Investigating the propagation from meteorological to hydrological drought by introducing the nonlinear dependence with directed information transfer index

Author(s):  
Zhaoqiang Zhou ◽  
Haiyun Shi ◽  
Qiang Fu ◽  
Yibo Ding ◽  
Tianxiao Li ◽  
...  
Author(s):  
Nilotpal Debbarma ◽  
Parthasarathi Choudhury ◽  
Parthajit Roy

Abstract Non availability of adequate extreme rainfall information at any place of interest are solved using regionalization where subjective grouping of similar attributes of nearby gauged stations is performed. K-Means and Fuzzy C-Means are commonly used methods in regionalization of rainfall, but application of genetic algorithm is very rarely explored. Genetic algorithms (GA) are highly efficient evolutionary algorithms, and through an appropriate objective function can effectively achieve the purpose of clustering. In the present study, Davies-Bouldin index is considered and validation is performed using a set of validation measures. Taking into account the varied output obtained in each validation measure, an ensembled approach involving multi criteria decision making is applied to obtain optimal ranked solutions, and the procedure is extended to K-Means and Fuzzy C-Means for comparision. From the results obtained, GA based clustering is found to outperform other two algorithms in formation of homogenous regions with better performances in leave-one-out cross validation (LOOCV) test and sensitivity analysis. Accuracy of regional growth curves of regions assessed using regional relative bias and RMSE suggest low uncertainty and accurate quantile estimates in GA regions. Further, information transfer index based on entropy evaluated among GA regions is found to be highest and K-Means lowest.


Engineering ◽  
2013 ◽  
Vol 05 (10) ◽  
pp. 57-61
Author(s):  
Ping Xie ◽  
Peipei Ma ◽  
Xiaoling Chen ◽  
Xiaoli Li ◽  
Yuping Su

2009 ◽  
Vol 48 (01) ◽  
pp. 18-28 ◽  
Author(s):  
M. Ungureanu ◽  
C. Ligges ◽  
D. Hemmelmann ◽  
T. Wüstenberg ◽  
J. Reichenbach ◽  
...  

Summary Objectives: The main objective is to show current topics and future trends in the field of medical signal processing which are derived from current research concepts. Signal processing as an integrative concept within the scope of medical informatics is demonstrated. Methods: For all examples time-variant multivariate autoregressive models were used. Based on this modeling, the concept of Granger causality in terms of the time-variant Granger causality index and the time-variant partial directed coherence was realized to investigate directed information transfer between different brain regions. Results: Signal informatics encompasses several diverse domains including: processing steps, methodologies, levels and subject fields, and applications. Five trends can be recognized and in order to illustrate these trends, three analysis strategies derived from current neuroscientific studies are presented. These examples comprise high-dimensional fMRI and EEG data. In the first example, the quantification of time-variant-directed information transfer between activated brain regions on the basis of fast-fMRI data is introduced and discussed. The second example deals with the investigation of differences in word processing between dyslexic and normal reading children. Different dynamic neural networks of the directed information transfer are identified on the basis of event-related potentials. The third example shows time-variant cortical connectivity networks derived from a source model. Conclusions: These examples strongly emphasize the integrative nature of signal informatics, encompassing processing steps, methodologies, levels and subject fields, and applications.


2021 ◽  
Author(s):  
Francisco García-Rosales ◽  
Luciana López-Jury ◽  
Eugenia Gonzalez-Palomares ◽  
Johannes Wetekam ◽  
Yuranny Cabral-Calderín ◽  
...  

AbstractThe mammalian frontal and auditory cortices are fundamental structures supporting vocal production, yet the dynamics of information exchange between these regions during vocalization are unknown. Here, we tackle this issue by means of electrophysiological recordings in the fronto-auditory network of freely-vocalizing Carollia perspicillata bats. We find that oscillations in frontal and auditory cortices provide correlates of vocal production with complementary patterns across structures. Causality analyses of oscillatory activity revealed directed information exchange in the network, predominantly of top-down nature (frontal to auditory). Such directed connectivity was dynamic, as it depended on the type of vocalization produced, and on the timing relative to vocal onset. Remarkably, we observed the emergence of bottom-up information transfer only when bats produced calls with evident post-vocal consequences (echolocation pulses). Our results link vocal production to dynamic information transfer between sensory (auditory) and association areas in a highly vocal mammalian animal model.


2006 ◽  
Vol 45 (06) ◽  
pp. 643-650 ◽  
Author(s):  
L. Leistritz ◽  
W. Hesse ◽  
T. Wüstenberg ◽  
C. Fitzek ◽  
J. R. Reichenbach ◽  
...  

