ArticleJournal of cognitive neuroscience2022
Using High-Density Electroencephalography to Explore Spatiotemporal Representations of Object Categories in Visual Cortex.
Article in Journal of cognitive neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Increasing EEG electrode density improves decoding of visual categories and source localization: an exploratory ultra-high-density EEG study.Communications engineering · 2026Article
- Trait anxiety is associated with reduced reward-related replay at rest.Nature communications · 2025Article
- Using multivariate pattern analysis to increase effect sizes for event-related potential analyses.Psychophysiology · 2024Article
- Using Multivariate Pattern Analysis to Increase Effect Sizes for Event-Related Potential Analyses.bioRxiv : the preprint server for biology · 2024Article
- Temporal differences and commonalities between hand and tool neural processing.Scientific reports · 2023Article
- The Architecture of Object-Based Attention.Psychonomic bulletin & review · 2023Review
- Temporal asymmetries and interactions between dorsal and ventral visual pathways during object recognition.Cerebral cortex communications · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
Visual object perception involves neural processes that unfold over time and recruit multiple regions of the brain. Here, we use high-density EEG to investigate the spatiotemporal representations of object categories across the dorsal and ventral pathways. In , human participants were presented with images from two animate object categories (birds and insects) and two inanimate categories (tools and graspable objects). In , participants viewed images of tools and graspable objects from a different stimulus set, one in which a shape confound that often exists between these categories (elongation) was controlled for. To explore the temporal dynamics of object representations, we employed time-resolved multivariate pattern analysis on the EEG time series data. This was performed at the electrode level as well as in source space of two regions of interest: one encompassing the ventral pathway and another encompassing the dorsal pathway. Our results demonstrate shape, exemplar, and category information can be decoded from the EEG signal. Multivariate pattern analysis within source space revealed that both dorsal and ventral pathways contain information pertaining to shape, inanimate object categories, and animate object categories. Of particular interest, we note striking similarities obtained in both ventral stream and dorsal stream regions of interest. These findings provide insight into the spatio-temporal dynamics of object representation and contribute to a growing literature that has begun to redefine the traditional role of the dorsal pathway.
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