Using Human Neuroimaging to Examine Top-down Modulation of Visual Perception

Sprague, Thomas C.; Serences, John T.

doi:10.1007/978-1-4939-2236-9_12

Cited by 11 publications

(10 citation statements)

References 95 publications

(176 reference statements)

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“…IEMs can be thought of as a form of targeted data reduction that allows for quantification of characteristics of the underlying feature-specific neural population, such as its response selectivity (Sprague & Serences, 2015). Figure 3A shows the temporal evolution of reconstructed channel tuning functions, with time points with significant selectivity marked with black squares.…”

Section: Resultsmentioning

confidence: 99%

“…Multivariate IEMs model the relationship between neural activity and stimulus features using hypothesized response profiles, which can then be used to reconstruct the neural representation of novel stimuli that vary with respect to the trained feature (Sprague & Serences, 2015). Previous work applying IEMs to fMRI data has been able to reconstruct the perception of and STM for basic visual features, such as color, orientation, and spatial location (Ester, Sprague, & Serences, 2015; Sprague, Ester, & Serences, 2014; Ester, Anderson, Serences, & Awh, 2013; Kok, Brouwer, van Gerven, & de Lange, 2013; Sprague & Serences, 2013; Ho et al, 2012; Scolari, Byers, & Serences, 2012; Brouwer & Heeger, 2009, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Decoding and Reconstructing the Focus of Spatial Attention from the Topography of Alpha-band Oscillations

Samaha

Sprague

Postle

2016

Journal of Cognitive Neuroscience

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148

141

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Many aspects of perception and cognition are supported by activity in neural populations that are tuned to different stimulus features (e.g., orientation, spatial location, color). Goal-directed behavior, such as sustained attention, requires a mechanism for the selective prioritization of contextually appropriate representations. A candidate mechanism of sustained spatial attention is neural activity in the alpha band (8–13 Hz), whose power in the human EEG covaries with the focus of covert attention. Here, we applied an inverted encoding model to assess whether spatially selective neural responses could be recovered from the topography of alpha-band oscillations during spatial attention. Participants were cued to covertly attend to one of six spatial locations arranged concentrically around fixation while EEG was recorded. A linear classifier applied to EEG data during sustained attention demonstrated successful classification of the attended location from the topography of alpha power, although not from other frequency bands. We next sought to reconstruct the focus of spatial attention over time by applying inverted encoding models to the topography of alpha power and phase. Alpha power, but not phase, allowed for robust reconstructions of the specific attended location beginning around 450 msec postcue, an onset earlier than previous reports. These results demonstrate that posterior alpha-band oscillations can be used to track activity in feature-selective neural populations with high temporal precision during the deployment of covert spatial attention.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decoding and Reconstructing the Focus of Spatial Attention from the Topography of Alpha-band Oscillations

Samaha

Sprague

Postle

2016

Journal of Cognitive Neuroscience

Self Cite

148

141

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show abstract

“…As exploratory analyses prompted by reviewers' comments, we used forward encoding models to investigate the spatial selectivity of visible and imagined representations across time. Encoding models can be used with neuroimaging data to investigate neural encoding of many visual feature dimensions (Sprague and Serences, 2015). Such models have been applied to fMRI data to assess encoding of features such as colour (Brouwer and Heeger, 2009), orientation (Scolari et al, 2012) and position (Sprague and Serences, 2013).…”

Section: Multivariate Encoding Analysesmentioning

confidence: 99%

Overlapping neural representations for the position of visible and imagined objects

Robinson

Grootswagers

Shatek

et al. 2020

Preprint

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AbstractHumans can covertly track the position of an object, even if the object is temporarily occluded. What are the neural mechanisms underlying our capacity to track moving objects when there is no physical stimulus for the brain to track? One possibility is that the brain “fills-in” information about imagined objects using internally generated representations similar to those generated by feed-forward perceptual mechanisms. Alternatively, the brain might deploy a higher order mechanism, for example using an object tracking model that integrates visual signals and motion dynamics (Kwon et al., 2015). In the present study, we used electroencephalography (EEG) and time-resolved multivariate pattern analyses to investigate the spatial processing of visible and imagined objects. Participants tracked an object that moved in discrete steps around fixation, occupying six consecutive locations. They were asked to imagine that the object continued on the same trajectory after it disappeared and move their attention to the corresponding positions. Time-resolved decoding of EEG data revealed that the location of the visible stimuli could be decoded shortly after image onset, consistent with early retinotopic visual processes. For processing of unseen/imagined positions, the patterns of neural activity resembled stimulus-driven mid-level visual processes, but were detected earlier than perceptual mechanisms, implicating an anticipatory and more variable tracking mechanism. Encoding models revealed that spatial representations were much less precise for imagined than visible stimuli. Monitoring the position of imagined objects thus utilises similar perceptual processes as processing objects that are actually present, but with different temporal dynamics. These results indicate that internally generated representations rely on top-down processes, and their timing is influenced by the predictability of the stimulus. All data and analysis code for this study are available at https://osf.io/8v47t/.

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“…According to so-called slot models, this limit arises due to a fixed number of discrete slots or information and desynchronization/excitation of populations coding relevant information (Noonan et al, 2016;Bacigalupo & Luck, 2019;Foster & Awh, 2019). Moreover, several studies have reconstructed features of the memorized target from the spatial pattern of alpha power during the maintenance interval (Sprague & Serences, 2015;Foster et al, 2016;Ester, Nouri & Rodriguez, 2018;Foster & Awh, 2019). This finding might suggest that alpha oscillations are involved in the maintenance of the targets rather than in the inhibition of distractors.…”

Section: Introductionmentioning

confidence: 99%

Lateralized alpha oscillations are irrelevant for the behavioral retro-cueing benefit in visual working memory

Mössing

Busch

2020

PeerJ

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The limited capacity of visual working memory (vWM) necessitates the efficient allocation of available resources by prioritizing relevant over irrelevant items. Retro-cues, which inform about the future relevance of items after encoding has already finished, can improve the quality of memory representations of the relevant items. A candidate mechanism of this retro-cueing benefit is lateralization of neural oscillations in the alpha-band, but its precise role is still debated. The relative decrease of alpha power contralateral to the relevant items has been interpreted as supporting inhibition of irrelevant distractors or as supporting maintenance of relevant items. Here, we aimed at resolving this debate by testing how the magnitude of alpha-band lateralization affects behavioral performance: does stronger lateralization improve the precision of the relevant memory or does it reduce the biasing influence of the irrelevant distractor? We found that it does neither: while the data showed a clear retro-cue benefit and a biasing influence of non-target items as well as clear cue-induced alpha-band lateralization, the magnitude of this lateralization was not correlated with any performance parameter. This finding may indicate that alpha-band lateralization, which is typically observed in response to mnemonic cues, indicates an automatic shift of attention that only coincides with, but is not directly involved in mnemonic prioritization.

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Using Human Neuroimaging to Examine Top-down Modulation of Visual Perception

Cited by 11 publications

References 95 publications

Decoding and Reconstructing the Focus of Spatial Attention from the Topography of Alpha-band Oscillations

Decoding and Reconstructing the Focus of Spatial Attention from the Topography of Alpha-band Oscillations

Overlapping neural representations for the position of visible and imagined objects

Lateralized alpha oscillations are irrelevant for the behavioral retro-cueing benefit in visual working memory

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