Summary Objectives: Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients. In this investigation, the focus centers on distinguishing between brain areas with normal and reduced perfusion on the basis of the dynamics of contrast agent inflow and washout. Methods: Fast fMRI sequences were analyzed with time-variant Granger causality (tvGC). The tvGC is based on a time-variant autoregressive model and is used for the quantification of the directed information transfer between activated brain areas. Generalized Dynamic Neural Networks (GDNN) with time-variant weights were applied on dynamic contrast agent MRI sequences as a nonlinear operator in order to enhance differences in the signal courses of pixels of normal and injured tissues. Results: A simple motor task (self-paced finger tapping) is used in an fMRI design to investigate directed interactions between defined brain areas. A significant information transfer can be determined for the direction primary motor cortex to supplementary motor area during a short time period of about five seconds after stimulus. The analysis of dynamic contrast agent MRI sequences demonstrates that the trained GDNN enables a reliable tissue classification. Three classes are of interest: normal tissue, tissue at risk for death, and dead tissue. Conclusions: The time-variant multivariate analysis of directed information transfer derived from fMRI sequences and the computation of perfusion maps by GDNN demonstrate that dynamic analysis methods are essential tools for 4D image analysis.


2014 ◽  
Vol 45 (1) ◽  
pp. 33-39 ◽  
Author(s):  
Daniele Marinazzo ◽  
Olivia Gosseries ◽  
Mélanie Boly ◽  
Didier Ledoux ◽  
Mario Rosanova ◽  
...  

2021 ◽  
Author(s):  
Francisco García-Rosales ◽  
Luciana López-Jury ◽  
Eugenia González-Palomarez ◽  
Johannes Wetekam ◽  
Yuranny Cabral-Calderin ◽  
...  

Abstract The mammalian frontal and auditory cortices are fundamental structures supporting vocal behaviour, yet the patterns of information exchange between these regions during vocalization remain unknown. Here, we address this issue by means of electrophysiological recordings in the fronto-auditory network of freely-vocalizing Carollia perspicillata bats. We show that oscillations in frontal and auditory cortices predict vocalization type with complementary patterns across structures. Transfer entropy analyses of oscillatory activity revealed directed information exchange in the circuit, predominantly of top-down nature (frontal to auditory). The dynamics of information flow depended on vocalization type and on the timing relative to vocal onset. Remarkably, we observed the emergence of predominant bottom-up information transfer, only when animals produced calls with imminent post-vocal consequences (echolocation signals). These results unveil changes of information flow in a large-scale sensory and association network associated to the behavioural consequences of vocalization in a highly vocal mammalian model.  


2011 ◽  
Vol 12 (Suppl 1) ◽  
pp. P18 ◽  
Author(s):  
Mikail Rubinov ◽  
Joseph Lizier ◽  
Mikhail Prokopenko ◽  
Michael Breakspear

2011 ◽  
Vol 106 (4) ◽  
pp. 2012-2023 ◽  
Author(s):  
Ana V. Cruz ◽  
Nicolas Mallet ◽  
Peter J. Magill ◽  
Peter Brown ◽  
Bruno B. Averbeck

Abnormal oscillatory synchrony is increasingly acknowledged as a pathophysiological hallmark of Parkinson's disease, but what promotes such activity remains unclear. We used novel, nonlinear time series analyses and information theory to capture the effects of dopamine depletion on directed information flow within and between the subthalamic nucleus (STN) and external globus pallidus (GPe). We compared neuronal activity recorded simultaneously from these nuclei in 6-hydroxydopamine-lesioned Parkinsonian rats with that in dopamine-intact control rats. After lesioning, both nuclei displayed pronounced augmentations of beta-frequency (∼20 Hz) oscillations and, critically, information transfer between STN and GPe neurons was increased. Furthermore, temporal profiles of the directed information transfer agreed with the neurochemistry of these nuclei, being “excitatory” from STN to GPe and “inhibitory” from GPe to STN. Separation of the GPe population in lesioned animals into “type-inactive” (GP-TI) and “type-active” (GP-TA) neurons, according to definitive firing preferences, revealed distinct temporal profiles of interaction with STN and each other. The profile of GP-TI neurons suggested their output is of greater causal significance than that of GP-TA neurons for the reduced activity that periodically punctuates the spiking of STN neurons during beta oscillations. Moreover, STN was identified as a key candidate driver for recruiting ensembles of GP-TI neurons but not GP-TA neurons. Short-latency interactions between GP-TI and GP-TA neurons suggested mutual inhibition, which could rhythmically dampen activity and promote anti-phase firing across the two subpopulations. Results thus indicate that information flow around the STN-GPe circuit is exaggerated in Parkinsonism and further define the temporal interactions underpinning this.


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