Decoding Color Visual Working Memory from EEG Signals Using Graph Convolutional Neural Networks

2021 ◽  
Author(s):  
Xiaowei Che ◽  
Yuanjie Zheng ◽  
Xin Chen ◽  
Sutao Song ◽  
Shouxin Li
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Neural Coding ◽  
Memory Performance ◽  
Eeg Signals ◽  
Convolutional Network ◽  
Convolutional Networks ◽  
Behavioral Measurement ◽  
Scalp Electroencephalogram ◽  
Decoding Accuracy

Color has an important role in object recognition and visual working memory (VWM). Decoding color VWM in the human brain is helpful to understand the mechanism of visual cognitive process and evaluate memory ability. Recently, several studies showed that color could be decoded from scalp electroencephalogram (EEG) signals during the encoding stage of VWM, which process visible information with strong neural coding. Whether color could be decoded from other VWM processing stages, especially the maintaining stage which processes invisible information, is still unknown. Here, we constructed an EEG color graph convolutional network model (ECo-GCN) to decode colors during different VWM stages. Based on graph convolutional networks, ECo-GCN considers the graph structure of EEG signals and may be more efficient in color decoding. We found that (1) decoding accuracies for colors during the encoding, early, and late maintaining stages were 81.58%, 79.36%, and 77.06%, respectively, exceeding those during the pre-stimuli stage (67.34%), and (2) the decoding accuracy during maintaining stage could predict participants’ memory performance. The results suggest that EEG signals during the maintaining stage may be more sensitive than behavioral measurement to predict the VWM performance of human, and ECo-GCN provides an effective approach to explore human cognitive function.

Greater Visual Working Memory Capacity for Visually Matched Stimuli When They Are Perceived as Meaningful

2021 ◽  
Vol 33 (5) ◽  
pp. 902-918 ◽  
Author(s):  
Isabel E. Asp ◽  
Viola S. Störmer ◽  
Timothy F. Brady
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Visual Information ◽  
Memory Performance ◽  
Working Memory Capacity ◽  
Visual Complexity ◽  
Memory Capacity ◽  
Subjective Perception ◽  
Neural Delay ◽  
Meaningful Stimuli

Abstract Almost all models of visual working memory—the cognitive system that holds visual information in an active state—assume it has a fixed capacity: Some models propose a limit of three to four objects, where others propose there is a fixed pool of resources for each basic visual feature. Recent findings, however, suggest that memory performance is improved for real-world objects. What supports these increases in capacity? Here, we test whether the meaningfulness of a stimulus alone influences working memory capacity while controlling for visual complexity and directly assessing the active component of working memory using EEG. Participants remembered ambiguous stimuli that could either be perceived as a face or as meaningless shapes. Participants had higher performance and increased neural delay activity when the memory display consisted of more meaningful stimuli. Critically, by asking participants whether they perceived the stimuli as a face or not, we also show that these increases in visual working memory capacity and recruitment of additional neural resources are because of the subjective perception of the stimulus and thus cannot be driven by physical properties of the stimulus. Broadly, this suggests that the capacity for active storage in visual working memory is not fixed but that more meaningful stimuli recruit additional working memory resources, allowing them to be better remembered.

scholarly journals Anticipatory alpha phase influences visual working memory performance

NeuroImage ◽  
2014 ◽  
Vol 85 ◽  
pp. 794-802 ◽  
Author(s):  
Theodore P. Zanto ◽  
James Z. Chadick ◽  
Adam Gazzaley
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Memory Performance ◽  
Alpha Phase

scholarly journals Separating memoranda in depth increases visual working memory performance

2019 ◽  
Vol 19 (1) ◽  
pp. 4 ◽  
Author(s):  
Chaipat Chunharas ◽  
Rosanne L. Rademaker ◽  
Thomas C. Sprague ◽  
Timothy F. Brady ◽  
John T. Serences
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Memory Performance

scholarly journals Visual working memory performance in aphantasia

Cortex ◽  
2018 ◽  
Vol 105 ◽  
pp. 61-73 ◽  
Author(s):  
Christianne Jacobs ◽  
Dietrich S. Schwarzkopf ◽  
Juha Silvanto
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Memory Performance

scholarly journals Atypical development of visual working memory performance in autism spectrum disorder

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Beatriz Luna ◽  
Kirsten O'Hearn
Keyword(s):  
Autism Spectrum Disorder ◽  
Working Memory ◽  
Visual Working Memory ◽  
Memory Performance ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Childhood And Adolescence ◽  
Visual Feature ◽  
Performance Differences ◽  
Atypical Development

Visual working memory (VWM) typically improves across childhood and adolescence. Yet, it remains unclear whether such improvement occurs in autism (ASD). We measured color, shape, and pattern VWM performance in children (N=49; Mage=11y; 41 males), adolescents (N=46; Mage=15y; 38 males), and adults (N=51; Mage=24y; 47 males) with and without ASD (91% White, 6% Black or multiracial). By adulthood, color VWM accuracy among 4 items was better in the TD group relative to ASD (p2=.039). In childhood, shape VWM RT among 8 items was faster in the TD group relative to ASD (p2=.063). While VWM capacity was intact in ASD, VWM performance differences between ASD and TD may depend on age and visual feature.

scholarly journals Naturalistic coding of working memory in primate prefrontal cortex

2020 ◽  
Author(s):  
Megan Roussy ◽  
Rogelio Luna ◽  
Lyndon Duong ◽  
Benjamin Corrigan ◽  
Roberto A. Gulli ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Memory Performance ◽  
Memory Function ◽  
Nmda Receptor Antagonist ◽  
Inhibitory Neurons ◽  
Natural Behavior ◽  
Neuronal Populations ◽  
Memory Representations ◽  
Decoding Accuracy

SummaryThe primate lateral prefrontal cortex (LPFC) is considered fundamental for temporarily maintaining and manipulating mental representations that serve behavior, a cognitive function known as working memory1. Studies in non-human primates have shown that LPFC lesions impair working memory2 and that LPFC neuronal activity encodes working memory representations3. However, such studies have used simple displays and constrained gaze while subjects held information in working memory3, which put into question their ethological validity4,5. Currently, it remains unclear whether LPFC microcircuits can support working memory function during natural behavior. We tested macaque monkeys in a working memory navigation task in a life-like virtual environment while their gaze was unconstrained. We show that LPFC neuronal populations robustly encode working memory representations in these conditions. Furthermore, low doses of the NMDA receptor antagonist, ketamine, impaired working memory performance while sparing perceptual and motor skills. Ketamine decreased the firing of narrow spiking inhibitory interneurons and increased the firing of broad spiking cells reducing population decoding accuracy for remembered locations. Our results show that primate LPFC generates robust neural codes for working memory in naturalistic settings and that such codes rely upon a fine balance between the activation of excitatory and inhibitory neurons.

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