharp oscillatory beta features underlie the previously reported PAC, providing an alternative to the standard interpretation of PAC as an interaction between two distinct frequency components. Specifically, the ratio between peak and trough sharpness is nearly perfectly correlated with beta-high gamma PAC (r = 0.96) and predicts PD-related motor deficit. Using a simulation of the local field potential, we demonstrate that sharp oscillatory waves can arise from synchronous synaptic activity. We propose that exaggerated beta-high gamma PAC may actually reflect such synchronous synaptic activity, manifesting as sharp beta oscillations that are \"smoothed out\" with DBS. These results support the \"desynchronization\" hypothesis of DBS wherein DBS counteracts pathological synchronization throughout the basal ganglia-thalamocortical loop. We argue that PAC can be influenced by more than one mechanism. In this case synaptic synchrony, rather than the often assumed spike-field coherence, may underlie exaggerated PAC. These often overlooked temporal features of the oscillatory waveform carry critical physiological information about neural processes and dynamics that may lead to better understanding of underlying neuropathology.

Neuroscience

Balanced Oscillatory Coupling Improves Information Flow

All animals are able to rapidly change their behavior. The neural basis of such flexibility requires that groups of distant neural ensembles rapidly alter communications with selectivity and fidelity. Low frequency oscillations are a strong candidate for how neurons coordinate communication via the dynamic instantiation of functional networks. These dynamic networks are argued to rapidly guide the flow of information, with the presumption that stronger oscillations more strongly influence information flow. Surprisingly, there is scant evidence or theoretical support for how oscillatory activity might enhance information flow. Here we introduce a novel computational model for oscillatory neural communication and show that, rather than the strength of the oscillation, it is the balance between excitatory and inhibitory neuronal activity that has the largest effect on information flow. When coupling between an oscillation and spiking has balanced excitatory-inhibitory inputs, information flow is enhanced via improved discriminability between signal and noise. In contrast, when coupling is unbalanced, driven either by excessive excitation or inhibition, information flow is obstructed, regardless of the strength of the oscillation. A multitude of neuropathologies, including Parkinsons disease, schizophrenia, and autism, are associated with oscillatory disruptions and excitation-inhibition imbalances. Our results show that understanding the distinction between balanced and unbalanced oscillatory coupling offers a unifying mechanistic framework for understanding effective neural communication and its disruption in neuropathology.

Neuroscience