Dataset Information

Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions.

ABSTRACT: Objective: Phase transfer entropy (TEθ) methods perform well in animal sensory-spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the TEθ methods. Specifically, four TEθ methods are applied to the simulated signals generated by a neural mass model and the actual neural data from ferrets with known interaction properties to investigate the accuracy, stability, and computational complexity of the TEθ methods in identifying the directional coupling. Then, the most suitable method is selected based on the performance baseline and used on the local field potential recorded from pigeons to detect the interaction between the hippocampus (Hp) and nidopallium caudolaterale (NCL) in visual-spatial associative learning. Results: (1) This paper obtains a performance baseline table that contains the most suitable method for different scenarios. (2) The TEθ method identifies an information flow preferentially from Hp to NCL of pigeons at the θ band (4-12 Hz) in visual-spatial associative learning. Significance: These outcomes provide a reference for the TEθ methods in detecting the interactions between brain areas.

SUBMITTER: Zhu JY

PROVIDER: S-EPMC10378602 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions.

Zhu Jun-Yao JY Li Meng-Meng MM Zhang Zhi-Heng ZH Liu Gang G Wan Hong H

Entropy (Basel, Switzerland) 20230629 7

Objective: Phase transfer entropy (TEθ) methods perform well in animal sensory-spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the TEθ methods. Specifically, four TEθ methods are applied to the simulated signals generated by a neural mass model and the actual neural data from ferrets with known interaction properties to investigate the accuracy, ...[more]

PMID: 37509941

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Project description:BACKGROUND: Epistasis is recognized fundamentally important for understanding the mechanism of disease-causing genetic variation. Though many novel methods for detecting epistasis have been proposed, few studies focus on their comparison. Undertaking a comprehensive comparison study is an urgent task and a pathway of the methods to real applications. RESULTS: This paper aims at a comparison study of epistasis detection methods through applying related software packages on datasets. For this purpose, we categorize methods according to their search strategies, and select five representative methods (TEAM, BOOST, SNPRuler, AntEpiSeeker and epiMODE) originating from different underlying techniques for comparison. The methods are tested on simulated datasets with different size, various epistasis models, and with/without noise. The types of noise include missing data, genotyping error and phenocopy. Performance is evaluated by detection power (three forms are introduced), robustness, sensitivity and computational complexity. CONCLUSIONS: None of selected methods is perfect in all scenarios and each has its own merits and limitations. In terms of detection power, AntEpiSeeker performs best on detecting epistasis displaying marginal effects (eME) and BOOST performs best on identifying epistasis displaying no marginal effects (eNME). In terms of robustness, AntEpiSeeker is robust to all types of noise on eME models, BOOST is robust to genotyping error and phenocopy on eNME models, and SNPRuler is robust to phenocopy on eME models and missing data on eNME models. In terms of sensitivity, AntEpiSeeker is the winner on eME models and both SNPRuler and BOOST perform well on eNME models. In terms of computational complexity, BOOST is the fastest among the methods. In terms of overall performance, AntEpiSeeker and BOOST are recommended as the efficient and effective methods. This comparison study may provide guidelines for applying the methods and further clues for epistasis detection.

Project description:BackgroundSensitive methods for detecting asymptomatic malaria infections are essential for identifying potential transmission reservoirs and obtaining an accurate assessment of malaria epidemiology in low-endemicity areas aiming to eliminate malaria. PCR techniques to detect parasite nucleic acids (DNA or RNA) are among the most commonly used molecular methods. However, most of these methods are of low throughput and cannot be used for large-scale molecular epidemiological studies. A recently developed capture and ligation probe-PCR (CLIP-PCR) is claimed to have the sensitivity of molecular techniques and the high throughput capacity needed for screening purposes. This study aimed to compare several molecular methods for detecting asymptomatic and submicroscopic Plasmodium infections in healthy residents of a malaria-hypoendemic region in Southeast Asia, where malaria elimination is in sight.MethodThis study compared three molecular detection methods side-by-side, namely nested PCR targeting the rRNA genes, nested RT-PCR to detect parasite rRNA, and CLIP-PCR to detect parasite rRNA in 1005 healthy individuals in northeastern Myanmar. For nested PCR and RT-PCR, parasite DNA and total RNA were extracted from ~100 µL of blood, whereas RNA used for CLIP-PCR was from a 3 mm disk of dried blood filter paper. The sensitivity and specificity of these methods were compared with those of conventional light microscopy. In addition, RT-PCR and quantitative RT-PCR (qRT-PCR) targeting the Pvs25 gene in Plasmodium vivax were used to assess gametocyte prevalence in the samples.ResultsLight microscopy detected Plasmodium infections in only 1.19% of the residents harbouring the parasites. CLIP-PCR had slightly better performance and detected Plasmodium infections in 1.89% of the population. Further improvement was achieved by nested PCR to detect parasite DNA, which detected P. vivax and Plasmodium falciparum infections in 2.39% of the residents. The nested RT-PCR targeting rRNA, however, detected as many as 187 (18.61%) individuals having Plasmodium infections with P. vivax being the predominant species (176 P. vivax, 5 P. falciparum and 6 P. falciparum/P. vivax mixed infections). Of the 210 Plasmodium-positive samples detected by all molecular methods, 115 were Pvs25-positive by qRT-PCR, indicating that a large proportion of asymptomatic individuals were gametocyte carriers.ConclusionNested RT-PCR based on the detection of asexual-stage parasite rRNA was the most sensitive, with a more than sixfold higher sensitivity than the other two molecular methods of parasite detection. CLIP-PCR has an increased throughput, but its sensitivity in this study was much lower than those of other molecular methods, which may be partially due to the smaller amount of RNA input used.

Dataset Information

Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions.

Publications

Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions.

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