Very high density EEG elucidates spatiotemporal aspects of early visual processing

Robinson, Amanda K.; Venkatesh, Praveen; Boring, Matthew J.; Tarr, Michael J.; Grover, Pulkit; Behrmann, Marlene

doi:10.1038/s41598-017-16377-3

Cited by 57 publications

(48 citation statements)

References 29 publications

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“…One factor that might have influenced our ability to decode information during imagery, however, is the density of channels; most prior experiments use a greater number of channels than the 64 we had (128 EEG channels in [51] and 256 MEG channels in Dijkstra et al (2018) [3]). This increased number of channels may provide better signal to noise ratio and increase chances of finding an effect [52]. An additional consideration is that individual variability in image generation would reduce the sensitivity of population statistics.…”

Section: Discussionmentioning

confidence: 99%

Decoding Images in the Mind’s Eye: The Temporal Dynamics of Visual Imagery

Shatek

Grootswagers

Robinson

et al. 2019

Vision

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Mental imagery is the ability to generate images in the mind in the absence of sensory input. Both perceptual visual processing and internally generated imagery engage large, overlapping networks of brain regions. However, it is unclear whether they are characterized by similar temporal dynamics. Recent magnetoencephalography work has shown that object category information was decodable from brain activity during mental imagery, but the timing was delayed relative to perception. The current study builds on these findings, using electroencephalography to investigate the dynamics of mental imagery. Sixteen participants viewed two images of the Sydney Harbour Bridge and two images of Santa Claus. On each trial, they viewed a sequence of the four images and were asked to imagine one of them, which was cued retroactively by its temporal location in the sequence. Time-resolved multivariate pattern analysis was used to decode the viewed and imagined stimuli. Although category and exemplar information was decodable for viewed stimuli, there were no informative patterns of activity during mental imagery. The current findings suggest stimulus complexity, task design and individual differences may influence the ability to successfully decode imagined images. We discuss the implications of these results in the context of prior findings of mental imagery.

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Section: Discussionmentioning

confidence: 99%

Decoding Images in the Mind’s Eye: The Temporal Dynamics of Visual Imagery

Shatek

Grootswagers

Robinson

et al. 2019

Vision

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“…This study takes advantage of the findings from Robinson et al [30] in which we used decoding analyses in typical individuals to measure EEG responses to checkerboard stimuli (see Figure 1). In that study, we used checkerboard displays that differed in spatial frequency (low, medium and high) that could appear in either the left or the right visual field.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of Types of Visual Agnosia Using EEG

Haigh

Robinson

Grover

et al. 2018

Vision

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Visual recognition deficits are the hallmark symptom of visual agnosia, a neuropsychological disorder typically associated with damage to the visual system. Most research into visual agnosia focuses on characterizing the deficits through detailed behavioral testing, and structural and functional brain scans are used to determine the spatial extent of any cortical damage. Although the hierarchical nature of the visual system leads to clear predictions about the temporal dynamics of cortical deficits, there has been little research on the use of neuroimaging methods with high temporal resolution to characterize the temporal profile of agnosia deficits. Here, we employed high-density electroencephalography (EEG) to investigate alterations in the temporal dynamics of the visual system in two individuals with visual agnosia. In the context of a steady state visual evoked potential paradigm (SSVEP), individuals viewed pattern-reversing checkerboards of differing spatial frequency, and we assessed the responses of the visual system in the frequency and temporal domain. JW, a patient with early visual cortex damage, showed impaired SSVEP response relative to a control group and to the second patient (SM) who had right temporal lobe damage. JW also showed lower decoding accuracy for early visual responses (around 100 ms). SM, whose lesion is more anterior in the visual system, showed good decoding accuracy initially but low decoding after 500 ms. Overall, EEG and multivariate decoding methods can yield important insights into the temporal dynamics of visual responses in individuals with visual agnosia.

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“…The current investigation exploited high-density EEG, which may have been instrumental to attaining signal localization to cortical regions sufficiently accurate to replicate previous HMM-based pattern decomposition of MEG data 16,78 . Whereas EEG consistently achieves as high temporal resolution as MEG, the present investigation is one of a relatively small subset of studies in which high-density EEG afforded good spatial resolution [79][80][81] .…”

Section: Discussionmentioning

confidence: 99%

Spontaneous activity changes in large-scale cortical networks in older adults couple to distinct hemodynamic morphology

Sitnikova

Hughes

Howard

et al. 2020

Preprint

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Neurovascular coupling is a dynamic core mechanism supporting brain energy demand. Therefore, even spontaneous changes in neural activity not linked directly to goal-directed behavior are expected to evoke a vascular hemodynamic response (HDR). Here, we developed a novel procedure for estimating transient neural activity states based on source-localized electroencephalogram (EEG) in combination with HDR estimation based on simultaneously acquired functional magnetic resonance imaging (fMRI). We demonstrate a readily apparent spatial correspondence between electrophysiological neural states and time-locked local HDR during rest, describing for the first time how features of neurovascular coupling may differ among unique large-scale brain networks. In the default mode network, the HDR pattern in our sample of older adults was associated with a structural surrogate marker of general cerebrovascular deterioration and predicted temporal disruption in electrophysiological activity linked to memory decline. These results demonstrate the potential of our integrated EEG/fMRI analysis for making inferences about neural and vascular processes in higher-level cognitive networks in healthy and at-risk populations.Intrinsic neural activity not explicitly associated with performing a task is an indicator of brain health. However, our understanding of how natural activity patterns arise is far from complete. The consequences of dysregulated intrinsic neuronal firing on life-sustaining cellular processes, such as gene expression and protein synthesis, are highlighted by animal models 1 . In the human brain, large-scale recordings at the cell population level link abnormal intrinsic neural activity to the progression of brain disorders, such as Alzheimer's dementia [2][3][4] . Much of what we know about intrinsic neural activity in humans comes from functional magnetic resonance imaging (fMRI), which relies on neurovascular coupling to make inferences about neural activity 5 . Inherently, variations both in neural activity and responsiveness of the associated vascular support, which is the signal detected by this imaging technique, can influence patterns in fMRI data, especially in the aging brain prone to cerebrovascular changes and patients with brain disorders accompanied by vascular comorbidities 6,7 . Therefore, new procedures for disambiguating between the neural and hemodynamic features in the human brain are needed.Studies using fMRI have demonstrated that large-scale brain networks recruited by tasks are also spontaneously reactivated during resting state [8][9][10][11] . Two recent analytic approaches, focusing on electrophysiological correlates of neural activity that are temporally resolved on rapid scales of cognition 12 , suggested that such spontaneous reactivations may constitute transient states of network activity coupled to local vascular hemodynamic response (HDR). First, a novel mathematical tool based on the Hidden Markov Model (HMM) discerned recurring transient states of spatially coordinated amplitude chan...

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Very high density EEG elucidates spatiotemporal aspects of early visual processing

Cited by 57 publications

References 29 publications

Decoding Images in the Mind’s Eye: The Temporal Dynamics of Visual Imagery

Decoding Images in the Mind’s Eye: The Temporal Dynamics of Visual Imagery

Differentiation of Types of Visual Agnosia Using EEG

Spontaneous activity changes in large-scale cortical networks in older adults couple to distinct hemodynamic morphology

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