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Results for “recurrence timing”

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PubMed2002

On unique representations of certain dynamical systems produced by continuous-time recurrent neural networks.

This article extends previous mathematical studies on elucidating the redundancy for describing functions by feedforward neural networks (FNNs) to the elucidation of redundancy for describing dynamical systems (DSs) by continuous-time recurrent neural networks (RNNs). In order to approximate a DS on R(n) using an RNN with n visible units, an n-dimensional affine neural dynamical system (A-NDS) can be used as the DS actually produced by the above RNN under an affine map from its visible state-space R(n) to its hidden state-space. Therefore, we consider the problem of clarifying the redundancy for describing A-NDSs by RNNs and affine maps. We clarify to what extent a pair of an RNN and an affine map is uniquely determined by its corresponding A-NDS and also give a nonredundant sufficient search set for the DS approximation problem based on A-NDS.

Journal Article↗
PubMed1993

Kin and nursing home lengths of stay: a backward recurrence time approach.

There are numerous hypotheses about the role played by kin in decreasing the length of elderly persons' nursing home stays, yet few studies have explicitly examined the relationship between kin and episode length. Here we use backward recurrence time data from the Current Resident File of the 1985 National Nursing Home Survey to estimate models in which the hazard of leaving a nursing home depends upon covariates . Women admitted at age 65 or older stay, on average, 26 months in an institution, while men have an average stay of 19 months. Controlling for demographic factors, insurance status, and various chronic and morbid conditions, we find that, on average, having a living spouse decreases the length of stay by four months for men and three months for women. Having a living child decreases the mean length of stay for women by three months, but has no effect on the mean length of stay for men. Findings underscore the importance of family members in shortening the lengths of time spent by older persons in nursing homes.

Aged↗
PubMed2006

Parameter space structure of continuous-time recurrent neural networks.

A fundamental challenge for any general theory of neural circuits is how to characterize the structure of the space of all possible circuits over a given model neuron. As a first step in this direction, this letter begins a systematic study of the global parameter space structure of continuous-time recurrent neural networks (CTRNNs), a class of neural models that is simple but dynamically universal. First, we explicitly compute the local bifurcation manifolds of CTRNNs. We then visualize the structure of these manifolds in net input space for small circuits. These visualizations reveal a set of extremal saddle node bifurcation manifolds that divide CTRNN parameter space into regions of dynamics with different effective dimensionality. Next, we completely characterize the combinatorics and geometry of an asymptotically exact approximation to these regions for circuits of arbitrary size. Finally, we show how these regions can be used to calculate estimates of the probability of encountering different kinds of dynamics in CTRNN parameter space.

Animals↗
PubMed2005

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

With the completion of the human and a few model organisms' genomes, and with the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time-based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Our method requires approximately 6 . N byte memory and a computational time of N log N to extract all the repeat-related and periodic or quasi-periodic features from a sequence of length N without any prior knowledge on the consensus sequence of those features, hence enables us to carry out sequence analysis on the whole genomic scale by a PC.

Algorithms↗
PubMed1990

Eleven times recurrences of a parasagittal falxmeningioma. Case report.

Although meningiomas are of benign character and generally of encapsulated growth, recurrence is a known problem in treatment. The authors present the time course of a recurrent parasagittal meningioma of the falx, which recurred eleven times. Despite modern radiological diagnostic methods, which made early diagnosis of recurrent tumour possible, and the use of modern microsurgical techniques with radical tumour extirpation and followed by radiotherapy, the fatal course of benign tumour disease could not be stopped.

Adult↗
PubMed1991

Predicting recurrence time of esophageal carcinoma through assessment of histologic factors and DNA ploidy.

Cytophotometric analysis of nuclear DNA content was done in 128 patients with squamous cell carcinoma of the esophagus. The relationship among histopathologic features, DNA distribution pattern, and survival time was investigated from the standpoint of recurrence. Of 128 patients, 77 (60.1%) died of recurrence within 2 years after surgery: 16 (12.5%) from 2 to 5 years and two (1.6%) over 5 years. The rate of death of recurrence within 2 years was higher in patients with T4 or N1 than T1, T2, and T3 or N0 (P less than 0.01). Survivors over 5 years more frequently possessed type II DNA pattern than types III and IV (P less than 0.05). The rate of death of recurrence within 2 years was 34.4% in type II, which was lower than the 59.6% rate in type III (P less than 0.05) and the 76.6% rate in type IV (P less than 0.01). Survivors from 2 to 5 years were higher in type III than in type IV (P less than 0.05), and recurrence over 5 years was found only in type II. This inclination was more apparent in those with curative resection. In the patients with type II, careful follow-up may be needed over 5 years for late recurrence. However, in those with type IV, no recurrence over 2 years could be regarded as healed because most of their recurrences occur within 2 years. These findings suggest that the growth rate of esophageal carcinoma should reflect DNA aneuploidy, and the DNA analysis of esophageal carcinoma should be a valuable parameter for postoperative follow-up planning.

Carcinoma, Squamous Cell↗
PubMed1997

The prediction of risk of recurrence and time to recurrence of hepatocellular carcinoma after orthotopic liver transplantation: a pilot study.

