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Changes in Local Network Activity Approximated by Reverse Spike-Triggered Local Field Potentials Predict the Focus of Attention
Author(s) -
Abdelrahman Sharafeldin,
Vanessa L. Mock,
Stephen Meisenhelter,
Jacqueline R. HembrookShort,
Farran Briggs
Publication year - 2020
Publication title -
cerebral cortex communications
Language(s) - English
Resource type - Journals
ISSN - 2632-7376
DOI - 10.1093/texcom/tgaa014
Subject(s) - local field potential , wavelet , pattern recognition (psychology) , artificial intelligence , neuroscience , computer science , visual cortex , receptive field , stimulus (psychology) , psychology , cognitive psychology
The effects of visual spatial attention on neuronal firing rates have been well characterized for neurons throughout the visual processing hierarchy. Interestingly, the mechanisms by which attention generates more or fewer spikes in response to a visual stimulus remain unknown. One possibility is that attention boosts the likelihood that synaptic inputs to a neuron result in spikes. We performed a novel analysis to measure local field potentials (LFPs) just prior to spikes, or reverse spike-triggered LFP “wavelets,” for neurons recorded in primary visual cortex (V1) of monkeys performing a contrast change detection task requiring covert shifts in visual spatial attention. We used dimensionality reduction to define LFP wavelet shapes with single numerical values, and we found that LFP wavelet shape changes correlated with changes in neuronal firing rate. We then tested whether a simple classifier could predict monkeys’ focus of attention from LFP wavelet shape. LFP wavelet shapes sampled in discrete windows were predictive of the locus of attention for some neuronal types. These findings suggest that LFP wavelets are a useful proxy for local network activity influencing spike generation, and changes in LFP wavelet shape are predictive of the focus of attention.

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