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Updated: May 6, 2026

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
Published on: June 12, 2017
Alpha phase coding supports feature binding during working memory maintenance
Mattia F Pagnotta1, Aniol Santo-Angles2, Ainsley Temudo2,3
1Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA. pagnotta@berkeley.edu.
Neural phase synchrony is key for binding features in working memory (WM). Disruptions in this synchrony lead to binding errors, revealing WM capacity limits and the role of alpha-band oscillations.
Area of Science:
- Cognitive Neuroscience
- Neuroscience
Background:
- Working memory (WM) relies on binding object features into unified representations.
- The precise neural mechanisms for feature binding and the cause of binding errors remain largely unknown.
- Binding errors, where features are incorrectly associated, highlight limitations in WM capacity.
Purpose of the Study:
- To investigate the role of neural phase synchrony in working memory feature binding.
- To test the hypothesis that binding errors stem from perturbations in neural synchrony.
- To elucidate the neural dynamics underlying feature binding and WM capacity limitations.
Main Methods:
- Utilized magnetoencephalography (MEG) to record brain activity in human subjects.
- Employed a cognitive task specifically designed to elicit binding (swap) errors in working memory.
- Analyzed phase-locked oscillatory activity and phase coding variability during memory retention.
Main Results:
- Swap errors were associated with reduced phase-locked oscillatory activity during WM retention.
- This reduction aligns with predictions from attractor models of spiking neural networks.
- Increased phase coding variability in the alpha-band over sensorimotor areas characterized swap errors.
Conclusions:
- Neural phase synchrony is a critical mechanism for feature binding in working memory.
- Binding errors arise from disruptions and increased variability in phase coding dynamics.
- These findings suggest that feature binding emerges from neural competition within a distributed network.
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