Neural dynamics of visual ambiguity resolution by perceptual prior
Abstract
Past experiences have enormous power in shaping our daily perception. Currently, dynamical neural mechanisms underlying this process remain mysterious. Exploiting a dramatic visual phenomenon, where a single experience of viewing a clear image allows instant recognition of a related degraded image, we investigated this question using MEG and 7 Tesla fMRI in humans. We observed that following the acquisition of perceptual priors, different degraded images are represented much more distinctly in neural dynamics starting from ~500 ms after stimulus onset. Content-specific neural activity related to stimulus-feature processing dominated within 300 ms after stimulus onset, while content-specific neural activity related to recognition processing dominated from 500 ms onward. Model-driven MEG-fMRI data fusion revealed the spatiotemporal evolution of neural activities involved in stimulus, attentional, and recognition processing. Together, these findings shed light on how experience shapes perceptual processing across space and time in the brain.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
National Institute of Neurological Disorders and Stroke
- Biyu J He
Klingenstein-Simons Neuroscience Fellowship
- Biyu J He
Department of State Fulbright program
- Carlos González-García
National Science Foundation (BCS-1753218)
- Biyu J He
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Christian Büchel, University Medical Center Hamburg-Eppendorf, Germany
Ethics
Human subjects: The experiment was approved by the Institutional Review Board of the National Institute of Neurological Disorders and Stroke (under protocol #14-N-0002). All subjects provided written informed consent.
Version history
- Received: September 9, 2018
- Accepted: February 25, 2019
- Accepted Manuscript published: March 7, 2019 (version 1)
- Version of Record published: March 13, 2019 (version 2)
Copyright
© 2019, Flounders et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,986
- views
-
- 392
- downloads
-
- 36
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here, we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between ‘bimodal cells’ showing interleaved phase precession and procession, and ‘unimodal cells’ in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells’ firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.
-
- Neuroscience
Learning requires the ability to link actions to outcomes. How motivation facilitates learning is not well understood. We designed a behavioral task in which mice self-initiate trials to learn cue-reward contingencies and found that the anterior cingulate region of the prefrontal cortex (ACC) contains motivation-related signals to maximize rewards. In particular, we found that ACC neural activity was consistently tied to trial initiations where mice seek to leave unrewarded cues to reach reward-associated cues. Notably, this neural signal persisted over consecutive unrewarded cues until reward-associated cues were reached, and was required for learning. To determine how ACC inherits this motivational signal we performed projection-specific photometry recordings from several inputs to ACC during learning. In doing so, we identified a ramp in bulk neural activity in orbitofrontal cortex (OFC)-to-ACC projections as mice received unrewarded cues, which continued ramping across consecutive unrewarded cues, and finally peaked upon reaching a reward-associated cue, thus maintaining an extended motivational state. Cellular resolution imaging of OFC confirmed these neural correlates of motivation, and further delineated separate ensembles of neurons that sequentially tiled the ramp. Together, these results identify a mechanism by which OFC maps out task structure to convey an extended motivational state to ACC to facilitate goal-directed learning.