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Laminar Organization of Working Memory Signals in Human Visual Cortex
Samuel J D Lawrence1, Tim van Mourik1, Peter Kok2
1Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
Current Biology : CB
|October 23, 2018
Summary
Top-down signals in visual working memory are organized differently in the human brain. Research shows these internally generated signals are selectively present in deep and superficial layers of the primary visual cortex (V1).
Area of Science:
- Neuroscience
- Cognitive Neuroscience
- Visual Perception
Background:
- The human primary visual cortex (V1) processes both incoming visual data and top-down cognitive signals, like visual working memory.
- Top-down signals are crucial for visualizing features, as higher-order regions lack specific representational capacity.
- Internally generated signals must be organized differently from bottom-up signals to avoid triggering genuine perception.
Purpose of the Study:
- To investigate the laminar organization of internally generated signals during visual working memory in the human visual system.
- To understand how bottom-up and top-down signals are deployed within the visual cortex.
Main Methods:
- Utilized lamina-resolved functional magnetic resonance imaging (fMRI).
- Simultaneously measured activity in early visual areas (V1-V3) during visual working memory tasks.
- Analyzed the spatial distribution of item-specific working memory signals across cortical layers.
Main Results:
- Observed item-specific working memory signals in early visual cortex (V1-V3).
- In V1, these signals were selectively found in deep and superficial cortical layers, avoiding middle layers.
- Working memory activity was present across all depths in V2 and V3.
Conclusions:
- Demonstrated the distinct laminar organization of internally generated signals in the human visual cortex during working memory.
- Provided novel insights into the differential deployment of bottom-up and top-down signals in visual processing.
- Suggests a mechanism for separating sensory input from internally generated representations based on cortical layer specificity.
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