Orthotopic liver transplantation (OLTx) in the presence of hepatocellular carcinoma (HCC) has been complicated by high recurrence rates. The ability to determine the risk and timing of HCC recurrence on an individual basis would greatly aid in the candidate selection process resulting in a more efficient use of donated organs and allow the individualization and better evaluation of adjuvant chemotherapy. The 214 patients who underwent OLTx in the presence of HCC were analyzed. From the 178 patients who survived more than 150 days, 71 (40%) have suffered HCC recurrence. Based on five risk factors, that is, gender, tumor number, lobar tumor distribution, tumor size, grade of vascular invasion, artificial neural network models predicting the likelihood of HCC recurrence within 1, 2, and 3 consecutive years after transplantation were developed. Based on model predictions, those combinations of risk factors that should/should not lead to recurrence were generated, allowing stratification of patients into the following three groups: 1) patients who should not suffer HCC recurrence and who should not need adjuvant therapy, 2) patients who will suffer recurrence and for whom postoperative chemotherapy significantly prolonged survival (but did not prevent recurrence), and 3) patients who may or may not suffer HCC recurrence and whose recurrence may be prevented by adjuvant chemotherapy. The outcome of OLTx for patients with HCC can be prognosticated based on a number of clinical variables. If verified through multicenter trials, these models could be made available to transplantation programs performing OLTx in the presence of HCC.

Adolescent↗
PubMed2003

Adjuvant chemotherapy for transplanted hepatocellular carcinoma patients: impact on survival or HCV recurrence timing.

INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. In the Western world the current epidemic of cirrhosis due to the hepatitis C virus (HCV) is increasing the number of new cases. Liver transplantation (OLTx) represents a radical treatment for HCC and the underlying cirrhosis. Whether adjuvant chemotherapy is indicated in the postoperative period to prevent recurrence is controversial. MATERIAL AND PATIENTS: Forty-eight HCC patients underwent liver transplantation during 11 years, including 21 who were chemo-treated (CT) patients. Thirty-one patients (65%) had post-necrotic virus-C cirrhosis (PNC-C). Twenty-one cases (44%) were p-TNM stages III-IV, and 15 cases (31%) incidental HCC detected in the explanted liver. Seven HCV patients (15%) received chemotherapy (before 1998). RESULTS: One-, 3-, and 5-year overall survival rates were 100%, 85%, 79% (CT group), and 89%, 71%, 71% (no CT group), respectively. The HCV recurrence-free survival rates at 3, 6, and 12 months were 29%, 14%, 0% for the CT group, versus 76%, 38%, 25% for the no CT group (P =.005). CONCLUSIONS: Discontinuation of HCV-HCC patients by chemotherapeutic adjuvant protocols after transplantation appears rational due to the early hepatitis C recurrence confirmed in our series. Moreover, few studies have demonstrated that CT prolongs survival of HCC transplanted patients. New pharmacological approaches are necessary to solve these questions.

Adult↗
PubMed2004

Chronometric readout from a memory trace: gamma-frequency field stimulation recruits timed recurrent activity in the rat CA3 network.

Synchronous population activity is prevalent in neurones of the central nervous system and experimentally captured as oscillatory electric fields, the frequency of which can represent the state of the neural circuit, e.g. theta (approximately 5 Hz) and gamma (approximately 40 Hz). Such field oscillations, however, are not merely a result of coherent neuronal activity. They may also play active roles in information processing in the brain. In this study, we observed that, in cultured hippocampal slices, CA3 pyramidal cells responded to single-pulse stimuli with monosynaptic and polysynaptic potentials and firing spikes which occurred after variable latencies. The variability of the spike latencies was greatly reduced in the presence of weak electric field oscillations, especially the oscillation in the gamma-band frequency range, that per se induced only small fluctuations in the subthreshold membrane potential, and this effect was inhibited by blockade of NMDA receptor activity. Furthermore, the latency of the firing spikes changed if the stimulus was applied at a different phase of the imposed gamma oscillations. These results may suggest that the background field oscillations serve as an extracellular time reference and assure accurate and stable decoding of a memory trace present in cortical feedback networks.

Action Potentials↗
PubMed2001

Attractive periodic sets in discrete-time recurrent networks (with emphasis on fixed-point stability and bifurcations in two-neuron networks).

We perform a detailed fixed-point analysis of two-unit recurrent neural networks with sigmoid-shaped transfer functions. Using geometrical arguments in the space of transfer function derivatives, we partition the network state-space into distinct regions corresponding to stability types of the fixed points. Unlike in the previous studies, we do not assume any special form of connectivity pattern between the neurons, and all free parameters are allowed to vary. We also prove that when both neurons have excitatory self-connections and the mutual interaction pattern is the same (i.e., the neurons mutually inhibit or excite themselves), new attractive fixed points are created through the saddle-node bifurcation. Finally, for an N-neuron recurrent network, we give lower bounds on the rate of convergence of attractive periodic points toward the saturation values of neuron activations, as the absolute values of connection weights grow.

Mathematics↗