ArticleCognitive neurodynamics2019
Functional and effective connectivity based features of EEG signals for object recognition.
Article in Cognitive neurodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- A two-person neuroscience perspective on parent-infant dyadic expansion of consciousness.Frontiers in human neuroscience · 2026Article
- Develop an emotion recognition system using jointly connectivity between electroencephalogram and electrocardiogram signals.Heliyon · 2025Article
- EEG Signals Classification Related to Visual Objects Using Long Short-Term Memory Network and Nonlinear Interval Type-2 Fuzzy Regression.Brain topography · 2025Article
- EEG synchronization signatures for decoding attentional states during continuous force control.Frontiers in neuroscience · 2025Article
- Correlates of implicit semantic processing as revealed by representational similarity analysis applied to EEG.iScience · 2024Article
- Age-related changes in human brain functional connectivity using graph theory and machine learning techniques in resting-state fMRI data.GeroScience · 2024Article
- Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.Biomedical engineering online · 2024Article
- The applied principles of EEG analysis methods in neuroscience and clinical neurology.Military Medical Research · 2023Review
- Automatic Seizure Detection and Prediction Based on Brain Connectivity Features and a CNNs Meet Transformers Classifier.Brain sciences · 2023Article
- Spatial-temporal graph convolutional network for Alzheimer classification based on brain functional connectivity imaging of electroencephalogram.Human brain mapping · 2022Article
- Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals.Cognitive neurodynamics · 2022Article
- A Novel Approach for Segment-Length Selection Based on Stationarity to Perform Effective Connectivity Analysis Applied to Resting-State EEG Signals.Sensors (Basel, Switzerland) · 2022Article
- EEG Connectivity during Active Emotional Musical Performance.Sensors (Basel, Switzerland) · 2022Article
- Three-Level Distributed Real-Time Monitoring of Construction near Underground Infrastructure Using a Combined Intelligent Method.Sensors (Basel, Switzerland) · 2022Article
- Brain functional and effective connectivity based on electroencephalography recordings: A review.Human brain mapping · 2022Review
- Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coupling for Human EEG After Stroke.Frontiers in computational neuroscience · 2022Article
- A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test.Cognitive neurodynamics · 2021Article
- Neural computing in four spatial dimensions.Cognitive neurodynamics · 2021Article
- Influence of Sliding Time Window Size Selection Based on Heart Rate Variability Signal Analysis on Intelligent Monitoring of Noxious Stimulation under Anesthesia.Neural plasticity · 2021Article
- Research on Recognition of Motor Imagination Based on Connectivity Features of Brain Functional Network.Neural plasticity · 2021Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Classifying different object categories is one of the most important aims of brain-computer interface researches. Recently, interactions between brain regions were studied using different methods, such as functional and effective connectivity techniques. Functional and effective connectivity techniques are applied to estimate human brain areas connectivity. The main purpose of this study is to compare classification accuracy of the most advanced functional and effective methods in order to classify 12 basic object categories using Electroencephalography (EEG) signals. In this paper, 19 channels EEG signals were collected from 10 healthy subjects; when they were visiting color images and instructed to select the target images among others. Correlation, magnitude square coherence, wavelet coherence (WC), phase synchronization and mutual information were applied to estimate functional cortical connectivity. On the other hand, directed transfer function, partial directed coherence, generalized partial directed coherence (GPDC) were used to obtain effective cortical connectivity. After feature extraction, the scalar feature selection methods including T-test and one-sided-anova were applied to rank and select the most informative features. The selected features were classified by a one-against-one support vector machine classifier. The results indicated that the use of different techniques led to different classifying accuracy and brain lobes analysis. WC and GPDC are the most accurate methods with performances of 80.15% and 64.43%, respectively.
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