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Neural decoding of visual stimuli varies with fluctuations in global network efficiency.

ABSTRACT: Functional magnetic resonance imaging (fMRI) studies have shown that neural activity fluctuates spontaneously between different states of global synchronization over a timescale of several seconds. Such fluctuations generate transient states of high and low correlation across distributed cortical areas. It has been hypothesized that such fluctuations in global efficiency might alter patterns of activity in local neuronal populations elicited by changes in incoming sensory stimuli. To test this prediction, we used a linear decoder to discriminate patterns of neural activity elicited by face and motion stimuli presented periodically while participants underwent time-resolved fMRI. As predicted, decoding was reliably higher during states of high global efficiency than during states of low efficiency, and this difference was evident across both visual and nonvisual cortical regions. The results indicate that slow fluctuations in global network efficiency are associated with variations in the pattern of activity across widespread cortical regions responsible for representing distinct categories of visual stimulus. More broadly, the findings highlight the importance of understanding the impact of global fluctuations in functional connectivity on specialized, stimulus driven neural processes. Hum Brain Mapp 38:3069-3080, 2017. © 2017 Wiley Periodicals, Inc.

SUBMITTER: Cocchi L

PROVIDER: S-EPMC6866876 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Neural decoding of visual stimuli varies with fluctuations in global network efficiency.

Cocchi Luca L Yang Zhengyi Z Zalesky Andrew A Stelzer Johannes J Hearne Luke J LJ Gollo Leonardo L LL Mattingley Jason B JB

Human brain mapping 20170325 6

Functional magnetic resonance imaging (fMRI) studies have shown that neural activity fluctuates spontaneously between different states of global synchronization over a timescale of several seconds. Such fluctuations generate transient states of high and low correlation across distributed cortical areas. It has been hypothesized that such fluctuations in global efficiency might alter patterns of activity in local neuronal populations elicited by changes in incoming sensory stimuli. To test this p ...[more]

PMID: 28342260

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Project description:Contextual information triggers predictions about the content ("what") of environmental stimuli to update an internal generative model of the surrounding world. However, visual information dynamically changes across time, and temporal predictability ("when") may influence the impact of internal predictions on visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information ("what") is affected by temporal predictability ("when"). Participants (N = 16) were presented with four consecutive Gabor patches (entrainers) with constant spatial frequency but with variable orientation and temporal onset. A fifth target Gabor was presented after a longer delay and with higher or lower spatial frequency that participants had to judge. We compared the neural responses to entrainers where the Gabor orientation could, or could not be temporally predicted along the entrainer sequence, and with inter-entrainer timing that was constant (predictable), or variable (unpredictable). We observed suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early visual responses, with the feature specificity of early visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable visual stimuli. These findings converge to suggest that the cognitive system processes visual features of temporally predictable stimuli in higher detail, while processing temporally uncertain stimuli may rely more heavily on abstract internal expectations.

Dataset Information

Neural decoding of visual stimuli varies with fluctuations in global network efficiency.

Publications

Neural decoding of visual stimuli varies with fluctuations in global network efficiency.

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