15 research outputs found

    The type of ploidy of chrysanthemum is not black or white: a comparison of a molecular approach to published cytological methods

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    Polyploidy is a widespread phenomenon among higher plants and a major factor shaping the structure and evolution of plant genomes. The important ornamental chrysanthemum (Chrysanthemum indicum hybrid) possesses a hexaploid genome with 54 chromosomes and was classified based on its evolutionary origin and cytological methods as an allopolyploid. However, it is questionable whether cytological methods are sufficient to determine the type of ploidy, and there are more informative methods available based on molecular marker analyses. Therefore, we collected segregation data for 406 dominant molecular marker alleles [327 amplified fragment length polymorphism (AFLPs), 65 single-strand conformation polymorphism (SSCPs) and 14 microsatellites (EST-SSRs)] in a biparental F1 population of 160 individuals. We analyzed these data for the characteristics that differ between allopolyploids and autopolyploids, including the segregation ratio of each marker, the ratio of single-dose (SD) to multi-dose (MD) markers, the ratio of SD markers in coupling to those in repulsion and the banding patterns of the SSRs. Whereas the analysis of the segregation ratio of each polymorphic marker indicated disomic (13 markers) as well as hexasomic (eight markers) inheritance, the ratio of SD markers in coupling to those in repulsion was 1:0, which is characteristic of autopolyploids. The observed ratio of SD to MD markers was 0.67:0.33 which is significantly different to the expected segregation for auto- and allohexaploids. Furthermore, the three EST-SSR alleles were inherited in all possible combinations and were not independent of each other, as expected for fixed heterozygosity in allopolyploids. Combining our results with published cytological data indicates that cultivated chrysanthemums should be classified as segmental allohexaploids.BMEL

    Brain oscillations track the formation of episodic memories in the real world

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    Despite the well-known influence of environmental context on episodic memory, little has been done to increase contextual richness within the lab. This leaves a blind spot lingering over the neuronal correlates of episodic memory formation in day-to-day life. To address this, we presented participants with a series of words to memorise along a pre-designated route across campus while a mobile EEG system acquired ongoing neural activity. Replicating lab-based subsequent memory effects (SMEs), we identified significant low to mid frequency power decreases (<30 Hz), including beta power decreases over the left inferior frontal gyrus. When investigating the oscillatory correlates of temporal and spatial context binding, we found that items strongly bound to spatial context exhibited significantly greater theta power decreases than items strongly bound to temporal context. These findings expand upon lab-based studies by demonstrating the influence of real world contextual factors that underpin memory formation

    How a co-actor’s task affects monitoring of own errors: evidence from a social event-related potential study

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    Efficient flexible behavior requires continuous monitoring of performance for possible deviations from the intended goal of an action. This also holds for joint action. When jointly performing a task, one needs to not only know the other’s goals and intentions but also generate behavioral adjustments that are dependent on the other person’s task. Previous studies have shown that in joint action people not only represent their own task but also the task of their co-actor. The current study investigated whether these so-called shared representations affect error monitoring as reflected in the response-locked error-related negativity (Ne/ERN) following own errors. Sixteen pairs of participants performed a social go/no-go task, while EEG and behavioral data were obtained. Responses were compatible or incompatible relative to the go/no-go action of the co-actor. Erroneous responses on no-go stimuli were examined. The results demonstrated increased Ne/ERN amplitudes and longer reaction times following errors on compatible compared to incompatible no-go stimuli. Thus, Ne/ERNs were larger after errors on trials that did not require a response from the co-actor either compared to errors on trials that did require a response from the co-actor. As the task of the other person is the only difference between these two types of errors, these findings show that people also represent their co-actor’s task during error monitoring in joint action. An extension of existing models on performance monitoring in individual action is put forward to explain the current findings in joint action. Importantly, we propose that inclusion of a co-actor’s task in performance monitoring may facilitate adaptive behavior in social interactions enabling fast anticipatory and corrective actions

    Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

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    Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.</p

    Event-Related Potentials Measured From In and Around the Ear Electrodes Integrated in a Live Hearing Device for Monitoring Sound Perception

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    Future hearing devices could exploit brain signals of the user derived from electroencephalography (EEG) measurements, for example, for fitting the device or steering signal enhancement algorithms. While previous studies have shown that meaningful brain signals can be obtained from ear-centered EEG electrodes, we here present a feasibility study where ear-EEG is integrated with a live hearing device. Seventeen normal-hearing participants were equipped with an individualized in-the-ear hearing device and an ear-EEG system that included 10 electrodes placed around the ear (cEEGrid) and 3 electrodes spread out in the concha. They performed an auditory discrimination experiment, where they had to detect an audible switch in the signal processing settings of the hearing device between repeated presentations of otherwise identical stimuli. We studied two aspects of the ear-EEG data: First, whether the switches in the hearing device settings can be identified in the brain signals, specifically event-related potentials. Second, we evaluated the signal quality for the individual electrode positions. The EEG analysis revealed significant differences between trials with and without a switch in the device settings in the N100 and P300 range of the event-related potential. The comparison of electrode positions showed that the signal quality is better for around-the-ear electrodes than for in-concha electrodes. These results confirm that meaningful brain signals related to the settings of a hearing device can be acquired from ear-EEG during real-time audio processing, particularly if electrodes around the ear are available

    Event-Related Potentials Measured From In and Around the Ear Electrodes Integrated in a Live Hearing Device for Monitoring Sound Perception

    No full text
    Future hearing devices could exploit brain signals of the user derived from electroencephalography (EEG) measurements, for example, for fitting the device or steering signal enhancement algorithms. While previous studies have shown that meaningful brain signals can be obtained from ear-centered EEG electrodes, we here present a feasibility study where ear-EEG is integrated with a live hearing device. Seventeen normal-hearing participants were equipped with an individualized in-the-ear hearing device and an ear-EEG system that included 10 electrodes placed around the ear (cEEGrid) and 3 electrodes spread out in the concha. They performed an auditory discrimination experiment, where they had to detect an audible switch in the signal processing settings of the hearing device between repeated presentations of otherwise identical stimuli. We studied two aspects of the ear-EEG data: First, whether the switches in the hearing device settings can be identified in the brain signals, specifically event-related potentials. Second, we evaluated the signal quality for the individual electrode positions. The EEG analysis revealed significant differences between trials with and without a switch in the device settings in the N100 and P300 range of the event-related potential. The comparison of electrode positions showed that the signal quality is better for around-the-ear electrodes than for in-concha electrodes. These results confirm that meaningful brain signals related to the settings of a hearing device can be acquired from ear-EEG during real-time audio processing, particularly if electrodes around the ear are available
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