Evidence map›Paper›PMID 33584234›Full record

ArticleFrontiers in computational neuroscience2020

Predicting Grating Orientations With Cross-Frequency Coupling and Least Absolute Shrinkage and Selection Operator in V1 and V4 of Rhesus Monkeys.

Zhaohui Li, Yue Du, Youben Xiao, Liyong Yin

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Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhaohui LiSchool of Information Science and Engineering, Yanshan University, Qinhuangdao, China.
Yue DuSchool of Information Science and Engineering, Yanshan University, Qinhuangdao, China.
Youben XiaoSchool of Information Science and Engineering, Yanshan University, Qinhuangdao, China.
Liyong YinDepartment of Neurology, The First Hospital of Qinhuangdao, Qinhuangdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Orientation selectivity, as an emergent property of neurons in the visual cortex, is of critical importance in the processing of visual information. Characterizing the orientation selectivity based on neuronal firing activities or local field potentials (LFPs) is a hot topic of current research. In this paper, we used cross-frequency coupling and least absolute shrinkage and selection operator (LASSO) to predict the grating orientations in V1 and V4 of two rhesus monkeys. The experimental data were recorded by utilizing two chronically implanted multi-electrode arrays, which were placed, respectively, in V1 and V4 of two rhesus monkeys performing a selective visual attention task. The phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC) were employed to characterize the cross-frequency coupling of LFPs under sinusoidal grating stimuli with different orientations. Then, a LASSO logistic regression model was constructed to predict the grating orientation based on the strength of PAC and AAC. Moreover, the cross-validation method was used to evaluate the performance of the model. It was found that the average accuracy of the prediction based on the combination of PAC and AAC was 73.9%, which was higher than the predicting accuracy with PAC or AAC separately. In conclusion, a LASSO logistic regression model was introduced in this study, which can predict the grating orientations with relatively high accuracy by using PAC and AAC together. Our results suggest that the principle behind the LASSO model is probably an alternative direction to explore the mechanism for generating orientation selectivity.

Indexed as

cross-frequency couplingLASSOlocal field potentialorientation selectivityvisual cortex

Identifiers

PMID33584234
PMCPMC7874040

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