Stochastic optimized control
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The structure of food webs is frequently described using phenomenological stochastic models. A prominent example, the niche model, was found to produce artificial food webs resembling real food webs according to a range of summary statistics. However, the size structure of food webs generated by the niche model and real food webs has not yet been rigorously compared. To fill this void, I use a body mass based version of the niche model and compare prey-predator body mass allometry and predator-prey body mass ratios predicted by the model to empirical data. The results show that the model predicts weaker size structure than observed in many real food webs. I introduce a modified version of the niche model which allows to control the strength of size-dependence of predator-prey links. In this model, optimal prey body mass depends allometrically on predator body mass and on a second trait, such as foraging mode. These empirically motivated extensions of the model allow to represent size structure of real food webs realistically and can be used to generate artificial food webs varying in several aspects of size structure in a controlled way. Hence, by explicitly including the role of species traits, this model provides new opportunities for simulating the consequences of size structure for food web dynamics and stability.
Objective: Conventional selection of pre-ictal EEG epochs for seizure prediction algorithm training data typically assumes a continuous pre-ictal brain state preceding a seizure. This is carried out by defining a fixed duration, pre-ictal time period before seizures from which pre-ictal training data epochs are uniformly sampled. However, stochastic physiological and pathological fluctuations in EEG data characteristics and underlying brain states suggest that pre-ictal state dynamics may be more complex, and selection of pre-ictal training data segments to reflect this could improve algorithm performance. Methods: We propose a semi-supervised technique to select pre-ictal training data most distinguishable from interictal EEG according to pre-specified data characteristics. The proposed method uses hierarchical clustering to identify optimal pre-ictal data epochs. Results: In this paper we compare the performance of a seizure forecasting algorithm with and without hierarchical clustering of pre-ictal periods in chronic iEEG recordings from six canines with naturally occurring epilepsy. Hierarchical clustering of training data improved results for Time In Warning (TIW) (0.18 vs. 0.23) and False Positive Rate (FPR) (0.5 vs. 0.59) when evaluated across all subjects (p<0.001, n=6). Results were mixed when evaluating TIW, FPR, and Sensitivity for individual dogs. Conclusion: Hierarchical clustering is a helpful method for training data selection overall, but should be evaluated on a subject-wise basis. Significance: The clustering method can be used to optimize results of forecasting towards sensitivity or TIW or FPR, and therefore can be useful for epilepsy management.
- Publikační typ
- časopisecké články MeSH
... fundamental theorem of simulation -- There are five completely new chapters that cover Monte Carlo control ... ... -- 2.1.1 Uniform Simulation 36 r 2.1.2 The Inverse Transform 38 i 2.1.3 Alternatives 40 -- 2.1.4 Optimal ... ... 157 -- 5.1 Introduction 157 -- 5.2 Stochastic Exploration 159 -- 5.2.1 A Basic Solution 159 -- 5.2.2 ... ... Gradient Methods 162 -- 5.2.3 Simulated Annealing 163 -- 5.2.4 Prior Feedback 169 -- 5.3 Stochastic ... ... and Control 292 -- 7.6.1 Optimizing the Acceptance Rate 292 -- 7.6.2 Conditioning and Accelerations ...
Springer texts in statistics
2nd ed. xxx, 645 s., grafy
... Deconvolution Using the FFT 641 -- 13.2 Correlation and Autocorrelation Using the FFT 648 -- 13.3 Optimal ... ... Differential Equations 899 -- 17.0 Introduction 899 -- 17.1 Runge-Kutta Method 907 -- 17.2 Adaptive Stepsize Control ... ... Sets of Equations 931 -- 17.6 Multistep, Multivalue, and Predictor-Corrector Methods 942 -- 17.7 Stochastic ...
3rd ed. xxi, 1235 s. : il. ; 27 cm + 1 CD-ROM
- MeSH
- matematické výpočty počítačové MeSH
- matematika MeSH
- numerická analýza pomocí počítače * MeSH
- Publikační typ
- monografie MeSH
... Computing the Effect of Interventions 72 -- 3.2.4 Identification of Causal Quantities 77 -- 3.3 Controlling ... ... in Decision Analysis 110 -- 4.1.3 Actions and Counterfactuals 112 -- 4.2 Conditional Actions and Stochastic ... ... Identification 114 -- 4.3.2 Remarks on Efficiency 116 -- 4.3.3 Deriving a Closed-Form Expression for Control ... ... Bounding Causal Effects with Instrumental Variables 262 -- 8.2.1 Problem Formulation: Constrained Optimization ...
1st ed. xii, 384 s.
- MeSH
- kauzalita MeSH
- pravděpodobnost MeSH
- Konspekt
- Přírodní vědy. Matematické vědy
- NLK Obory
- přírodní vědy
- statistika, zdravotnická statistika
Throughout life, sensory systems adapt to the sensory environment to provide optimal responses to relevant tasks. In the case of a developing system, sensory inputs induce changes that are permanent and detectable up to adulthood. Previously, we have shown that rearing rat pups in a complex acoustic environment (spectrally and temporally modulated sound) from postnatal day 14 (P14) to P28 permanently improves the response characteristics of neurons in the inferior colliculus and auditory cortex, influencing tonotopical arrangement, response thresholds and strength, and frequency selectivity, along with stochasticity and the reproducibility of neuronal spiking patterns. In this study, we used a set of behavioral tests based on a recording of the acoustic startle response (ASR) and its prepulse inhibition (PPI), with the aim to extend the evidence of the persistent beneficial effects of the developmental acoustical enrichment. The enriched animals were generally not more sensitive to startling sounds, and also, their PPI of ASR, induced by noise or pure tone pulses, was comparable to the controls. They did, however, exhibit a more pronounced PPI when the prepulse stimulus was represented either by a change in the frequency of a background tone or by a silent gap in background noise. The differences in the PPI of ASR between the enriched and control animals were significant at lower (55 dB SPL), but not at higher (65-75 dB SPL), intensities of background sound. Thus, rearing pups in the acoustically enriched environment led to an improvement of the frequency resolution and gap detection ability under more difficult testing conditions, i.e., with a worsened stimulus clarity. We confirmed, using behavioral tests, that an acoustically enriched environment during the critical period of development influences the frequency and temporal processing in the auditory system, and these changes persist until adulthood.
- MeSH
- akustická stimulace metody MeSH
- kritické období (psychologie) * MeSH
- krysa rodu rattus MeSH
- novorozená zvířata MeSH
- potkani Long-Evans MeSH
- rozlišení výšky zvuku fyziologie MeSH
- sluchová percepce fyziologie MeSH
- sluchové kmenové evokované potenciály fyziologie MeSH
- úleková reakce fyziologie MeSH
- věkové faktory MeSH
- životní prostředí * MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
